From 7f9f7ab3955aa3e0893966262017e7a1ab0a0fd5 Mon Sep 17 00:00:00 2001 From: Ben Hoover Date: Sat, 12 Jul 2025 15:45:31 -0400 Subject: [PATCH 1/2] Initialize .qmd version of hamux --- .gitignore | 3 + CONTRIBUTING.md | 0 LICENSE | 2 +- Makefile | 7 + README.md | 475 ++- assets/HyperSynapse-fig1.png | Bin 181905 -> 0 bytes assets/HypersynapseEnergy.png | Bin 23561 -> 0 bytes assets/LayerEnergy.png | Bin 58627 -> 0 bytes assets/SynapseEnergy.png | Bin 283020 -> 0 bytes assets/fig1.png | Bin 1226253 -> 0 bytes assets/logo.png | Bin 141366 -> 0 bytes environment.yml | 11 - examples/CIFAR 2layer Training.ipynb | 2848 ----------------- examples/MNIST 2layer Training.ipynb | 1476 --------- examples/classification.py | 343 -- examples/launch_classification.py | 63 - hamux/CONTRIBUTING.md | 46 - hamux/__init__.py | 10 +- hamux/core.py | 286 +- hamux/datasets.py | 212 -- hamux/ham.py | 200 -- hamux/lagrangians.py | 502 ++- hamux/layers.py | 120 - hamux/registry.py | 262 -- hamux/synapses.py | 383 --- hamux/tfjs_helpers.py | 129 - hamux/utils.py | 74 - nbs/.gitignore | 1 - nbs/00_core.qmd | 773 +++++ nbs/00_lagrangians.ipynb | 978 ------ nbs/01_lagrangians.qmd | 497 +++ nbs/01_layers.ipynb | 703 ---- nbs/02_synapses.ipynb | 689 ---- nbs/03_ham.ipynb | 1059 ------ nbs/04_registry.ipynb | 631 ---- nbs/05_tfjs.ipynb | 304 -- nbs/_quarto.yml | 4 + .../figures/HAMUX-header.png | Bin nbs/figures/HypersynapseOverview.png | Bin 0 -> 88135 bytes nbs/figures/NeuronOverview.png | Bin 0 -> 92423 bytes nbs/figures/hamux-undirected-synapses.png | Bin 0 -> 146202 bytes nbs/figures/hamux_overview.png | Bin 0 -> 445838 bytes nbs/ieee.csl | 400 +++ nbs/index.ipynb | 610 ---- nbs/index.qmd | 228 ++ nbs/nbdev.yml | 4 +- nbs/references.bib | 1390 +++++++- nbs/sidebar.yml | 7 +- pyproject.toml | 38 + requirements-dev.txt | 5 - scripts/build.sh | 21 + scripts/prep_pypi.py | 35 + scripts/sync_dependencies.py | 39 + settings.ini | 26 +- setup.py | 19 +- uv.lock | 2692 ++++++++++++++++ 56 files changed, 6870 insertions(+), 11735 deletions(-) create mode 100644 CONTRIBUTING.md create mode 100644 Makefile delete mode 100644 assets/HyperSynapse-fig1.png delete mode 100644 assets/HypersynapseEnergy.png delete mode 100644 assets/LayerEnergy.png delete mode 100644 assets/SynapseEnergy.png delete mode 100644 assets/fig1.png delete mode 100644 assets/logo.png delete mode 100644 environment.yml delete mode 100644 examples/CIFAR 2layer Training.ipynb delete mode 100644 examples/MNIST 2layer Training.ipynb delete mode 100644 examples/classification.py delete mode 100644 examples/launch_classification.py delete mode 100644 hamux/CONTRIBUTING.md delete mode 100644 hamux/datasets.py delete mode 100644 hamux/ham.py delete mode 100644 hamux/layers.py delete mode 100644 hamux/registry.py delete mode 100644 hamux/synapses.py delete mode 100644 hamux/tfjs_helpers.py delete mode 100644 hamux/utils.py delete mode 100644 nbs/.gitignore create mode 100644 nbs/00_core.qmd delete mode 100644 nbs/00_lagrangians.ipynb create mode 100644 nbs/01_lagrangians.qmd delete mode 100644 nbs/01_layers.ipynb delete mode 100644 nbs/02_synapses.ipynb delete mode 100644 nbs/03_ham.ipynb delete mode 100644 nbs/04_registry.ipynb delete mode 100644 nbs/05_tfjs.ipynb rename assets/header.png => nbs/figures/HAMUX-header.png (100%) create mode 100644 nbs/figures/HypersynapseOverview.png create mode 100644 nbs/figures/NeuronOverview.png create mode 100644 nbs/figures/hamux-undirected-synapses.png create mode 100644 nbs/figures/hamux_overview.png create mode 100644 nbs/ieee.csl delete mode 100644 nbs/index.ipynb create mode 100644 nbs/index.qmd create mode 100644 pyproject.toml delete mode 100644 requirements-dev.txt create mode 100644 scripts/build.sh create mode 100644 scripts/prep_pypi.py create mode 100644 scripts/sync_dependencies.py create mode 100644 uv.lock diff --git a/.gitignore b/.gitignore index 8d6689d..f35ba49 100644 --- a/.gitignore +++ b/.gitignore @@ -157,3 +157,6 @@ checklink/cookies.txt # Quarto .quarto +OLD/ + +*.ini.backup \ No newline at end of file diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md new file mode 100644 index 0000000..e69de29 diff --git a/LICENSE b/LICENSE index 261eeb9..3b106e8 100644 --- a/LICENSE +++ b/LICENSE @@ -186,7 +186,7 @@ same "printed page" as the copyright notice for easier identification within third-party archives. - Copyright [yyyy] [name of copyright owner] + Copyright 2022, fastai Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..17cda0d --- /dev/null +++ b/Makefile @@ -0,0 +1,7 @@ +.PHONY: pypi prepare + +pypi: + uv run python scripts/prep_pypi.py + +prepare: + uv run bash scripts/build.sh \ No newline at end of file diff --git a/README.md b/README.md index ee80a05..2fa1be7 100644 --- a/README.md +++ b/README.md @@ -1,9 +1,11 @@ -HAMUX -================ +# HAMUX + -HAMUX Logo +A new class of Deep Learning model built around **ENERGY**. + +![HAMUX Logo](./figures/HAMUX-header.png) Part proof-of-concept, part functional prototype, HAMUX is designed to bridge modern AI architectures and Hopfield Networks. @@ -11,13 +13,17 @@ bridge modern AI architectures and Hopfield Networks. **HAMUX**: A **H**ierarchical **A**ssociative **M**emory **U**ser e**X**perience. -[Documentation](https://bhoov.github.io/hamux) -[Github](https://github.com/bhoov/hamux) +[Documentation](https://bhoov.github.io/hamux). Also described in our +[tutorial on Associative Memory](https://arxiv.org/abs/2507.06211) +(ch. 3). -
- 🚧 HAMUX is under construction. Please checkout barebones-HAMUX in the meantime. -
+### Quickstart +The code in this codebase is meant to be as minimal as possible. *We do +not provide a complete component library for associative memory*. It +consists of 1 main logic file (`hamux/core.py`) (`<200` lines of +important code), 1 file of example lagrangians (`hamux/lagrangians.py`) +and 1 demo notebook: **`demo.ipynb`**. Intended for research code. ## A Universal Abstraction for Hopfield Networks @@ -30,302 +36,247 @@ and enables anyone to: - 🏆 That resemble modern DL operations -**Every** architecture built using HAMUX is a *dynamical system* -guaranteed to have a *tractable energy* function that *converges* to a -fixed point. Our deep [Hierarchical Associative +**Every** architecture built using HAMUX is a formal Associative Memory +(AM). That is, the architecture defines a *tractable energy*, whose +minimization describes a *dynamical system* that is guaranteed to +*converge* to a fixed point. [Hierarchical Associative Memories](https://arxiv.org/abs/2107.06446) (HAMs) have several additional advantages over traditional [Hopfield Networks](http://www.scholarpedia.org/article/Hopfield_network) (HNs): -| Hopfield Networks (HNs) | Hierarchical Associative Memories (HAMs) | -|--------------------------------------------------------|------------------------------------------------------------------------------------------------------------| -| HNs are only **two layers** systems | HAMs connect **any number** of layers | +| Hopfield Networks (HNs) | Hierarchical Associative Memories (HAMs) | +|----|----| +| HNs are only **two layers** systems | HAMs connect **any number** of layers | +| HNs have **limited storage capacity** | HAMs can be used to describe Associative Memories with much denser storage | | HNs model only **simple relationships** between layers | HAMs model **any complex but differentiable operation** (e.g., convolutions, pooling, attention, $\ldots$) | -| HNs use only **pairwise synapses** | HAMs use **many-body synapses** (which we denote **HyperSynapses**) | +| HNs use only **pairwise synapses** | HAMs can also use **many-body synapses** (which we denote **HyperSynapses**) | ## How does HAMUX work? -> **HAMUX** is a -> hypergraph of -> 🌀neurons connected via 🤝hypersynapses, an abstraction sufficiently -> general to model the complexity of connections used in modern AI -> architectures. - -
- We conflate the terms hypersynapse and synapse regularly. We explicitly say "pairwise synapse" when referring to the classical understanding of synapses. -
- -HAMUX defines two fundamental building blocks of energy: the **🌀neuron -layer** and the **🤝hypersynapse** (an abstraction of a pairwise synapse -to include many-body interactions) connected via a -[**hypergraph**](https://en.wikipedia.org/wiki/Hypergraph). It is a -fully dynamical system, where the “hidden state” $x_i^l$ of each layer -$l$ (blue squares in the figure below) is an independent variable that -evolves over time. The update rule of each layer is entirely local; only -signals from a layer’s connected synapses (red circles in the figure -below) can tell the hidden state how to change. This is shown in the -following equation: - -$$\tau \frac{d x_{i}^{l}}{dt} = -\frac{\partial E}{\partial g_i^l}$$ - -where $g_i^l$ are the *activations* (i.e., non-linearities) on each -neuron layer, described in the section on [Neuron -Layers](#🌀Neuron-Layers). Concretely, we implement the above -differential equation as the following discretized equation (where the -bold ${\mathbf x}_l$ is the collection of all elements in layer $l$’s -state): - -$$ \mathbf{x}_l^{(t+1)} = \mathbf{x}_l^{(t)} - \frac{dt}{\tau} \nabla_{\mathbf{g}_l}E(t)$$ - -HAMUX handles all the complexity of scaling this fundamental update -equation to many layers and hyper synapses. In addition, it provides a -*framework* to: +![**HAMUX is a [hypergraph](https://en.wikipedia.org/wiki/Hypergraph) of +🌀neurons connected via 🤝hypersynapses**, an abstraction sufficiently +general to model any conceivable Associative +Memory.](./figures/hamux_overview.png) + +See our walkthrough in [this notebook](./nbs/00_core.ipynb) for a more +detailed explanation of how everything works. + +In summary, this library handles all the complexity of scaling modular, +learnable energy functions that interconnect many layers and +hypersynapses. It is a barebones framework to explore Associative +Memories that look like Deep Learning architectures. 1. Implement your favorite Deep Learning operations as a - [HyperSynapse](https://bhoov.github.io/hamux/synapses.html) + [HyperSynapse](./00_core.ipynb#sec-hypersynapses) 2. Port over your favorite activation functions as - [Lagrangians](https://bhoov.github.io/hamux/lagrangians.html) -3. Connect your layers and hypersynapses into a - [HAM](https://bhoov.github.io/hamux/ham.html) (using a hypergraph as - the data structure) -4. Inject your data into the associative memory -5. Automatically calculate and descend the energy given the hidden - states at any point in time - -Use these features to train any hierarchical associative memory on your -own data! All of this made possible by -[JAX](https://github.com/google/jax). - -The `examples/` subdirectory contains a (growing) list of examples on -how to apply HAMUX on real data. - -
-HAMUX Overview -
Explaining the "energy fundamentals" of HAMUX (Layers and Synapses, left) using a 4-layer, 3-synapse example HAM (middle) that can be built using the code on the right.
-
- -### 🌀Neuron Layers - -Neuron layers are the recurrent unit of a HAM; that is, 🌀neurons keep a -state that changes over time according to the dynamics of the system. -These states always change to minimize the global energy function of the -system. - -For those of us familiar with traditional Deep Learning architectures, -we are familiar with nonlinear activation functions like the `ReLU` and -`SoftMax`. A neuron layer in HAMUX is exactly that: a nonlinear -activation function defined on some neuron. However, we need to express -the activation function as a convex **Lagrangian function** -$\mathcal{L}$ that is the integral of the desired non-linearity such -that the **derivative of the Lagrangian function** $\nabla \mathcal{L}$ -is our desired non-linearity. E.g., consider the ReLU: - -$$ -\begin{align*} -\mathcal{L}(x) &:= \frac{1}{2} (\max(x, 0))^2\\ -\nabla \mathcal{L} &= \max(x, 0) = \mathrm{relu}(x)\\ -\end{align*} -$$ - -We need to define our activation layer in terms of the *Lagrangian* of -the ReLU instead of the ReLU itself. Extending this constraint to other -nonlinearities makes it possible to define the scalar energy for any -neuron in a HAM. It turns out that many activation functions used in -today’s Deep Learning landscape are expressible as a Lagrangian. HAMUX -is “batteries-included” for many common activation functions including -`relu`s, `softmax`es, `sigmoid`s, `LayerNorm`s, etc. See our -[documentation on -Lagrangians](https://bhoov.github.io/hamux/lagrangians.html) for -examples on how to implement efficient activation functions from -Lagrangians in JAX. We show how to turn Lagrangians into usable energy -building blocks in our [documentation on neuron -layers](https://bhoov.github.io/hamux/layers.html). - -### 🤝HyperSynapses - -A 🤝hypersynapse ONLY sees activations of connected 🌀neuron layers. Its -one job: report HIGH ⚡️energy if the connected activations are -dissimilar and LOW ⚡️energy when they are aligned. Hypersynapses can -resemble convolutions, dense multiplications, even attention… Take a -look at our [documentation on -(hyper)synapses](https://bhoov.github.io/hamux/synapses.html). - -
- 🚨 Point of confusion: modern AI frameworks have ConvLayers and NormalizationLayers. In HAMUX, these would be more appropriately called ConvSynapses and NormalizationLagrangians. -
- -## Install - -**From pip**: - - pip install hamux - -If you are using accelerators beyond the CPU you will need to -additionally install the corresponding `jax` and `jaxlib` versions -following [their -documentation](https://github.com/google/jax#installation). E.g., - - pip install --upgrade "jax[cuda]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html - -**From source**: - -After cloning: - - cd hamux - conda env create -f environment.yml - conda activate hamux - pip install --upgrade "jax[cuda]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html # If using GPU accelerator - pip install -e . - pip install -r requirements-dev.txt # To run the examples - -## How to Use + [Lagrangians](./01_lagrangians.ipynb) +3. Connect layers and hypersynapses into a hypergraph with a [single + total energy](./00_core.ipynb#sec-energy-hypergraphs). +4. Easily use autograd for descending states. -``` python -import hamux as hmx -import jax.numpy as jnp -import jax -import jax.tree_util as jtu -``` +All of this made possible by [JAX](https://github.com/google/jax) and +[equinox](https://github.com/patrick-kidger/equinox). -We can build a simple 4 layer HAM architecture using the following code +## Installation -``` python -layers = [ - hmx.TanhLayer((32,32,3)), # e.g., CIFAR Images - hmx.SigmoidLayer((11,11,1000)), # CIFAR patches - hmx.SoftmaxLayer((10,)), # CIFAR Labels - hmx.SoftmaxLayer((1000,)), # Hidden Memory Layer -] +Install latest from the GitHub [repo](https://github.com/bhoov/hamux) -synapses = [ - hmx.ConvSynapse((3,3), strides=3), - hmx.DenseSynapse(), - hmx.DenseSynapse(), -] +``` sh +$ pip install git+https://github.com/bhoov/hamux.git +``` -connections = [ - ([0,1], 0), - ([1,3], 1), - ([2,3], 2), -] +or from [pypi](https://pypi.org/project/hamux/) -rng = jax.random.PRNGKey(0) -param_key, state_key, rng = jax.random.split(rng, 3) -states, ham = hmx.HAM(layers, synapses, connections).init_states_and_params(param_key, state_key=state_key); +``` sh +pip install hamux ``` -Notice that we did not specify any output channel shapes in the -synapses. The desired output shape is computed from the layers connected -to each synapse during `hmx.HAM.init_states_and_params`. - -We have two fundamental objects: `states` and `ham`. The `ham` object -contains the connectivity structure of the HAM (e.g., -layer+hypersynapse+hypergraph information) alongside the **parameters** -of the network. The `states` object is a list of length `nlayers` where -each item is a tensor representing the neuron states of the -corresponding layer. +## How to use ``` python -assert len(states) == ham.n_layers -assert all([state.shape == layer.shape for state, layer in zip(states, ham.layers)]) +import hamux as hmx +import jax, jax.numpy as jnp, jax.random as jr, jax.tree_util as jtu +import equinox as eqx +from typing import * +import matplotlib.pyplot as plt ``` -We make it easy to run the dynamics of any HAM. Every `forward` function -is defined external to the memory and can be modified to extract -different memories from different layers, as desired. The general steps -for any forward function are: +``` python +class LinearSynapse(eqx.Module): + """The energy synapse corrolary of the linear layer in standard neural networks""" + W: jax.Array + def __call__(self, xhat1:jax.Array, xhat2:jax.Array): + return xhat1 @ self.W @ xhat2 + + @classmethod + def rand_init(cls, key: jax.Array, D1: int, D2: int): + Winit = 0.02 * jr.normal(key, (D1, D2)) + return cls(W=Winit) + +key = jr.key(0) +nhid = 9 +nlabel = 8 +ninput = 7 + +neurons = { + "input": hmx.NeuronLayer(hmx.lagr_identity, (ninput,)), + "labels": hmx.NeuronLayer(hmx.lagr_softmax, (nlabel,)), + "hidden": hmx.NeuronLayer(hmx.lagr_softmax, (nhid,)) +} + +synapses = { + "dense1": LinearSynapse.rand_init(key, ninput, nhid), + "dense2": LinearSynapse.rand_init(key, nlabel, nhid) +} + +connections = [ + (("input", "hidden"), "dense1"), + (("labels", "hidden"), "dense2") +] -1. Initialize the dynamic states -2. Inject an initial state into the system -3. Run dynamics, calculating energy gradient at every point in time. -4. Return the layer state/activation of interest +ham = hmx.HAM(neurons, synapses, connections) +``` ``` python -def fwd(model, x, depth=15, dt=0.1): - """Assuming a trained HAM, run association with the HAM on batched inputs `x`""" - # 1. Initialize model states at t=0. Account for batch size - xs = model.init_states(x.shape[0]) - - # Inject initial state - xs[0] = x - - energies = [] - for i in range(depth): - energies.append(model.venergy(xs)) # If desired, observe the energy - dEdg = model.vdEdg(xs) # Calculate the gradients - xs = jtu.tree_map(lambda x, stepsize, grad: x - stepsize * grad, xs, model.alphas(dt), dEdg) - - - # Return probabilities of our label layer - probs = model.layers[-2].activation(xs[-2]) - return jnp.stack(energies), probs +xs = ham.init_states() # No batch size +xhats = ham.activations(xs) + +ham.energy_tree(xhats, xs) +ham.energy(xhats, xs) +ham.dEdact(xhats, xs) ``` + {'hidden': Array([ 0.00705259, 0.00320656, -0.02189678, 0.00424237, 0.00248319, + -0.00192548, 0.00498188, 0.00388546, 0.00415148], dtype=float32), + 'input': Array([ 0.00667361, 0.00921866, 0.00110246, -0.00476699, -0.0013505 , + -0.00371795, -0.00420904], dtype=float32), + 'labels': Array([ 0.00667361, 0.00921866, 0.00110246, -0.00476699, -0.0013505 , + -0.00371795, -0.00420904, 0.00254421], dtype=float32)} + ``` python -batch_size=3 -x = jax.random.normal(jax.random.PRNGKey(2), (batch_size, 32,32,3)) -energies, probs = fwd(ham, x, depth=20, dt=0.3) -print(probs.shape) # batchsize, nclasses -assert jnp.allclose(probs.sum(-1), 1) -``` +vham = ham.vectorize() +bs = 3 +xs = vham.init_states(bs) # Batch size 3 +xhats = vham.activations(xs) + +print(vham.energy_tree(xhats, xs)) +print(vham.energy(xhats, xs)) +print(vham.dEdact(xhats, xs)) - (3, 10) +ham = vham.unvectorize() +``` -![](index_files/figure-gfm/cell-12-output-1.png) + {'connections': [Array([0., 0., 0.], dtype=float32), Array([0.00068681, 0.00068681, 0.00068681], dtype=float32)], 'neurons': {'hidden': Array([-2.1972246, -2.1972246, -2.1972246], dtype=float32), 'input': Array([0., 0., 0.], dtype=float32), 'labels': Array([-2.0794415, -2.0794415, -2.0794415], dtype=float32)}} + [-4.275979 -4.275979 -4.275979] + {'hidden': Array([[ 0.00705259, 0.00320656, -0.02189678, 0.00424237, 0.00248319, + -0.00192548, 0.00498188, 0.00388546, 0.00415148], + [ 0.00705259, 0.00320656, -0.02189678, 0.00424237, 0.00248319, + -0.00192548, 0.00498188, 0.00388546, 0.00415148], + [ 0.00705259, 0.00320656, -0.02189678, 0.00424237, 0.00248319, + -0.00192548, 0.00498188, 0.00388546, 0.00415148]], dtype=float32), 'input': Array([[ 0.00667361, 0.00921866, 0.00110246, -0.00476699, -0.0013505 , + -0.00371795, -0.00420904], + [ 0.00667361, 0.00921866, 0.00110246, -0.00476699, -0.0013505 , + -0.00371795, -0.00420904], + [ 0.00667361, 0.00921866, 0.00110246, -0.00476699, -0.0013505 , + -0.00371795, -0.00420904]], dtype=float32), 'labels': Array([[ 0.00667361, 0.00921866, 0.00110246, -0.00476699, -0.0013505 , + -0.00371795, -0.00420904, 0.00254421], + [ 0.00667361, 0.00921866, 0.00110246, -0.00476699, -0.0013505 , + -0.00371795, -0.00420904, 0.00254421], + [ 0.00667361, 0.00921866, 0.00110246, -0.00476699, -0.0013505 , + -0.00371795, -0.00420904, 0.00254421]], dtype=float32)} + +We can check that the energy descent using randomize weights behaves as +expected. -
- More examples coming soon! -
+``` python +# Randomize the initial states +rkey = jr.key(42) +key_tree = dict(zip(xs.keys(), jr.split(rkey, len(xs)))) +xs = jtu.tree_map(lambda key, x: jr.normal(key, x.shape), key_tree, xs) +xhats = vham.activations(xs) + +nsteps = 40 +step_size = 0.5 +energies = jnp.empty((nsteps, bs)) +for i in range(nsteps): + energy, dEdxhats = vham.dEdact(xhats, xs, return_energy=True) + energies = energies.at[i].set(energy) + xs = jtu.tree_map(lambda x, u: x - step_size * u, xs, dEdxhats) + +plt.plot(jnp.arange(nsteps), energies) +``` -## The Energy Function vs the Loss Function + -We use JAX’s autograd to descend the energy function of our system AND -the loss function of our task. The derivative of the energy is always -taken wrt to our *states*; the derivative of the loss function is always -taken wrt our *parameters*. During training, we change our parameters to -optimize the *Loss Function*. During inference, we assume that -parameters are constant. +See the +[`nbs/_examples`](https://github.com/bhoov/hamux/tree/main/nbs/_examples) +directory for more examples. -**Autograd for Descending Energy** +## Developing locally -Every [`HAM`](https://bhoov.github.io/hamux/ham.html#ham) defines the -energy function for our system, which is everything we need to compute -memories of the system. Naively, we can calculate $\nabla_x E$: the -derivative of the energy function wrt the *states* of each layer: +`uv` (in `pyproject.toml`) handles all dependencies, `nbdev` (and its +`settings.ini`) handles all packaging. We handle syncing between the +`pyproject.toml` and `settings.ini` files using +`scripts/sync_dependencies.py`. -``` python -stepsize = 0.01 -fscore_naive = jax.grad(ham.energy) -next_states = jax.tree_util.tree_map(lambda state, score: state - stepsize, states, fscore_naive(states)) -``` +> [!WARNING] +> +> Package is currently based on a fork of +> [nbdev](https://github.com/bhoov/nbdev/tree/qmd_support) that allows +> development in plain text `.qmd` files. -But it turns out we improve the efficiency of our network if we instead -take $\nabla_g E$: the derivative of the energy wrt the *activations* -instead of the *states*. They have the same local minima, even though -the trajectory to get there is different. Some nice terms cancel, and we -get: +**Prerequisite**: Download [‘uv’](https://docs.astral.sh/uv/) -$$\nabla_g E_\text{HAM} = x + \nabla_g E_\text{synapse}$$ +``` sh +uv sync +uv run uv pip install -e . -``` python -stepsize = 0.01 -def fscore_smart(xs): - gs = ham.activations(xs) - return jax.tree_util.tree_map(lambda x, nabla_g_Esyn: x + nabla_g_Esyn, xs, jax.grad(ham.synapse_energy)(gs)) +# OPTIONAL: Add GPU enabled JAX e.g., for CUDA 12 +uv run uv pip install -U "jax[cuda12]" -next_states = jax.tree_util.tree_map(lambda state, score: state - stepsize, states, fscore_smart(states)) +source .venv/bin/activate +nbdev_prepare ``` -## Credits +``` sh +uv sync +source .venv/bin/activate -Read our extended abstract on OpenReview: [HAMUX: A Universal -Abstraction for Hierarchical Hopfield -Networks](https://openreview.net/forum?id=SAv3nhzNWhw) +# Make changes to source files in `nbs/`. +uv run nbdev_prepare # Before committing changes, export and test library +uv run nbdev_preview # Preview docs +``` -Work is a collaboration between the [MIT-IBM Watson AI -Lab](https://mitibmwatsonailab.mit.edu/) and the -[PoloClub](https://poloclub.github.io/) @ GA Tech. - [Ben -Hoover](https://www.bhoov.com/) (IBM & GATech) - [Polo -Chau](https://faculty.cc.gatech.edu/~dchau/) (GATech) - [Hendrik -Strobelt](http://hendrik.strobelt.com/) (IBM) - [Dmitry -Krotov](https://mitibmwatsonailab.mit.edu/people/dmitry-krotov/) (IBM) +### VSCode for developmentautomatic library export + +> Never let your `.qmd` source get out of sync with your `.py` library. + +VSCode has an excellent interactive mode for developing quarto files. We +install the +[`Run on Save`](https://marketplace.visualstudio.com/items?itemName=emeraldwalk.RunOnSave) +extension to keep the `.qmd` files in sync with the `.py` library, +removing the need for explicit `nbdev_export` commands. + +To accomplish this, copy and paste the following into your +user/workspace settings (`Cmd+Shift+P` then either “Preferences: Open +User settings (JSON)” or “Preferences: Open Workspace settings (JSON)”) + +``` js +{ + "files.watcherExclude": { + "**/.git/objects/**": true, + "**/.git/subtree-cache/**": true, + "**/node_modules/*/**": true, + "**/.hg/store/**": true, + }, + "emeraldwalk.runonsave": { + "commands": [ + { + "match": "nbs/.*\\.qmd$", // Replace with your own nbs/ directory + "cmd": "source ${workspaceFolder}/.venv/bin/activate && nbdev_export", // Replace with a path to your python env where `nbdev` is installed + } + ] + } +} +``` diff --git a/assets/HyperSynapse-fig1.png b/assets/HyperSynapse-fig1.png deleted file mode 100644 index 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cudatoolkit - - cudnn - - ipywidgets \ No newline at end of file diff --git a/examples/CIFAR 2layer Training.ipynb b/examples/CIFAR 2layer Training.ipynb deleted file mode 100644 index 9be1cfc..0000000 --- a/examples/CIFAR 2layer Training.ipynb +++ /dev/null @@ -1,2848 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "27b441e5-c359-412d-98ba-7613144e496e", - "metadata": {}, - "source": [ - "# Minimal CIFAR Demo for Classification\n", - "\n", - "A minimal demo on the CIFAR training dataset for classification. A lot of this notebook includes boilerplate. Look for the 🚀 symbol for important notes" - ] - }, - { - "cell_type": "markdown", - "id": "9f22e7f2-703d-458d-a9b7-3fa209a29702", - "metadata": {}, - "source": [ - "Load important libraries. Modify GPU usage details here." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "22160802-0004-4506-a81c-8d4a945e7196", - "metadata": {}, - "outputs": [], - "source": [ - "%reload_ext autoreload \n", - "%autoreload 2\n", - "\n", - "import os\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n", - "os.environ[\"XLA_FLAGS\"] = \"--xla_gpu_force_compilation_parallelism=1\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9f87a2cb-8351-4e3e-b60e-3a6c6f73d9a4", - "metadata": {}, - "outputs": [], - "source": [ - "import jax\n", - "import jax.numpy as jnp\n", - "import hamux as hmx\n", - "import treex as tx\n", - "from flax import linen as nn # For initializers\n", - "import optax\n", - "import jax.tree_util as jtu\n", - "from typing import *\n", - "import matplotlib.pyplot as plt\n", - "from dataclasses import dataclass\n", - "from loguru import logger\n", - "from einops import rearrange\n", - "from tqdm.auto import trange, tqdm\n", - "from pathlib import Path" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "95c7c026-22db-4526-b1bf-dbbfaa14e37e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[GpuDevice(id=0, process_index=0)]" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jax.devices()" - ] - }, - { - "cell_type": "markdown", - "id": "f4e2aa82-2cee-4607-9d56-eea2ce808491", - "metadata": {}, - "source": [ - "# Training functions\n", - "\n", - "For the classification task." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1c7ba2fa-f4d5-40b4-b706-90d33ec4d6c4", - "metadata": {}, - "outputs": [], - "source": [ - "class TrainState(tx.Module):\n", - " model: tx.Module\n", - " optimizer: tx.Optimizer\n", - " apply_fn: Callable\n", - " filter_betas: bool\n", - " rng: jnp.ndarray = tx.Rng.node()\n", - " eval_rng: jnp.ndarray = tx.Rng.node()\n", - "\n", - " def __init__(\n", - " self, model, optimizer, apply_fn, rng, filter_betas=False, do_normal_init=False\n", - " ):\n", - " self.filter_betas = filter_betas\n", - " self.model = model\n", - " self.optimizer = tx.Optimizer(optimizer).init(self.params)\n", - " self.apply_fn = apply_fn\n", - " self.rng, self.eval_rng = jax.random.split(rng)\n", - " self.do_normal_init = do_normal_init\n", - "\n", - " @property\n", - " def params(self):\n", - " if self.filter_betas:\n", - " return self.model.filter(lambda x: \"beta\" not in x.name)\n", - " return self.model.filter(tx.Parameter)\n", - "\n", - " def apply_updates(self, grads):\n", - " new_params = self.optimizer.update(grads, self.params)\n", - " self.model = self.model.merge(new_params)\n", - " return self\n", - "\n", - "\n", - "def cross_entropy_loss(*, probs, labels):\n", - " n_classes = probs.shape[-1]\n", - " labels_onehot = jax.nn.one_hot(labels, num_classes=n_classes)\n", - " smoothed_labels = (0.1 / n_classes + labels_onehot)\n", - " smoothed_labels = smoothed_labels / jnp.abs(smoothed_labels).sum(-1, keepdims=True)\n", - "\n", - " stable_probs = (probs + 1e-6) / (1+(1e-6)*n_classes)\n", - " loss = -jnp.sum(smoothed_labels * jnp.log(stable_probs), axis=-1).mean()\n", - " return loss\n", - "\n", - "\n", - "def compute_metrics(*, probs, labels):\n", - " loss = cross_entropy_loss(probs=probs, labels=labels)\n", - " accuracy = jnp.mean(jnp.argmax(probs, -1) == labels)\n", - " metrics = {\n", - " \"probs_min\": probs.min(),\n", - " 'probs_max': probs.max(),\n", - " 'loss': loss,\n", - " 'accuracy': accuracy,\n", - " }\n", - " return metrics\n", - "\n", - "\n", - "@jax.jit\n", - "def train_step(state, batch):\n", - " if state.do_normal_init:\n", - " rng, state.rng = jax.random.split(state.rng)\n", - " else:\n", - " rng = None\n", - "\n", - " def loss_fn(params):\n", - " state.model = state.model.merge(params)\n", - " x = batch[\"image\"]\n", - " probs = state.apply_fn(state.model, x, rng=rng)\n", - " loss = cross_entropy_loss(probs=probs, labels=batch[\"label\"])\n", - " return loss, (probs, state)\n", - "\n", - " grad_fn = jax.value_and_grad(loss_fn, has_aux=True)\n", - " (_, (probs, state)), grads = grad_fn(state.params)\n", - "\n", - " state = state.apply_updates(grads)\n", - " metrics = compute_metrics(probs=probs, labels=batch[\"label\"])\n", - " return state, metrics\n", - "\n", - "@jax.jit\n", - "def eval_step(state, batch):\n", - " x = batch[\"image\"]\n", - " if state.do_normal_init:\n", - " rng = state.eval_rng\n", - " else:\n", - " rng = None\n", - " probs = state.apply_fn(state.model, x, rng=rng)\n", - " return compute_metrics(probs=probs, labels=batch['label'])\n", - "\n", - "def train_epoch(state, train_dl, epoch):\n", - " \"\"\"Train for a single epoch.\"\"\"\n", - " batch_metrics = []\n", - " bs = train_dl.batch_size\n", - " for i, batch in enumerate(tqdm(train_dl, leave=False)):\n", - " batch = {\"image\": jnp.array(batch[0]), \"label\": jnp.array(batch[1])}\n", - " state, metrics = train_step(state, batch)\n", - " batch_metrics.append(metrics)\n", - "\n", - " # compute mean of metrics across each batch in epoch.\n", - " batch_metrics_np = jax.device_get(batch_metrics)\n", - " epoch_metrics_np = {\n", - " k: np.mean([metrics[k] for metrics in batch_metrics_np])\n", - " for k in batch_metrics_np[0]\n", - " }\n", - " return state, epoch_metrics_np[\"loss\"], epoch_metrics_np[\"accuracy\"]\n", - "\n", - "\n", - "def eval_model(state, test_dl):\n", - " batch_metrics = []\n", - "\n", - " for i, batch in enumerate(test_dl):\n", - " batch = {\"image\": jnp.array(batch[0]), \"label\": jnp.array(batch[1])}\n", - "\n", - " metrics = eval_step(state, batch)\n", - " batch_metrics.append(metrics)\n", - " batch_metrics_np = jax.device_get(batch_metrics)\n", - " summary = {\n", - " k: np.mean([metrics[k] for metrics in batch_metrics_np])\n", - " for k in batch_metrics_np[0]\n", - " }\n", - "\n", - " return summary[\"loss\"], summary[\"accuracy\"]" - ] - }, - { - "cell_type": "markdown", - "id": "8f582c18-5dc3-4e1d-817f-51dad2f7a98b", - "metadata": {}, - "source": [ - "# Dataset\n", - "\n", - "We load the CIFAR dataset with selected augmentations" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4cbbc562-2435-4fc1-bb5a-1fd497bf2916", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Files already downloaded and verified\n", - "Files already downloaded and verified\n" - ] - } - ], - "source": [ - "from hamux.datasets import *\n", - "\n", - "dl_args = DataloadingArgs(\n", - " dataset=\"torch/CIFAR10\",\n", - " # aa=\"rand\",\n", - " aa=None,\n", - " reprob=0.,\n", - " vflip=0.0,\n", - " hflip=0.5,\n", - " scale=(0.2, 1.0),\n", - " batch_size=100,\n", - " color_jitter=0.5,\n", - " validation_batch_size=1000,\n", - ")\n", - "data_config = DataConfigCIFAR10(input_size=(3, 32, 32))\n", - "\n", - "train_dl, eval_dl = create_dataloaders(dl_args, data_config)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8f561396-39a6-4e41-a6f7-c4d56c77818b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "for batch in train_dl:\n", - " imgs, labels = batch\n", - " break\n", - " \n", - "plt.imshow(data_config.show(imgs[8]))" - ] - }, - { - "cell_type": "markdown", - "id": "89d52c96-7861-4ed3-9d20-691c23b79311", - "metadata": {}, - "source": [ - "# Model Creation from Scratch\n", - "\n", - "We rewrite the synapse and layer for a simple 2 layer CIFAR network" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "054a2550-d0cd-4346-b386-e340a8e5032a", - "metadata": {}, - "outputs": [], - "source": [ - "class HopfieldNetworkAsSynapse(hmx.Synapse):\n", - " \"\"\"A simple reimplementation of a Hopfield Network as a synapse, returning the alignment\"\"\"\n", - " W1: jnp.ndarray = tx.Parameter.node() # treex's preferred way of declaring an attribute as a parameter\n", - " W2: jnp.ndarray = tx.Parameter.node()\n", - " nhid: int\n", - " beta: float = tx.Parameter.node()\n", - " \n", - " def __init__(self, nhid:int, beta_init=0.1):\n", - " self.nhid = nhid\n", - " self.beta = beta_init\n", - " \n", - " def __call__(self, g1, g2):\n", - " \"\"\"The alignment function, defined on an unbatched `g`\"\"\"\n", - " if self.initializing():\n", - " self.W1 = nn.initializers.normal(0.02)(tx.next_key(), g1.shape + (self.nhid,))\n", - " self.W2 = nn.initializers.normal(0.02)(tx.next_key(), g2.shape + (self.nhid,))\n", - " hidsig = g1 @ self.W1 + g2 @ self.W2\n", - " hid_lagrangian_value = 1/self.beta * jnp.exp(self.beta * hidsig)\n", - " return hid_lagrangian_value.sum(-1)\n", - " \n", - "ImageLayer = hmx.Layer(hmx.lagrangians.LTanh(beta=0.1), (32*32*3,))\n", - "LabelLayer = hmx.Layer(hmx.lagrangians.LSoftmax(beta=0.1), (10,))\n", - "\n", - "layers = [ImageLayer, LabelLayer]\n", - "synapses = [HopfieldNetworkAsSynapse(nhid=1000)]\n", - "connections = [((0,1),0)]\n", - "ham = hmx.HAM(layers, synapses, connections)" - ] - }, - { - "cell_type": "markdown", - "id": "f9f6a204-b294-49f5-b326-41743405c754", - "metadata": {}, - "source": [ - "A layer is uniquely defined by a lagrangian function and a neuron shape" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "806ff11d-0bf7-4fb3-b1cd-d27c5ce89ea9", - "metadata": {}, - "outputs": [], - "source": [ - "def fwd(model, x, depth=4, dt=1, rng=None):\n", - " \"\"\"A pure function to extract desired information from the configured HAM, applied on batched inputs\"\"\"\n", - " # Initialize hidden states to our image\n", - " xs = model.init_states(x.shape[0], rng=rng)\n", - " xs[0] = jnp.array(rearrange(x, \"... c h w -> ... (c h w)\"))\n", - "\n", - " # Masks allow us to clamp our visible data over time\n", - " masks = jtu.tree_map(lambda x: jnp.ones_like(x, dtype=jnp.int8), xs)\n", - " masks[0] = jnp.zeros_like(masks[0], dtype=jnp.int8) # Don't evolve images\n", - "\n", - " for i in range(depth):\n", - " updates = model.vupdates(xs) # Calculate the updates\n", - " xs = model.step(\n", - " xs, updates, dt=dt, masks=masks\n", - " ) # Add them to our current states\n", - "\n", - " # All labels have a softmax activation function as the last layer, spitting out probabilities\n", - " return model.layers[-1].g(xs[-1])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d8ef102b-89b8-4b41-8ba2-ed3a805ac5d7", - "metadata": {}, - "outputs": [], - "source": [ - "jax_key = jax.random.PRNGKey(0)\n", - "k1, jax_key = jax.random.split(jax_key)\n", - "lr = 0.001\n", - "num_epochs = 100\n", - "states, ham = ham.init_states_and_params(k1, bs=1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c44f5d31-883c-448f-a338-b71dc2960ba8", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/optimizer.py:79: FutureWarning: jax.tree_leaves is deprecated, and will be removed in a future release. Use jax.tree_util.tree_leaves instead.\n", - " params = jax.tree_leaves(params)\n", - "2022-10-18 15:34:04.099 | INFO | __main__::31 - NParams=3082003\n", - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/module.py:241: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.\n", - " flat, _ = jax.tree_flatten(self)\n", - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/utils.py:167: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.\n", - " tree_types = jax.tree_flatten(\n", - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/utils.py:375: FutureWarning: jax.tree_leaves is deprecated, and will be removed in a future release. Use jax.tree_util.tree_leaves instead.\n", - " count = sum((x.size if hasattr(x, \"size\") else 0 for x in jax.tree_leaves(obj)), 0)\n", - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/utils.py:377: FutureWarning: jax.tree_leaves is deprecated, and will be removed in a future release. Use jax.tree_util.tree_leaves instead.\n", - " (x.nbytes if hasattr(x, \"nbytes\") else 0 for x in jax.tree_leaves(obj)), 0\n" - ] - }, - { - "data": { - "text/html": [ - "
┏━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓\n",
-       "┃ path                   module                 params                 Parameter         ┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩\n",
-       "│ *                     │ HAM()                 │                       │                   │\n",
-       "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n",
-       "│ .layers[0]            │ Layer()               │ bias: None            │                   │\n",
-       "│                       │                       │                       │                   │\n",
-       "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n",
-       "│ .layers[0].lagrangian │ LTanh()               │ beta: 0.1             │                   │\n",
-       "│                       │                       │                       │                   │\n",
-       "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n",
-       "│ .layers[1]            │ Layer()               │ bias: None            │                   │\n",
-       "│                       │                       │                       │                   │\n",
-       "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n",
-       "│ .layers[1].lagrangian │ LSoftmax()            │ beta: 0.1             │                   │\n",
-       "│                       │                       │                       │                   │\n",
-       "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n",
-       "│ .synapses[0]          │ HopfieldNetworkAsSyn… │ W1: Parameter(3072, 3,082,000  12.3MB │\n",
-       "│                       │                       │ 1000)  float32        │                   │\n",
-       "│                       │                       │ W2: Parameter(10,     │                   │\n",
-       "│                       │                       │ 1000)    float32      │                   │\n",
-       "│                       │                       │ beta: 0.1             │                   │\n",
-       "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n",
-       "│                                                              Total:  3,082,000  12.3MB │\n",
-       "└───────────────────────┴───────────────────────┴───────────────────────┴───────────────────┘\n",
-       "                                                                                             \n",
-       "                             Total Parameters: 3,082,000  12.3MB                             \n",
-       "
\n" - ], - "text/plain": [ - "┏━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓\n", - "┃\u001b[1m \u001b[0m\u001b[1mpath \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mmodule \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mparams \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mParameter \u001b[0m\u001b[1m \u001b[0m┃\n", - "┡━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩\n", - "│ * │ HAM() │ │ │\n", - "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n", - "│ .layers[0] │ Layer() │ bias: None │ │\n", - "│ │ │ │ │\n", - "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n", - "│ .layers[0].lagrangian │ LTanh() │ beta: 0.1 │ │\n", - "│ │ │ │ │\n", - "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n", - "│ .layers[1] │ Layer() │ bias: None │ │\n", - "│ │ │ │ │\n", - "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n", - "│ .layers[1].lagrangian │ LSoftmax() │ beta: 0.1 │ │\n", - "│ │ │ │ │\n", - "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n", - "│ .synapses[0] │ HopfieldNetworkAsSyn… │ W1: Parameter(\u001b[32m3072, \u001b[0m │ \u001b[32m3,082,000\u001b[0m \u001b[2m12.3MB\u001b[0m │\n", - "│ │ │ \u001b[32m1000\u001b[0m) \u001b[2mfloat32\u001b[0m │ │\n", - "│ │ │ W2: Parameter(\u001b[32m10, \u001b[0m │ │\n", - "│ │ │ \u001b[32m1000\u001b[0m) \u001b[2mfloat32\u001b[0m │ │\n", - "│ │ │ beta: 0.1 │ │\n", - "├───────────────────────┼───────────────────────┼───────────────────────┼───────────────────┤\n", - "│\u001b[1m \u001b[0m\u001b[1m \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1m \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1m Total:\u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1;32m3,082,000\u001b[0m\u001b[1m \u001b[0m\u001b[1;2m12.3MB\u001b[0m\u001b[1m \u001b[0m│\n", - "└───────────────────────┴───────────────────────┴───────────────────────┴───────────────────┘\n", - "\u001b[1m \u001b[0m\n", - "\u001b[1m Total Parameters: \u001b[0m\u001b[1;32m3,082,000\u001b[0m\u001b[1m \u001b[0m\u001b[1;2m12.3MB\u001b[0m\u001b[1m \u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-10-18 15:34:04.115 | INFO | __main__::32 - \n" - ] - } - ], - "source": [ - "# ham, forward_classification = hmx.create_model(args.model)\n", - "\n", - "optimizer = optax.adamw(0.001)\n", - "state = TrainState(\n", - " ham,\n", - " optimizer,\n", - " fwd,\n", - " rng=jax_key,\n", - " filter_betas=False,\n", - ")\n", - "\n", - "\n", - "def get_nparams(model):\n", - " params, meta = jtu.tree_flatten(model.parameters())\n", - "\n", - " def get_nel(x):\n", - " try:\n", - " return x.size\n", - " except AttributeError: # float\n", - " return 1\n", - "\n", - " return sum([get_nel(p) for p in params])\n", - "\n", - "\n", - "def escape_ansi(line):\n", - " import re\n", - "\n", - " ansi_escape = re.compile(r\"(?:\\x1B[@-_]|[\\x80-\\x9F])[0-?]*[ -/]*[@-~]\")\n", - " return ansi_escape.sub(\"\", line)\n", - "\n", - "logger.info(f\"NParams={get_nparams(state.model)}\")\n", - "logger.info(escape_ansi(state.model.tabulate()))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cc02748e-1fd3-49b8-b95c-2bbb4847426e", - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "b8cd4d79c06c450d97d9ab7760611f02", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/100 [00:00:31 - Couldn't remove _logs/DummyCifar_epoch--1_acc--100.000.pckl, [Errno 2] No such file or directory: '_logs/DummyCifar_epoch--1_acc--100.000.pckl'\n", - "2022-10-18 15:34:25.197 | INFO | __main__::41 - [1/100] | BestAcc: 38.610 | TrainLoss: 2.10 | TrainAcc: 25.82 | curr_val_acc=38.61\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [2/100] | BestAcc: 39.680 | TrainLoss: 2.02 | TrainAcc: 30.18 | curr_val_acc=39.68\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [3/100] | BestAcc: 39.970 | TrainLoss: 2.00 | TrainAcc: 31.37 | curr_val_acc=39.97\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [4/100] | BestAcc: 43.380 | TrainLoss: 1.99 | TrainAcc: 32.36 | curr_val_acc=43.38\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [5/100] | BestAcc: 43.380 | TrainLoss: 1.97 | TrainAcc: 32.84 | curr_val_acc=43.26\n" - 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] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [22/100] | BestAcc: 48.890 | TrainLoss: 1.89 | TrainAcc: 37.59 | curr_val_acc=48.89\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [23/100] | BestAcc: 48.890 | TrainLoss: 1.89 | TrainAcc: 37.17 | curr_val_acc=48.47\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [24/100] | BestAcc: 49.180 | TrainLoss: 1.88 | TrainAcc: 37.77 | curr_val_acc=49.18\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [25/100] | BestAcc: 49.820 | TrainLoss: 1.88 | TrainAcc: 37.64 | curr_val_acc=49.82\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [26/100] | BestAcc: 50.680 | TrainLoss: 1.88 | TrainAcc: 37.87 | curr_val_acc=50.68\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [27/100] | BestAcc: 50.680 | TrainLoss: 1.88 | TrainAcc: 38.57 | curr_val_acc=49.42\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [28/100] | BestAcc: 50.680 | TrainLoss: 1.87 | TrainAcc: 38.47 | curr_val_acc=50.01\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [29/100] | BestAcc: 50.680 | TrainLoss: 1.88 | TrainAcc: 38.23 | curr_val_acc=50.25\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [30/100] | BestAcc: 50.680 | TrainLoss: 1.87 | TrainAcc: 38.51 | curr_val_acc=49.75\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [31/100] | BestAcc: 50.680 | TrainLoss: 1.87 | TrainAcc: 38.38 | curr_val_acc=50.41\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [32/100] | BestAcc: 50.680 | TrainLoss: 1.87 | TrainAcc: 38.37 | curr_val_acc=50.57\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [33/100] | BestAcc: 50.680 | TrainLoss: 1.87 | TrainAcc: 38.74 | curr_val_acc=50.39\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [34/100] | BestAcc: 50.680 | TrainLoss: 1.86 | TrainAcc: 39.11 | curr_val_acc=50.42\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [35/100] | BestAcc: 51.090 | TrainLoss: 1.86 | TrainAcc: 39.13 | curr_val_acc=51.09\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [36/100] | BestAcc: 51.090 | TrainLoss: 1.86 | TrainAcc: 39.01 | curr_val_acc=50.16\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [37/100] | BestAcc: 51.090 | TrainLoss: 1.86 | TrainAcc: 38.74 | curr_val_acc=49.89\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [38/100] | BestAcc: 51.090 | TrainLoss: 1.85 | TrainAcc: 39.13 | curr_val_acc=50.74\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [39/100] | BestAcc: 51.090 | TrainLoss: 1.85 | TrainAcc: 39.11 | curr_val_acc=50.39\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [40/100] | BestAcc: 51.090 | TrainLoss: 1.85 | TrainAcc: 39.43 | curr_val_acc=50.33\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [41/100] | BestAcc: 51.090 | TrainLoss: 1.85 | TrainAcc: 38.98 | curr_val_acc=51.03\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [42/100] | BestAcc: 51.190 | TrainLoss: 1.85 | TrainAcc: 39.34 | curr_val_acc=51.19\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [43/100] | BestAcc: 51.260 | TrainLoss: 1.85 | TrainAcc: 39.47 | curr_val_acc=51.26\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [44/100] | BestAcc: 51.800 | TrainLoss: 1.85 | TrainAcc: 39.45 | curr_val_acc=51.80\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [45/100] | BestAcc: 51.800 | TrainLoss: 1.84 | TrainAcc: 39.52 | curr_val_acc=51.51\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [46/100] | BestAcc: 51.800 | TrainLoss: 1.84 | TrainAcc: 39.85 | curr_val_acc=50.62\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [47/100] | BestAcc: 52.090 | TrainLoss: 1.84 | TrainAcc: 39.55 | curr_val_acc=52.09\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [48/100] | BestAcc: 52.090 | TrainLoss: 1.84 | TrainAcc: 39.85 | curr_val_acc=51.18\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [49/100] | BestAcc: 52.090 | TrainLoss: 1.84 | TrainAcc: 39.77 | curr_val_acc=51.35\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [50/100] | BestAcc: 52.210 | TrainLoss: 1.84 | TrainAcc: 39.84 | curr_val_acc=52.21\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [51/100] | BestAcc: 52.210 | TrainLoss: 1.84 | TrainAcc: 39.95 | curr_val_acc=52.16\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [52/100] | BestAcc: 52.300 | TrainLoss: 1.84 | TrainAcc: 39.61 | curr_val_acc=52.30\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [53/100] | BestAcc: 52.300 | TrainLoss: 1.84 | TrainAcc: 39.64 | curr_val_acc=51.83\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [54/100] | BestAcc: 52.300 | TrainLoss: 1.84 | TrainAcc: 39.88 | curr_val_acc=51.55\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [55/100] | BestAcc: 52.790 | TrainLoss: 1.83 | TrainAcc: 39.75 | curr_val_acc=52.79\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [56/100] | BestAcc: 52.830 | TrainLoss: 1.83 | TrainAcc: 39.94 | curr_val_acc=52.83\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [57/100] | BestAcc: 52.830 | TrainLoss: 1.83 | TrainAcc: 40.30 | curr_val_acc=51.67\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [58/100] | BestAcc: 52.830 | TrainLoss: 1.83 | TrainAcc: 40.27 | curr_val_acc=52.75\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [59/100] | BestAcc: 52.830 | TrainLoss: 1.83 | TrainAcc: 40.35 | curr_val_acc=51.97\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [60/100] | BestAcc: 52.830 | TrainLoss: 1.83 | TrainAcc: 39.88 | curr_val_acc=52.16\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [61/100] | BestAcc: 52.830 | TrainLoss: 1.82 | TrainAcc: 40.59 | curr_val_acc=52.44\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [62/100] | BestAcc: 52.830 | TrainLoss: 1.83 | TrainAcc: 40.11 | curr_val_acc=52.40\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [63/100] | BestAcc: 52.920 | TrainLoss: 1.83 | TrainAcc: 40.66 | curr_val_acc=52.92\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [64/100] | BestAcc: 52.920 | TrainLoss: 1.83 | TrainAcc: 40.30 | curr_val_acc=51.41\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [65/100] | BestAcc: 52.920 | TrainLoss: 1.83 | TrainAcc: 40.42 | curr_val_acc=51.27\n" - 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] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [70/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 40.56 | curr_val_acc=52.87\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [71/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 41.00 | curr_val_acc=52.85\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [72/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 40.86 | curr_val_acc=52.33\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [73/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 40.84 | curr_val_acc=53.21\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [74/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 40.58 | curr_val_acc=53.08\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [75/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 40.76 | curr_val_acc=52.37\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [76/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 41.04 | curr_val_acc=52.65\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [77/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 40.88 | curr_val_acc=52.08\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [78/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 40.97 | curr_val_acc=53.12\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [79/100] | BestAcc: 53.640 | TrainLoss: 1.81 | TrainAcc: 40.98 | curr_val_acc=53.14\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [80/100] | BestAcc: 53.640 | TrainLoss: 1.81 | TrainAcc: 40.94 | curr_val_acc=53.38\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [81/100] | BestAcc: 53.640 | TrainLoss: 1.81 | TrainAcc: 41.37 | curr_val_acc=53.08\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [82/100] | BestAcc: 53.640 | TrainLoss: 1.81 | TrainAcc: 41.13 | curr_val_acc=53.19\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [83/100] | BestAcc: 53.640 | TrainLoss: 1.82 | TrainAcc: 40.83 | curr_val_acc=53.17\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [84/100] | BestAcc: 53.740 | TrainLoss: 1.81 | TrainAcc: 41.35 | curr_val_acc=53.74\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [85/100] | BestAcc: 53.740 | TrainLoss: 1.81 | TrainAcc: 41.07 | curr_val_acc=53.32\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [86/100] | BestAcc: 53.740 | TrainLoss: 1.81 | TrainAcc: 41.31 | curr_val_acc=53.52\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [87/100] | BestAcc: 54.230 | TrainLoss: 1.81 | TrainAcc: 41.44 | curr_val_acc=54.23\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [88/100] | BestAcc: 54.420 | TrainLoss: 1.81 | TrainAcc: 41.76 | curr_val_acc=54.42\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [89/100] | BestAcc: 54.420 | TrainLoss: 1.81 | TrainAcc: 41.62 | curr_val_acc=54.38\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [90/100] | BestAcc: 54.420 | TrainLoss: 1.81 | TrainAcc: 41.68 | curr_val_acc=53.77\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [91/100] | BestAcc: 54.930 | TrainLoss: 1.81 | TrainAcc: 41.90 | curr_val_acc=54.93\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [92/100] | BestAcc: 54.930 | TrainLoss: 1.80 | TrainAcc: 41.47 | curr_val_acc=54.17\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [93/100] | BestAcc: 54.930 | TrainLoss: 1.81 | TrainAcc: 41.51 | curr_val_acc=53.77\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [94/100] | BestAcc: 54.930 | TrainLoss: 1.81 | TrainAcc: 41.31 | curr_val_acc=53.28\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [95/100] | BestAcc: 54.930 | TrainLoss: 1.80 | TrainAcc: 41.75 | curr_val_acc=53.97\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [96/100] | BestAcc: 54.930 | TrainLoss: 1.80 | TrainAcc: 41.89 | curr_val_acc=53.42\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [97/100] | BestAcc: 54.930 | TrainLoss: 1.80 | TrainAcc: 41.40 | curr_val_acc=54.36\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [98/100] | BestAcc: 54.930 | TrainLoss: 1.80 | TrainAcc: 41.72 | curr_val_acc=53.95\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [99/100] | BestAcc: 54.930 | TrainLoss: 1.80 | TrainAcc: 41.25 | curr_val_acc=54.37\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/500 [00:00:41 - [100/100] | BestAcc: 54.930 | TrainLoss: 1.80 | TrainAcc: 41.79 | curr_val_acc=52.55\n" - ] - } - ], - "source": [ - "# ===========================================\n", - "## Training\n", - "# ===========================================\n", - "@dataclass\n", - "class CkptTracker:\n", - " base_name: str\n", - " model: tx.Module = None\n", - " epoch: int = -1\n", - " best_acc: float = -1\n", - "\n", - " def get_save_name(self):\n", - " return f\"{self.base_name}_epoch-{self.epoch}_acc-{100*self.best_acc:.3f}.pckl\"\n", - "\n", - "\n", - "train_acc_list = []\n", - "test_acc_list = []\n", - "ckpt_tracker = CkptTracker(\"DummyCifar\")\n", - "logdir = Path(\"./_logs\")\n", - "logdir.mkdir(exist_ok=True, parents=True)\n", - "\n", - "\n", - "with trange(1, num_epochs + 1, unit=\"epochs\") as pbar:\n", - " for epoch in pbar:\n", - " state, train_loss, train_acc = train_epoch(state, train_dl, epoch)\n", - " test_loss, test_acc = eval_model(state, eval_dl)\n", - " if test_acc > ckpt_tracker.best_acc:\n", - " old_ckpt_name = str(logdir / ckpt_tracker.get_save_name())\n", - " try:\n", - " os.remove(old_ckpt_name)\n", - " except Exception as e:\n", - " logger.debug(f\"Couldn't remove {old_ckpt_name}, {e}\")\n", - " pass\n", - " ckpt_tracker.model = state.model\n", - " ckpt_tracker.epoch = epoch\n", - " ckpt_tracker.best_acc = test_acc\n", - " to_save = jtu.tree_map(hmx.utils.to_pickleable, ckpt_tracker.model.to_dict())\n", - " ckpt_name = str(logdir / ckpt_tracker.get_save_name())\n", - " hmx.utils.pytree_save(to_save, ckpt_name, overwrite=True)\n", - " desc = f\"[{epoch}/{num_epochs}] | BestAcc: {100*ckpt_tracker.best_acc:.3f} | TrainLoss: {train_loss:.2f} | TrainAcc: {100*train_acc:.2f}\"\n", - " addition = f\"curr_val_acc={100*test_acc:0.2f}\"\n", - " logger.info(desc + \" | \" + addition)\n", - " pbar.set_description(desc)\n", - " pbar.set_postfix(\n", - " train_acc=f\"{100*train_acc:0.2f}\", val_acc=f\"{100*test_acc:0.2f}\"\n", - " )" - ] - }, - { - "cell_type": "markdown", - "id": "04ba7898-19a8-491b-94d5-2dd5ad728223", - "metadata": {}, - "source": [ - "Brief analysis" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3f5398c4-3152-4701-a5da-e50c16d9ad71", - "metadata": {}, - "outputs": [], - "source": [ - "def fwd_energy(model, x, depth=4, dt=1, rng=None):\n", - " \"\"\"A pure function to extract desired information from the configured HAM, applied on batched inputs\"\"\"\n", - " # Initialize hidden states to our image\n", - " xs = model.init_states(x.shape[0], rng=rng)\n", - " xs[0] = jnp.array(rearrange(x, \"... c h w -> ... (c h w)\"))\n", - "\n", - " # Masks allow us to clamp our visible data over time\n", - " masks = jtu.tree_map(lambda x: jnp.ones_like(x, dtype=jnp.int8), xs)\n", - " # masks[0] = jnp.zeros_like(masks[0], dtype=jnp.int8) # Don't evolve images\n", - " all_xs = [xs]\n", - " energies = [model.venergy(xs)]\n", - "\n", - " for i in range(depth):\n", - " updates = model.vupdates(xs) # Calculate the updates\n", - " xs = model.step(\n", - " xs, updates, dt=dt, masks=masks\n", - " ) # Add them to our current states\n", - " all_xs.append(xs)\n", - " energies.append(model.venergy(xs))\n", - "\n", - " # All labels have a softmax activation function as the last layer, spitting out probabilities\n", - " return jnp.stack(energies), all_xs" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b54725f1-a671-4ed5-bae2-8278d811ac81", - "metadata": {}, - "outputs": [], - "source": [ - "img_start = batch[0][:1]\n", - "# img_start = jnp.ones_like(jnp.array(img_start))\n", - "energies, allxs = fwd_energy(ham, img_start, dt=0.2, depth=30)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fa204c07-db8f-4201-a21e-7a5b62327450", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:matplotlib.image:Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from torchvision.utils import make_grid\n", - "\n", - "def show_x(x):\n", - " x = rearrange(x, \"... (c h w) -> ... c h w\", c=3, h=32, w=32)\n", - " return data_config.show(torch.tensor(np.array(x)))\n", - "\n", - "aa = make_grid([rearrange(torch.tensor(show_x(x[0][0])), \"h w c -> c h w\") for x in allxs])\n", - "\n", - "plt.imshow(np.array(rearrange(aa, \"c h w -> h w c\")))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6e1b1ad7-d01e-4a94-987c-0423b5c27be5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.plot(energies)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6c08e34b-f2fc-4f83-bdbf-1cd05199f454", - "metadata": {}, - "outputs": [], - "source": [ - "# img_start = batch[0][:1]\n", - "# img_start = jnp.ones_like(jnp.array(img_start))\n", - "# # energies, allxs = fwd_energy(ham, img_start, dt=0.1, depth=60)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:hamux]", - "language": "python", - "name": "conda-env-hamux-py" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/MNIST 2layer Training.ipynb b/examples/MNIST 2layer Training.ipynb deleted file mode 100644 index 4c3c70b..0000000 --- a/examples/MNIST 2layer Training.ipynb +++ /dev/null @@ -1,1476 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "27b441e5-c359-412d-98ba-7613144e496e", - "metadata": {}, - "source": [ - "# Minimal MNIST Demo for Classification\n", - "\n", - "Showcase the power of an associative memory on MNIST" - ] - }, - { - "cell_type": "markdown", - "id": "9f22e7f2-703d-458d-a9b7-3fa209a29702", - "metadata": {}, - "source": [ - "Load important libraries. Modify GPU usage details here." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "22160802-0004-4506-a81c-8d4a945e7196", - "metadata": {}, - "outputs": [], - "source": [ - "%reload_ext autoreload \n", - "%autoreload 2\n", - "\n", - "import os\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"7\"\n", - "os.environ[\"XLA_FLAGS\"] = \"--xla_gpu_force_compilation_parallelism=1\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9f87a2cb-8351-4e3e-b60e-3a6c6f73d9a4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import jax\n", - "import jax.numpy as jnp\n", - "import hamux as hmx\n", - "import treex as tx\n", - "from flax import linen as nn # For initializers\n", - "import optax\n", - "import jax.tree_util as jtu\n", - "from typing import *\n", - "import matplotlib.pyplot as plt\n", - "from dataclasses import dataclass\n", - "from loguru import logger\n", - "from einops import rearrange\n", - "from tqdm.auto import trange, tqdm\n", - "from pathlib import Path\n", - "from torch.utils.data import DataLoader\n", - "import numpy as np\n", - "\n", - "import matplotlib.colors as colors\n", - "plt.set_cmap('bwr') # a good start: blue to white to red colormap" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "95c7c026-22db-4526-b1bf-dbbfaa14e37e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[GpuDevice(id=0, process_index=0)]" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jax.devices()" - ] - }, - { - "cell_type": "markdown", - "id": "f4e2aa82-2cee-4607-9d56-eea2ce808491", - "metadata": {}, - "source": [ - "# Training functions\n", - "\n", - "For the classification task." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1c7ba2fa-f4d5-40b4-b706-90d33ec4d6c4", - "metadata": {}, - "outputs": [], - "source": [ - "class TrainState(tx.Module):\n", - " model: tx.Module\n", - " optimizer: tx.Optimizer\n", - " apply_fn: Callable\n", - " filter_betas: bool\n", - " rng: jnp.ndarray = tx.Rng.node()\n", - " eval_rng: jnp.ndarray = tx.Rng.node()\n", - "\n", - " def __init__(\n", - " self, model, optimizer, apply_fn, rng, filter_betas=False, do_normal_init=False\n", - " ):\n", - " self.filter_betas = filter_betas\n", - " self.model = model\n", - " self.optimizer = tx.Optimizer(optimizer).init(self.params)\n", - " self.apply_fn = apply_fn\n", - " self.rng, self.eval_rng = jax.random.split(rng)\n", - " self.do_normal_init = do_normal_init\n", - "\n", - " @property\n", - " def params(self):\n", - " if self.filter_betas:\n", - " def good_name(x):\n", - " A = \"beta\" not in x.name\n", - " B = \"delta\" not in x.name\n", - " C = \"gamma\" not in x.name\n", - " return A and B and C\n", - " return self.model.filter(good_name)\n", - " return self.model.filter(tx.Parameter)\n", - "\n", - " def apply_updates(self, grads):\n", - " new_params = self.optimizer.update(grads, self.params)\n", - " self.model = self.model.merge(new_params)\n", - " return self\n", - "\n", - "\n", - "def cross_entropy_loss(*, probs, labels):\n", - " n_classes = probs.shape[-1]\n", - " labels_onehot = jax.nn.one_hot(labels, num_classes=n_classes)\n", - " # smoothed_labels = (0.1 / n_classes + labels_onehot)\n", - " # smoothed_labels = smoothed_labels / jnp.abs(smoothed_labels).sum(-1, keepdims=True)\n", - " smoothed_labels = labels_onehot\n", - " \n", - " stable_probs = (probs + 1e-6) / (1+(1e-6)*n_classes)\n", - " loss = -jnp.sum(smoothed_labels * jnp.log(stable_probs), axis=-1).mean()\n", - " loss = -jnp.sum(smoothed_labels * jnp.log(stable_probs), axis=-1).mean()\n", - "\n", - " return loss\n", - "\n", - "\n", - "def compute_metrics(*, probs, labels):\n", - " loss = cross_entropy_loss(probs=probs, labels=labels)\n", - " accuracy = jnp.mean(jnp.argmax(probs, -1) == labels)\n", - " metrics = {\n", - " \"probs_min\": probs.min(),\n", - " 'probs_max': probs.max(),\n", - " 'loss': loss,\n", - " 'accuracy': accuracy,\n", - " }\n", - " return metrics\n", - "\n", - "\n", - "@jax.jit\n", - "def train_step(state, batch):\n", - " if state.do_normal_init:\n", - " rng, state.rng = jax.random.split(state.rng)\n", - " else:\n", - " rng = None\n", - "\n", - " def loss_fn(params):\n", - " state.model = state.model.merge(params)\n", - " x = batch[\"image\"]\n", - " \n", - " probs = state.apply_fn(state.model, x, rng=rng)\n", - " loss = cross_entropy_loss(probs=probs, labels=batch[\"label\"])\n", - " return loss, (probs, state)\n", - "\n", - " grad_fn = jax.value_and_grad(loss_fn, has_aux=True)\n", - " (_, (probs, state)), grads = grad_fn(state.params)\n", - "\n", - " state = state.apply_updates(grads)\n", - " metrics = compute_metrics(probs=probs, labels=batch[\"label\"])\n", - " return state, metrics\n", - "\n", - "@jax.jit\n", - "def eval_step(state, batch):\n", - " x = batch[\"image\"]\n", - " if state.do_normal_init:\n", - " rng = state.eval_rng\n", - " else:\n", - " rng = None\n", - " probs = state.apply_fn(state.model, x, rng=rng)\n", - " return compute_metrics(probs=probs, labels=batch['label'])\n", - "\n", - "def train_epoch(state, train_dl, epoch):\n", - " \"\"\"Train for a single epoch.\"\"\"\n", - " batch_metrics = []\n", - " bs = train_dl.batch_size\n", - " for i, batch in enumerate(tqdm(train_dl, leave=False)):\n", - " batch = {\"image\": jnp.array(batch[0]), \"label\": jnp.array(batch[1])}\n", - " state, metrics = train_step(state, batch)\n", - " batch_metrics.append(metrics)\n", - "\n", - " # compute mean of metrics across each batch in epoch.\n", - " batch_metrics_np = jax.device_get(batch_metrics)\n", - " epoch_metrics_np = {\n", - " k: np.mean([metrics[k] for metrics in batch_metrics_np])\n", - " for k in batch_metrics_np[0]\n", - " }\n", - " return state, epoch_metrics_np[\"loss\"], epoch_metrics_np[\"accuracy\"]\n", - "\n", - "\n", - "def eval_model(state, test_dl):\n", - " batch_metrics = []\n", - "\n", - " for i, batch in enumerate(test_dl):\n", - " batch = {\"image\": jnp.array(batch[0]), \"label\": jnp.array(batch[1])}\n", - "\n", - " metrics = eval_step(state, batch)\n", - " batch_metrics.append(metrics)\n", - " batch_metrics_np = jax.device_get(batch_metrics)\n", - " summary = {\n", - " k: np.mean([metrics[k] for metrics in batch_metrics_np])\n", - " for k in batch_metrics_np[0]\n", - " }\n", - "\n", - " return summary[\"loss\"], summary[\"accuracy\"]" - ] - }, - { - "cell_type": "markdown", - "id": "ed7298d1-8894-47c0-9b3a-4b9a5c9936ec", - "metadata": {}, - "source": [ - "# Model Evaluation Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7a762e77-0824-4d57-a99f-24dba66fbaf7", - "metadata": {}, - "outputs": [], - "source": [ - "from hamux.datasets import *\n", - "\n", - "dl_args = DataloadingArgs(\n", - " dataset=\"torch/MNIST\",\n", - " # aa=\"rand\",\n", - " aa=None,\n", - " reprob=0.,\n", - " vflip=0.0,\n", - " hflip=0.0,\n", - " scale=(0.9, 1.1),\n", - " batch_size=100,\n", - " color_jitter=0.0,\n", - " validation_batch_size=1000,\n", - ")\n", - "data_config = DataConfigMNIST(input_size=(1, 28, 28), mean=0.5, std=0.5)\n", - "\n", - "train_dl, eval_dl = create_dataloaders(dl_args, data_config)\n", - "\n", - "for batch in train_dl:\n", - " imgs, labels = batch\n", - " break\n", - " \n", - "# plt.imshow(data_config.show(imgs[2]))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "097fb8e1-7109-4d44-bf1e-7833cee112e9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "norm = colors.TwoSlopeNorm(vcenter=0)\n", - "\n", - "imgs_big = rearrange(np.repeat(imgs, 11, axis=0)[:1024], \"... h w -> ... (h w)\")[:,0].T\n", - "imgs_big_show = rearrange(imgs_big, \"(h w) (kh kw) -> (kh h) (kw w)\", h=28, w=28, kh=32, kw=32)\n", - "\n", - "W2 = np.random.normal(size=(10,1024))\n", - "fig, axs = plt.subplots(1, 3, figsize=(15,6), width_ratios=(2,5,0.8))\n", - "def prep_axis(ax):\n", - " ax.axis('off')\n", - "[prep_axis(ax) for ax in axs]\n", - "\n", - "pos0 = axs[0].imshow(W2.T, aspect=\"auto\", interpolation=\"nearest\", norm=norm)\n", - "fig.colorbar(pos0, ax=axs[0], location=\"right\", shrink=0.7)\n", - "axs[0].set_title(\"Label matrix\")\n", - "\n", - "pos1 = axs[1].imshow(imgs_big_show, norm=norm)\n", - "axs[1].set_title(\"pixel_matrix\")\n", - "fig.colorbar(pos1, ax=axs[1], location=\"right\", shrink=0.7)\n", - "\n", - "\n", - "axs[2].set_title(\"activations\")\n", - "pos2 = axs[2].imshow(W2[:1].T, aspect=\"auto\", interpolation=\"nearest\", norm=norm)\n", - "fig.colorbar(pos2, ax=axs[2], location=\"right\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a2d5bbad-51c0-4252-9acd-d759d0a17c01", - "metadata": {}, - "outputs": [], - "source": [ - "def summarize_mnist_weights(ham, kh=32, kw=32, fig=None):\n", - " # W2 = np.random.normal(size=(10,1024))\n", - " norm = colors.TwoSlopeNorm(vcenter=0)\n", - "\n", - " Wimg = ham.synapses[0].W1\n", - " Wlabel = ham.synapses[0].W2\n", - " \n", - " nWimg = jnp.sqrt(jnp.power(Wimg,2).sum(-2, keepdims=True))\n", - " nWlabel = jnp.sqrt(jnp.power(Wlabel,2).sum(-2, keepdims=True))\n", - " \n", - " Wimg = Wimg / nWimg\n", - " Wlabel = Wlabel / nWlabel\n", - " \n", - " # imgs_big = rearrange(np.repeat(imgs, 11, axis=0)[:1024], \"... h w -> ... (h w)\")[:,0].T\n", - " Wimg_show = rearrange(Wimg, \"(h w) (kh kw) -> (kh h) (kw w)\", h=28, w=28, kh=kh, kw=kw)\n", - " \n", - " if fig is None:\n", - " fig, axs = plt.subplots(1, 2, figsize=(12,6), width_ratios=(2,5))\n", - " else:\n", - " axs = fig.subplots(1, 2, width_ratios=(2,5))\n", - " def prep_axis(ax):\n", - " ax.axis('off')\n", - " [prep_axis(ax) for ax in axs]\n", - "\n", - " pos0 = axs[0].imshow(Wlabel.T[:20], aspect=\"auto\", interpolation=\"nearest\")\n", - " # fig.colorbar(pos0, ax=axs[0], location=\"right\", shrink=0.7)\n", - " axs[0].set_title(\"Label matrix\")\n", - "\n", - " pos1 = axs[1].imshow(Wimg_show, norm=norm)\n", - " axs[1].set_title(\"pixel_matrix\")\n", - " fig.colorbar(pos1, ax=axs[1], location=\"right\", shrink=0.7)\n", - "\n", - "\n", - "# axs[2].set_title(\"activations\")\n", - "# pos2 = axs[2].imshow(W2[:1].T, aspect=\"auto\", interpolation=\"nearest\")\n", - "# fig.colorbar(pos2, ax=axs[2], location=\"right\")\n", - " return fig" - ] - }, - { - "cell_type": "markdown", - "id": "89d52c96-7861-4ed3-9d20-691c23b79311", - "metadata": {}, - "source": [ - "# Model Creation from Scratch\n", - "\n", - "We rewrite the synapse and layer for a simple 2 layer CIFAR network" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "054a2550-d0cd-4346-b386-e340a8e5032a", - "metadata": {}, - "outputs": [], - "source": [ - "def normal_init(std=1.0, mean=0.0):\n", - " def _f(key, shape, dtype=jnp.float64):\n", - " return (jax.random.normal(key, shape, dtype=dtype) * std) + mean\n", - " return _f\n", - "\n", - "class HopfieldNetworkAsSynapse(hmx.Synapse):\n", - " \"\"\"A simple reimplementation of a Hopfield Network as a synapse, returning the alignment\"\"\"\n", - " W1: jnp.ndarray = tx.Parameter.node() # treex's preferred way of declaring an attribute as a parameter\n", - " W2: jnp.ndarray = tx.Parameter.node()\n", - " nhid: int\n", - " beta: float = tx.Parameter.node()\n", - " \n", - " def __init__(self, nhid:int, beta_init=0.1):\n", - " self.nhid = nhid\n", - " self.beta = beta_init\n", - " \n", - " def __call__(self, g1, g2):\n", - " \"\"\"The alignment function, defined on an unbatched `g`\"\"\"\n", - " if self.initializing():\n", - " self.W1 = normal_init(mean=0.0, std=0.01)(tx.next_key(), g1.shape + (self.nhid,))\n", - " self.W2 = normal_init(std=0.01)(tx.next_key(), g2.shape + (self.nhid,))\n", - " # hidsig = g1 @ self.W1 + g2 @ self.W2\n", - " # hidsig = - jnp.abs(self.W1 - g1[:,None]).sum(-2) - jnp.abs(self.W2 - g2[:,None]).sum(-2)\n", - " # hidsig = - jnp.pow(jnp.abs(self.W1 - g1[:,None]),2).sum(-2) - jnp.pow(jnp.abs(self.W2 - g2[:,None]),2).sum(-2)\n", - "\n", - " # nW1 = jnp.abs(self.W1).sum(-2, keepdims=True)\n", - " # nW2 = jnp.abs(self.W2).sum(-2, keepdims=True)\n", - " nW1 = jnp.sqrt(jnp.power(self.W1,2).sum(-2, keepdims=True))\n", - " nW2 = jnp.sqrt(jnp.power(self.W2,2).sum(-2, keepdims=True))\n", - " \n", - " hidsig = g1 @ (self.W1 / nW1) + g2 @ (self.W2 / nW2)\n", - "\n", - " # hid_lagrangian_value = 1/self.beta * jax.nn.logsumexp(self.beta * hidsig, axis=-1)\n", - " hid_lagrangian_value = (1/self.beta * jnp.exp(self.beta * hidsig)).sum(-1)\n", - " return hid_lagrangian_value\n", - " \n", - "ImageLayer = hmx.Layer(hmx.lagrangians.LSphericalNorm(), (28*28,))\n", - "# ImageLayer = hmx.Layer(hmx.lagrangians.LTanh(beta=0.5), (28*28,))\n", - "LabelLayer = hmx.Layer(hmx.lagrangians.LSoftmax(beta=0.005), (10,))\n", - "\n", - "layers = [ImageLayer, LabelLayer]\n", - "synapses = [HopfieldNetworkAsSynapse(nhid=32**2, beta_init=7.)]\n", - "connections = [((0,1),0)]\n", - "ham = hmx.HAM(layers, synapses, connections)" - ] - }, - { - "cell_type": "markdown", - "id": "f9f6a204-b294-49f5-b326-41743405c754", - "metadata": {}, - "source": [ - "A layer is uniquely defined by a lagrangian function and a neuron shape" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "806ff11d-0bf7-4fb3-b1cd-d27c5ce89ea9", - "metadata": {}, - "outputs": [], - "source": [ - "def fwd(model, x, depth=1, dt=0.5, rng=None):\n", - " \"\"\"A pure function to extract desired information from the configured HAM, applied on batched inputs\"\"\"\n", - " # Initialize hidden states to our image\n", - " xs = model.init_states(x.shape[0], rng=rng)\n", - " xs[0] = jnp.array(rearrange(x, \"... c h w -> ... (c h w)\"))\n", - " \n", - " # NORMALIZE IMAGES\n", - " nx = jnp.sqrt(jnp.power(xs[0], 2).sum(-1, keepdims=True))\n", - " xs[0] = xs[0] / nx\n", - "\n", - " # Masks allow us to clamp our visible data over time\n", - " masks = jtu.tree_map(lambda x: jnp.ones_like(x, dtype=jnp.int8), xs)\n", - " masks[0] = jnp.zeros_like(masks[0], dtype=jnp.int8) # Don't evolve images\n", - "\n", - " for i in range(depth):\n", - " updates = model.vupdates(xs) # Calculate the updates\n", - " xs = model.step(\n", - " xs, updates, dt=dt, masks=masks\n", - " ) # Add them to our current states\n", - "\n", - " # All labels have a softmax activation function as the last layer, spitting out probabilities\n", - " return model.layers[-1].g(xs[-1]) # Probs\n", - " # return xs[-1] # Logits" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3eec13cd-ac06-44c0-b07f-077fcaec4679", - "metadata": {}, - "outputs": [], - "source": [ - "imgs_np = np.array(imgs)\n", - "nimg = jnp.sqrt(jnp.power(imgs_np, 2).sum(-1, keepdims=True))\n", - "normed_img = imgs_np / nimg" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d8ef102b-89b8-4b41-8ba2-ed3a805ac5d7", - "metadata": {}, - "outputs": [], - "source": [ - "jax_key = jax.random.PRNGKey(0)\n", - "k1, jax_key = jax.random.split(jax_key)\n", - "lr = 0.001\n", - "num_epochs = 100\n", - "states, ham = ham.init_states_and_params(k1, bs=1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4bd0bc47-9a06-4479-9e52-b95693150e76", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from hamux.datasets import *\n", - "\n", - "dl_args = DataloadingArgs(\n", - " dataset=\"torch/MNIST\",\n", - " # aa=\"rand\",\n", - " aa=None,\n", - " reprob=0.,\n", - " vflip=0.0,\n", - " hflip=0.0,\n", - " scale=(0.9, 1.1),\n", - " batch_size=100,\n", - " color_jitter=0.0,\n", - " validation_batch_size=1000,\n", - ")\n", - "data_config = DataConfigMNIST(input_size=(1, 28, 28), mean=0.5, std=0.5)\n", - "\n", - "train_dl, eval_dl = create_dataloaders(dl_args, data_config)\n", - "\n", - "for batch in train_dl:\n", - " imgs, labels = batch\n", - " break\n", - " \n", - "plt.imshow(data_config.show(imgs[2]))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c44f5d31-883c-448f-a338-b71dc2960ba8", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/optimizer.py:79: FutureWarning: jax.tree_leaves is deprecated, and will be removed in a future release. Use jax.tree_util.tree_leaves instead.\n", - " params = jax.tree_leaves(params)\n", - "2022-12-04 16:11:44.077 | INFO | __main__::31 - NParams=813058\n", - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/module.py:241: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.\n", - " flat, _ = jax.tree_flatten(self)\n", - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/utils.py:167: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.\n", - " tree_types = jax.tree_flatten(\n", - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/utils.py:375: FutureWarning: jax.tree_leaves is deprecated, and will be removed in a future release. Use jax.tree_util.tree_leaves instead.\n", - " count = sum((x.size if hasattr(x, \"size\") else 0 for x in jax.tree_leaves(obj)), 0)\n", - "/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/treex/utils.py:377: FutureWarning: jax.tree_leaves is deprecated, and will be removed in a future release. Use jax.tree_util.tree_leaves instead.\n", - " (x.nbytes if hasattr(x, \"nbytes\") else 0 for x in jax.tree_leaves(obj)), 0\n" - ] - }, - { - "data": { - "text/html": [ - "
┏━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓\n",
-       "┃ path                   module                      params                             Parameter      ┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩\n",
-       "│ *                     │ HAM()                      │                                   │                │\n",
-       "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n",
-       "│ .layers[0]            │ Layer()                    │ bias: None                        │                │\n",
-       "│                       │                            │                                   │                │\n",
-       "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n",
-       "│ .layers[0].lagrangian │ LSphericalNorm()           │                                   │                │\n",
-       "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n",
-       "│ .layers[1]            │ Layer()                    │ bias: None                        │                │\n",
-       "│                       │                            │                                   │                │\n",
-       "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n",
-       "│ .layers[1].lagrangian │ LSoftmax()                 │ beta: 0.005                       │                │\n",
-       "│                       │                            │                                   │                │\n",
-       "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n",
-       "│ .synapses[0]          │ HopfieldNetworkAsSynapse() │ W1: Parameter(784, 1024)  float32813,056  3.3MB │\n",
-       "│                       │                            │ W2: Parameter(10, 1024)   float32 │                │\n",
-       "│                       │                            │ beta: 7.0                         │                │\n",
-       "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n",
-       "│                                                                               Total:  813,056  3.3MB │\n",
-       "└───────────────────────┴────────────────────────────┴───────────────────────────────────┴────────────────┘\n",
-       "                                                                                                           \n",
-       "                                     Total Parameters: 813,056  3.3MB                                      \n",
-       "
\n" - ], - "text/plain": [ - "┏━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓\n", - "┃\u001b[1m \u001b[0m\u001b[1mpath \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mmodule \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mparams \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mParameter \u001b[0m\u001b[1m \u001b[0m┃\n", - "┡━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩\n", - "│ * │ HAM() │ │ │\n", - "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n", - "│ .layers[0] │ Layer() │ bias: None │ │\n", - "│ │ │ │ │\n", - "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n", - "│ .layers[0].lagrangian │ LSphericalNorm() │ │ │\n", - "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n", - "│ .layers[1] │ Layer() │ bias: None │ │\n", - "│ │ │ │ │\n", - "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n", - "│ .layers[1].lagrangian │ LSoftmax() │ beta: 0.005 │ │\n", - "│ │ │ │ │\n", - "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n", - "│ .synapses[0] │ HopfieldNetworkAsSynapse() │ W1: Parameter(\u001b[32m784, 1024\u001b[0m) \u001b[2mfloat32\u001b[0m │ \u001b[32m813,056\u001b[0m \u001b[2m3.3MB\u001b[0m │\n", - "│ │ │ W2: Parameter(\u001b[32m10, 1024\u001b[0m) \u001b[2mfloat32\u001b[0m │ │\n", - "│ │ │ beta: 7.0 │ │\n", - "├───────────────────────┼────────────────────────────┼───────────────────────────────────┼────────────────┤\n", - "│\u001b[1m \u001b[0m\u001b[1m \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1m \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1m Total:\u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1;32m813,056\u001b[0m\u001b[1m \u001b[0m\u001b[1;2m3.3MB\u001b[0m\u001b[1m \u001b[0m│\n", - "└───────────────────────┴────────────────────────────┴───────────────────────────────────┴────────────────┘\n", - "\u001b[1m \u001b[0m\n", - "\u001b[1m Total Parameters: \u001b[0m\u001b[1;32m813,056\u001b[0m\u001b[1m \u001b[0m\u001b[1;2m3.3MB\u001b[0m\u001b[1m \u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-12-04 16:11:44.091 | INFO | __main__::32 - \n" - ] - } - ], - "source": [ - "# ham, forward_classification = hmx.create_model(args.model)\n", - "\n", - "optimizer = optax.adamw(0.0001)\n", - "state = TrainState(\n", - " ham,\n", - " optimizer,\n", - " fwd,\n", - " rng=jax_key,\n", - " filter_betas=True,\n", - ")\n", - "\n", - "\n", - "def get_nparams(model):\n", - " params, meta = jtu.tree_flatten(model.parameters())\n", - "\n", - " def get_nel(x):\n", - " try:\n", - " return x.size\n", - " except AttributeError: # float\n", - " return 1\n", - "\n", - " return sum([get_nel(p) for p in params])\n", - "\n", - "\n", - "def escape_ansi(line):\n", - " import re\n", - "\n", - " ansi_escape = re.compile(r\"(?:\\x1B[@-_]|[\\x80-\\x9F])[0-?]*[ -/]*[@-~]\")\n", - " return ansi_escape.sub(\"\", line)\n", - "\n", - "logger.info(f\"NParams={get_nparams(state.model)}\")\n", - "logger.info(escape_ansi(state.model.tabulate()))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cc02748e-1fd3-49b8-b95c-2bbb4847426e", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch: 1, acc = 0.00\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "42cceb340b17474eb016f36902757a10", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/600 [00:00 1163\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_data_queue\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[38;5;28;01mTrue\u001b[39;00m, data)\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/multiprocessing/queues.py:122\u001b[0m, in \u001b[0;36mQueue.get\u001b[0;34m(self, block, timeout)\u001b[0m\n\u001b[1;32m 121\u001b[0m \u001b[38;5;66;03m# unserialize the data after having released the lock\u001b[39;00m\n\u001b[0;32m--> 122\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_ForkingPickler\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloads\u001b[49m\u001b[43m(\u001b[49m\u001b[43mres\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/torch/multiprocessing/reductions.py:297\u001b[0m, in \u001b[0;36mrebuild_storage_fd\u001b[0;34m(cls, df, size)\u001b[0m\n\u001b[1;32m 296\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrebuild_storage_fd\u001b[39m(\u001b[38;5;28mcls\u001b[39m, df, size):\n\u001b[0;32m--> 297\u001b[0m fd \u001b[38;5;241m=\u001b[39m \u001b[43mdf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdetach\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 298\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/multiprocessing/resource_sharer.py:57\u001b[0m, in \u001b[0;36mDupFd.detach\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 56\u001b[0m \u001b[38;5;124;03m'''Get the fd. This should only be called once.'''\u001b[39;00m\n\u001b[0;32m---> 57\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43m_resource_sharer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_connection\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_id\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m conn:\n\u001b[1;32m 58\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m reduction\u001b[38;5;241m.\u001b[39mrecv_handle(conn)\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/multiprocessing/resource_sharer.py:86\u001b[0m, in \u001b[0;36m_ResourceSharer.get_connection\u001b[0;34m(ident)\u001b[0m\n\u001b[1;32m 85\u001b[0m address, key \u001b[38;5;241m=\u001b[39m ident\n\u001b[0;32m---> 86\u001b[0m c \u001b[38;5;241m=\u001b[39m \u001b[43mClient\u001b[49m\u001b[43m(\u001b[49m\u001b[43maddress\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mauthkey\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcurrent_process\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mauthkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 87\u001b[0m c\u001b[38;5;241m.\u001b[39msend((key, os\u001b[38;5;241m.\u001b[39mgetpid()))\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/multiprocessing/connection.py:513\u001b[0m, in \u001b[0;36mClient\u001b[0;34m(address, family, authkey)\u001b[0m\n\u001b[1;32m 512\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m authkey \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 513\u001b[0m \u001b[43manswer_challenge\u001b[49m\u001b[43m(\u001b[49m\u001b[43mc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mauthkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 514\u001b[0m deliver_challenge(c, authkey)\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/multiprocessing/connection.py:757\u001b[0m, in \u001b[0;36manswer_challenge\u001b[0;34m(connection, authkey)\u001b[0m\n\u001b[1;32m 755\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 756\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAuthkey must be bytes, not \u001b[39m\u001b[38;5;132;01m{0!s}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;28mtype\u001b[39m(authkey)))\n\u001b[0;32m--> 757\u001b[0m message \u001b[38;5;241m=\u001b[39m \u001b[43mconnection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrecv_bytes\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m256\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# reject large message\u001b[39;00m\n\u001b[1;32m 758\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m message[:\u001b[38;5;28mlen\u001b[39m(CHALLENGE)] \u001b[38;5;241m==\u001b[39m CHALLENGE, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmessage = \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m'\u001b[39m \u001b[38;5;241m%\u001b[39m message\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/multiprocessing/connection.py:221\u001b[0m, in \u001b[0;36m_ConnectionBase.recv_bytes\u001b[0;34m(self, maxlength)\u001b[0m\n\u001b[1;32m 220\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnegative maxlength\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m--> 221\u001b[0m buf \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_recv_bytes\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmaxlength\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 222\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m buf \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/multiprocessing/connection.py:419\u001b[0m, in \u001b[0;36mConnection._recv_bytes\u001b[0;34m(self, maxsize)\u001b[0m\n\u001b[1;32m 418\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_recv_bytes\u001b[39m(\u001b[38;5;28mself\u001b[39m, maxsize\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m--> 419\u001b[0m buf \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_recv\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 420\u001b[0m size, \u001b[38;5;241m=\u001b[39m struct\u001b[38;5;241m.\u001b[39munpack(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m!i\u001b[39m\u001b[38;5;124m\"\u001b[39m, buf\u001b[38;5;241m.\u001b[39mgetvalue())\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/multiprocessing/connection.py:384\u001b[0m, in \u001b[0;36mConnection._recv\u001b[0;34m(self, size, read)\u001b[0m\n\u001b[1;32m 383\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m remaining \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m--> 384\u001b[0m chunk \u001b[38;5;241m=\u001b[39m \u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhandle\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mremaining\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 385\u001b[0m n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(chunk)\n", - "\u001b[0;31mConnectionResetError\u001b[0m: [Errno 104] Connection reset by peer", - "\nThe above exception was the direct cause of the following exception:\n", - "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn [15], line 34\u001b[0m\n\u001b[1;32m 31\u001b[0m fig \u001b[38;5;241m=\u001b[39m summarize_mnist_weights(state\u001b[38;5;241m.\u001b[39mmodel)\n\u001b[1;32m 32\u001b[0m display\u001b[38;5;241m.\u001b[39mdisplay(fig)\n\u001b[0;32m---> 34\u001b[0m state, train_loss, train_acc \u001b[38;5;241m=\u001b[39m train_epoch(state, train_dl, epoch)\n\u001b[1;32m 35\u001b[0m test_loss, test_acc \u001b[38;5;241m=\u001b[39m eval_model(state, eval_dl)\n\u001b[1;32m 36\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m test_acc \u001b[38;5;241m>\u001b[39m ckpt_tracker\u001b[38;5;241m.\u001b[39mbest_acc:\n", - "Cell \u001b[0;32mIn [4], line 98\u001b[0m, in \u001b[0;36mtrain_epoch\u001b[0;34m(state, train_dl, epoch)\u001b[0m\n\u001b[1;32m 96\u001b[0m batch_metrics \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 97\u001b[0m bs \u001b[38;5;241m=\u001b[39m train_dl\u001b[38;5;241m.\u001b[39mbatch_size\n\u001b[0;32m---> 98\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, batch \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(tqdm(train_dl, leave\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)):\n\u001b[1;32m 99\u001b[0m batch \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage\u001b[39m\u001b[38;5;124m\"\u001b[39m: jnp\u001b[38;5;241m.\u001b[39marray(batch[\u001b[38;5;241m0\u001b[39m]), \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlabel\u001b[39m\u001b[38;5;124m\"\u001b[39m: jnp\u001b[38;5;241m.\u001b[39marray(batch[\u001b[38;5;241m1\u001b[39m])}\n\u001b[1;32m 100\u001b[0m state, metrics \u001b[38;5;241m=\u001b[39m train_step(state, batch)\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/tqdm/notebook.py:259\u001b[0m, in \u001b[0;36mtqdm_notebook.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 257\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 258\u001b[0m it \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msuper\u001b[39m(tqdm_notebook, \u001b[38;5;28mself\u001b[39m)\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__iter__\u001b[39m()\n\u001b[0;32m--> 259\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m obj \u001b[38;5;129;01min\u001b[39;00m it:\n\u001b[1;32m 260\u001b[0m \u001b[38;5;66;03m# return super(tqdm...) will not catch exception\u001b[39;00m\n\u001b[1;32m 261\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m obj\n\u001b[1;32m 262\u001b[0m \u001b[38;5;66;03m# NB: except ... [ as ...] breaks IPython async KeyboardInterrupt\u001b[39;00m\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/tqdm/std.py:1195\u001b[0m, in \u001b[0;36mtqdm.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1192\u001b[0m time \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_time\n\u001b[1;32m 1194\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1195\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m obj \u001b[38;5;129;01min\u001b[39;00m iterable:\n\u001b[1;32m 1196\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m obj\n\u001b[1;32m 1197\u001b[0m \u001b[38;5;66;03m# Update and possibly print the progressbar.\u001b[39;00m\n\u001b[1;32m 1198\u001b[0m \u001b[38;5;66;03m# Note: does not call self.update(1) for speed optimisation.\u001b[39;00m\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/torch/utils/data/dataloader.py:681\u001b[0m, in \u001b[0;36m_BaseDataLoaderIter.__next__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 678\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sampler_iter \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 679\u001b[0m \u001b[38;5;66;03m# TODO(https://github.com/pytorch/pytorch/issues/76750)\u001b[39;00m\n\u001b[1;32m 680\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_reset() \u001b[38;5;66;03m# type: ignore[call-arg]\u001b[39;00m\n\u001b[0;32m--> 681\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_next_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 682\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_yielded \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 683\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dataset_kind \u001b[38;5;241m==\u001b[39m _DatasetKind\u001b[38;5;241m.\u001b[39mIterable \u001b[38;5;129;01mand\u001b[39;00m \\\n\u001b[1;32m 684\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_IterableDataset_len_called \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \\\n\u001b[1;32m 685\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_yielded \u001b[38;5;241m>\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_IterableDataset_len_called:\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/torch/utils/data/dataloader.py:1359\u001b[0m, in \u001b[0;36m_MultiProcessingDataLoaderIter._next_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1356\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_data(data)\n\u001b[1;32m 1358\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_shutdown \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tasks_outstanding \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m-> 1359\u001b[0m idx, data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1360\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tasks_outstanding \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 1361\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dataset_kind \u001b[38;5;241m==\u001b[39m _DatasetKind\u001b[38;5;241m.\u001b[39mIterable:\n\u001b[1;32m 1362\u001b[0m \u001b[38;5;66;03m# Check for _IterableDatasetStopIteration\u001b[39;00m\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/torch/utils/data/dataloader.py:1325\u001b[0m, in \u001b[0;36m_MultiProcessingDataLoaderIter._get_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1321\u001b[0m \u001b[38;5;66;03m# In this case, `self._data_queue` is a `queue.Queue`,. But we don't\u001b[39;00m\n\u001b[1;32m 1322\u001b[0m \u001b[38;5;66;03m# need to call `.task_done()` because we don't use `.join()`.\u001b[39;00m\n\u001b[1;32m 1323\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1324\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m-> 1325\u001b[0m success, data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_try_get_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1326\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m success:\n\u001b[1;32m 1327\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m data\n", - "File \u001b[0;32m/nethome/bhoover30/miniconda3/envs/hamux/lib/python3.9/site-packages/torch/utils/data/dataloader.py:1176\u001b[0m, in \u001b[0;36m_MultiProcessingDataLoaderIter._try_get_data\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 1174\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(failed_workers) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 1175\u001b[0m pids_str \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;28mstr\u001b[39m(w\u001b[38;5;241m.\u001b[39mpid) \u001b[38;5;28;01mfor\u001b[39;00m w \u001b[38;5;129;01min\u001b[39;00m failed_workers)\n\u001b[0;32m-> 1176\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDataLoader worker (pid(s) \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m) exited unexpectedly\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(pids_str)) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[1;32m 1177\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e, queue\u001b[38;5;241m.\u001b[39mEmpty):\n\u001b[1;32m 1178\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[38;5;28;01mNone\u001b[39;00m)\n", - "\u001b[0;31mRuntimeError\u001b[0m: DataLoader worker (pid(s) 976703, 976960) exited unexpectedly" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "from IPython import display\n", - "\n", - "# ===========================================\n", - "## Training\n", - "# ===========================================\n", - "@dataclass\n", - "class CkptTracker:\n", - " base_name: str\n", - " model: tx.Module = None\n", - " epoch: int = -1\n", - " best_acc: float = -1\n", - "\n", - " def get_save_name(self):\n", - " return f\"{self.base_name}_epoch-{self.epoch}_acc-{100*self.best_acc:.3f}.pckl\"\n", - "\n", - "\n", - "train_acc_list = []\n", - "test_acc_list = []\n", - "ckpt_tracker = CkptTracker(\"DummyMNIST\")\n", - "logdir = Path(\"./_logs\")\n", - "logdir.mkdir(exist_ok=True, parents=True)\n", - "\n", - "# fig, axs = plt.subplots(1, 2, figsize=(12,6), width_ratios=(2,5))\n", - "test_acc = 0\n", - "with trange(1, num_epochs + 1, unit=\"epochs\") as pbar:\n", - " for epoch in pbar:\n", - " if (epoch-1) % 1 == 0:\n", - " display.clear_output(wait=True)\n", - " print(f\"Epoch: {epoch}, acc = {100*test_acc:0.2f}\")\n", - " fig = summarize_mnist_weights(state.model)\n", - " display.display(fig)\n", - "\n", - " state, train_loss, train_acc = train_epoch(state, train_dl, epoch)\n", - " test_loss, test_acc = eval_model(state, eval_dl)\n", - " if test_acc > ckpt_tracker.best_acc:\n", - " old_ckpt_name = str(logdir / ckpt_tracker.get_save_name())\n", - " try:\n", - " os.remove(old_ckpt_name)\n", - " except Exception as e:\n", - " logger.debug(f\"Couldn't remove {old_ckpt_name}, {e}\")\n", - " pass\n", - " ckpt_tracker.model = state.model\n", - " ckpt_tracker.epoch = epoch\n", - " ckpt_tracker.best_acc = test_acc\n", - " to_save = jtu.tree_map(hmx.utils.to_pickleable, ckpt_tracker.model.to_dict())\n", - " ckpt_name = str(logdir / ckpt_tracker.get_save_name())\n", - " hmx.utils.pytree_save(to_save, ckpt_name, overwrite=True)\n", - " desc = f\"[{epoch}/{num_epochs}] | BestAcc: {100*ckpt_tracker.best_acc:.3f} | TrainLoss: {train_loss:.2f} | TrainAcc: {100*train_acc:.2f}\"\n", - " addition = f\"curr_val_acc={100*test_acc:0.2f}\"\n", - " logger.info(desc + \" | \" + addition)\n", - " pbar.set_description(desc)\n", - " pbar.set_postfix(\n", - " train_acc=f\"{100*train_acc:0.2f}\", val_acc=f\"{100*test_acc:0.2f}\"\n", - " )\n" - ] - }, - { - "cell_type": "markdown", - "id": "5cd9ac28-6947-4860-ab47-b842f1bef280", - "metadata": {}, - "source": [ - "# Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "13d98994-2788-442e-b78e-5784dfe5d4c8", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "model_fname = \"_logs/DummyMNIST_epoch-67_acc-97.890.pckl\"\n", - "loaded_model = hmx.HAM.load_ckpt(state.model, model_fname)\n", - "summarize_mnist_weights(loaded_model);" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "40b57a9b-38f9-4862-b9f7-ad0cee168091", - "metadata": {}, - "outputs": [], - "source": [ - "a = jnp.zeros((2,3,45,))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3f5398c4-3152-4701-a5da-e50c16d9ad71", - "metadata": {}, - "outputs": [], - "source": [ - "def fwd_energy(model, x, depth=4, dt=0.4, rng=None):\n", - " \"\"\"A pure function to extract desired information from the configured HAM, applied on batched inputs\"\"\"\n", - " # Initialize hidden states to our image\n", - " xs = model.init_states(x.shape[0], rng=rng)\n", - " xs[0] = jnp.array(rearrange(x, \"... c h w -> ... (c h w)\"))\n", - " \n", - " # Masks allow us to clamp our visible data over time\n", - " masks = jtu.tree_map(lambda x: jnp.ones_like(x, dtype=jnp.int8), xs)\n", - " \n", - " # if clamp_label is not None:\n", - " # xs[-1] = jnp.zeros_like(xs[-1]).at[...,clamp_label].set(1.)\n", - " # print(xs[-1])\n", - " # masks[-1] = jnp.zeros_like(masks[-1])\n", - "\n", - " # masks[0] = jnp.zeros_like(masks[0], dtype=jnp.int8) # Don't evolve images\n", - " all_xs = [xs]\n", - " energies = [model.venergy(xs)]\n", - "\n", - " for i in range(depth):\n", - " updates = model.vupdates(xs) # Calculate the updates\n", - " xs = model.step(\n", - " xs, updates, dt=dt, masks=masks\n", - " ) # Add them to our current states\n", - " all_xs.append(xs)\n", - " energies.append(model.venergy(xs))\n", - "\n", - " # All labels have a softmax activation function as the last layer, spitting out probabilities\n", - " return jnp.stack(energies), all_xs" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b54725f1-a671-4ed5-bae2-8278d811ac81", - "metadata": {}, - "outputs": [], - "source": [ - "img_start = batch[0][:1]\n", - "# img_start = jnp.ones_like(jnp.array(img_start))\n", - "energies, allxs = fwd_energy(loaded_model, img_start, dt=0.01, depth=30)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fefc1721-3741-45ff-9f8f-cdd093f3ad1e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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xo0ePNi6Xy5xxxhnmrbfeCjve1tZmvv3tb5v8/HyTmZlpLr30UrN3796wMf2p5VhYAi42Tv/hX82YRSvMx3s5rwAA4MT0N685jDHGxoyeULxer3Jzc9XY2CiPx2N3OQnjvAde1Y6DrVp+c6X+8aQCu8sBAABxrL95zbYl4ID+yumeYuFtY4ULAAAwOAjJGPLYUAQAAAw2QjKGvNDFek2slQwAAAYJIRlDXs+GInSSAQDA4CAkY8jLSWdragAAMLgIyRjy2JoaAAAMNkIyhjwu3AMAAIONkIwhz5PBhXsAAGBwEZIx5HnoJAMAgEFGSMaQx2YiAABgsBGSMeQxJxkAAAw2QjKGvBw2EwEAAIOMkIwhLzQnuaXDL3/A2FwNAABIBoRkDHmhTrIkNTPlAgAADAJCMoY8V6pT7tTgT5UNRQAAwGAgJCMuWCtcEJIBAMAgICQjLngyWOECAAAMHkIy4kLPCheEZAAAEHuEZMSFnl33mG4BAABij5CMuBDaUIRd9wAAwGAgJCMu5LiZbgEAAAYPIRlxwbpwz0dIBgAAsUdIRlxga2oAADCYCMmIC9acZKZbAACAQUBIRlywNhPhwj0AADAICMmICznpbCYCAAAGDyEZccHDnGQAADCICMmIC3SSAQDAYCIkIy6EOsleOskAAGAQEJIRF0Kd5PbOgDr9AZurAQAAiY6QjLgQCskSUy4AAEDsEZIRF1JTnMp0pUji4j0AABB7hGTEDS7eAwAAg4WQjLjBhiIAAGCwEJIRN9iaGgAADBZCMuIGG4oAAIDBQkhG3GBOMgAAGCyEZMSNHKuTTEgGAACxRUhG3PBYc5KZbgEAAGKLkIy40TPdgpAMAABii5CMuOHJYLoFAAAYHIRkxA0u3AMAAIOFkIy4keNmCTgAADA4CMmIG2wmAgAABgshGXGjZ04ynWQAABBbhGTEDTrJAABgsBCSETdCm4l0dAXU3um3uRoAAJDICMmIG9nuVOsxK1wAAIBYIiQjbqQ4HVZQZl4yAACIJUIy4oqHtZIBAMAgICQjroTmJROSAQBALBGSEVd6dt1jugUAAIgdQjLiSs8ycIRkAAAQO4RkxBWmWwAAgMFASEZc8WSwoQgAAIg9QjLiSk8nmekWAAAgdgjJiCs5LAEHAAAGASEZcSXUSfa20UkGAACxQ0hGXGEzEQAAMBgIyYgrntCcZB+dZAAAEDuEZMQV5iQDAIDBQEhGXGFOMgAAGAyEZMSV3p1kY4zN1QAAgERFSEZc8WQEO8ldAaP2zoDN1QAAgERFSEZcyXKlyOkIPmZDEQAAECuEZMQVh8OhbDdbUwMAgNgiJCPuWBfv0UkGAAAxQkhG3GEZOAAAEGuEZMSd0MV7zEkGAACxQkhG3GFragAAEGuEZMSd0JxkOskAACBWCMmIO6E5yd42OskAACA2CMmIOx46yQAAIMYIyYg7rG4BAABijZCMuNOzTjIhGQAAxAYhGXGnp5PMdAsAABAbhGTEHevCPTrJAAAgRgjJiDtsJgIAAGKNkIy4w2YiAAAg1gjJiDu9NxMxxthcDQAASESEZMSd0JzkgJFaOvw2VwMAABIRIRlxJyMtRSlOhyTmJQMAgNggJCPuOBwO5iUDAICYIiQjLuWwNTUAAIghQjLiEmslAwCAWCIkIy5ZIbmNTjIAAIg+QjLikseabkEnGQAARB8hGXEph5AMAABiiJCMuJRjrW7BdAsAABB9hGTEJZaAAwAAsURIRlwKTbfw0kkGAAAxQEhGXPJk0EkGAACxQ0hGXGIzEQAAEEuEZMSlHOYkAwCAGCIkIy6xBBwAAIglQjLiEjvuAQCAWCIkIy6Fdtxr7uhSIGBsrgYAACQaQjLiUqiTbEwwKAMAAEQTIRlxKT0tRa6U4M+XeckAACDaCMmIW8xLBgAAsUJIRtzyZLDCBQAAiA1CMuJWz1rJdJIBAEB0EZIRt9hQBAAAxAohGXErx83W1AAAIDYIyYhb1oV7dJIBAECUEZIRt0IX7nnpJAMAgCiLWUjesWOH5s6dq/LycmVkZGjcuHG655571NHRETZu/fr1Ouecc5Senq5Ro0Zp6dKlh33W8uXLNWnSJKWnp+uUU07Riy++GHbcGKO7775bpaWlysjIUFVVlbZs2RI2pr6+XnPmzJHH41FeXp7mzp2r5ubmAdeCoYM5yQAAIFZiFpI3bdqkQCCgX//619q4caMefPBBLVu2TN///vetMV6vV7NmzdKYMWO0du1aPfDAA7r33nv12GOPWWNWr16tK6+8UnPnztX777+v2bNna/bs2dqwYYM1ZunSpXr44Ye1bNkyrVmzRllZWaqurlZ7e7s1Zs6cOdq4caNWrlypFStW6I033tCNN944oFowtOSkswQcAACIETOIli5dasrLy63njz76qMnPzzc+n896bdGiRWbixInW82984xvm4osvDvuciooKc9NNNxljjAkEAqakpMQ88MAD1vGGhgbjdrvN008/bYwx5qOPPjKSzDvvvGONeemll4zD4TC7d+/udy3H0tjYaCSZxsbGfr8Hx++Zd3aaMYtWmGv+7xq7SwEAAHGiv3ltUOckNzY2qqCgwHpeU1Ojc889Vy6Xy3qturpamzdv1qFDh6wxVVVVYZ9TXV2tmpoaSdL27dtVW1sbNiY3N1cVFRXWmJqaGuXl5WnmzJnWmKqqKjmdTq1Zs6bftUTy+Xzyer1hNwweDzvuAQCAGBm0kLx161Y98sgjuummm6zXamtrVVxcHDYu9Ly2trbPMb2P937f0cYMHz487HhqaqoKCgqO+T29vyPSkiVLlJuba91GjRrV1ylAlHmYbgEAAGJkwCH5jjvukMPh6PO2adOmsPfs3r1bF154ob7+9a/rhhtuiFrxdlu8eLEaGxut265du+wuKakwJxkAAMRK6kDfcNttt+naa6/tc8zYsWOtx3v27NH555+vM88887CL4EpKSlRXVxf2Wuh5SUlJn2N6Hw+9VlpaGjZm+vTp1ph9+/aFfUZXV5fq6+uP+T29vyOS2+2W2+0+4jHEHttSAwCAWBlwJ7moqEiTJk3q8xaa17t7926dd955mjFjhh5//HE5neFfV1lZqTfeeEOdnT0hZ+XKlZo4caLy8/OtMatWrQp738qVK1VZWSlJKi8vV0lJSdgYr9erNWvWWGMqKyvV0NCgtWvXWmNeeeUVBQIBVVRU9LsWDC2hkNzS4VeXP2BzNQAAIJHEbE5yKCCPHj1a//Zv/6b9+/ertrY2bH7vVVddJZfLpblz52rjxo165pln9NBDD2nhwoXWmO985zt6+eWX9bOf/UybNm3Svffeq3fffVfz58+XJDkcDi1YsED33Xef/vSnP+nDDz/U1VdfrbKyMs2ePVuSNHnyZF144YW64YYb9Pbbb+vNN9/U/PnzdcUVV6isrKzftWBoCU23kKRmH1MuAABAFMVqeY3HH3/cSDrirbcPPvjAnH322cbtdpsRI0aY+++//7DPevbZZ82ECROMy+UyU6dONS+88ELY8UAgYO666y5TXFxs3G63ueCCC8zmzZvDxhw8eNBceeWVJjs723g8HnPdddeZpqamAdfSF5aAG3wT73zRjFm0wuw82GJ3KQAAIA70N685jDHGvoieWLxer3Jzc9XY2CiPx2N3OUnhH3/8N+1v8umFfzlbU8ty7S4HAAAMcf3Na4O6TjIQbWxNDQAAYoGQjLgWmpfMhiIAACCaCMmIax46yQAAIAYIyYhrPbvu0UkGAADRQ0hGXGNOMgAAiAVCMuKaFZJZJxkAAEQRIRlxjQv3AABALBCSEde4cA8AAMQCIRlxzeokc+EeAACIIkIy4hoX7gEAgFggJCOu5bAEHAAAiAFCMuKaJyPYSfbSSQYAAFFESEZcYzMRAAAQC4RkxLXQnOT2zoA6/QGbqwEAAImCkIy4lu1OtR5z8R4AAIgWQjLiWmqKU5muFElsKAIAAKKHkIy41zMvmU4yAACIDkIy4l7PWsl0kgEAQHQQkhH3QiGZZeAAAEC0EJIR99hQBAAARBshGXGPTjIAAIg2QjLinieDTjIAAIguQjLiXs+Fe3SSAQBAdBCSEffYmhoAAEQbIRlxj04yAACINkIy4l6ok+ylkwwAAKKEkIy4RycZAABEGyEZcS+HbakBAECUEZIR99iWGgAARBshGXGPzUQAAEC0EZIR90KbiXR0BdTe6be5GgAAkAgIyYh72a5UORzBx8xLBgAA0UBIRtxzOh3KdjEvGQAARA8hGQmBZeAAAEA0EZKREHLYUAQAAEQRIRkJwZNBJxkAAEQPIRkJoWdDETrJAADgxBGSkRCYkwwAAKKJkIyEwIYiAAAgmgjJSAie0IV7bUy3AAAAJ46QjITQMyeZTjIAADhxhGQkhJ45yXSSAQDAiSMkIyFw4R4AAIgmQjISQmhOcpOPTjIAADhxhGQkhNBmIt42OskAAODEEZKRENhMBAAARBMhGQmh95xkY4zN1QAAgHhHSEZCCHWSuwJG7Z0Bm6sBAADxjpCMhJDlSpHTEXzsZcoFAAA4QYRkJASHw8G8ZAAAEDWEZCSM0LxkL2slAwCAE0RIRsJga2oAABAthGQkDLamBgAA0UJIRsII7brHhiIAAOBEEZKRMDx0kgEAQJQQkpEwem8oAgAAcCIIyUgYLAEHAACihZCMhEEnGQAARAshGQnDk9F94R6dZAAAcIIIyUgYbCYCAACihZCMhMFmIgAAIFoIyUgYbCYCAACihZCMhOGhkwwAAKKEkIyE0XszEWOMzdUAAIB4RkhGwgjNSQ4YqaXDb3M1AAAgnhGSkTDS05xKdTokMS8ZAACcGEIyEobD4WBDEQAAEBWEZCQUa0ORNjrJAADg+BGSkVDoJAMAgGggJCOh5LjZmhoAAJw4QjISCp1kAAAQDYRkJBS2pgYAANFASEZC8WQEO8lMtwAAACeCkIyE0tNJJiQDAIDjR0hGQvEwJxkAAEQBIRkJhQv3AABANBCSkVA8TLcAAABRQEhGQgnNSfa20UkGAADHj5CMhNIz3YJOMgAAOH6EZCQU5iQDAIBoICQjoYSmWzR3dCkQMDZXAwAA4hUhGQkl1Ek2JhiUAQAAjgchGQklPS1FrtTgz9rbxrxkAABwfAjJSDhsKAIAAE4UIRkJp2drakIyAAA4PoRkJByWgQMAACeKkIyEE9p1z0tIBgAAx4mQjITDWskAAOBEEZKRcAjJAADgRBGSkXBymG4BAABOECEZCcfD6hYAAOAEEZKRcELTLdhMBAAAHC9CMhIOc5IBAMCJIiQj4fRsJkInGQAAHB9CMhIO21IDAIATRUhGwvFkcOEeAAA4MYRkJBzrwj2mWwAAgONESEbCCc1Jbu3wq8sfsLkaAAAQjwjJSDihTrIkNfuYcgEAAAaOkIyEk5biVHpa8KfNvGQAAHA8CMlISKFd9xrZUAQAABwHQjISEhuKAACAE0FIRkJiQxEAAHAiCMlISHSSAQDAiSAkIyH1bChCJxkAAAwcIRkJyWNtKEInGQAADFxMQ/JXvvIVjR49Wunp6SotLdU3v/lN7dmzJ2zM+vXrdc455yg9PV2jRo3S0qVLD/uc5cuXa9KkSUpPT9cpp5yiF198Mey4MUZ33323SktLlZGRoaqqKm3ZsiVsTH19vebMmSOPx6O8vDzNnTtXzc3NA64F8YE5yQAA4ETENCSff/75evbZZ7V582b94Q9/0LZt2/S1r33NOu71ejVr1iyNGTNGa9eu1QMPPKB7771Xjz32mDVm9erVuvLKKzV37ly9//77mj17tmbPnq0NGzZYY5YuXaqHH35Yy5Yt05o1a5SVlaXq6mq1t7dbY+bMmaONGzdq5cqVWrFihd544w3deOONA6oF8SPHzZxkAABwAswgev75543D4TAdHR3GGGMeffRRk5+fb3w+nzVm0aJFZuLEidbzb3zjG+biiy8O+5yKigpz0003GWOMCQQCpqSkxDzwwAPW8YaGBuN2u83TTz9tjDHmo48+MpLMO++8Y4156aWXjMPhMLt37+53LZHa29tNY2Ojddu1a5eRZBobGwd8bhBdj//9UzNm0Qrz7f9ca3cpAABgCGlsbOxXXhu0Ocn19fX63e9+pzPPPFNpacF/Cq+pqdG5554rl8tljauurtbmzZt16NAha0xVVVXYZ1VXV6umpkaStH37dtXW1oaNyc3NVUVFhTWmpqZGeXl5mjlzpjWmqqpKTqdTa9as6XctkZYsWaLc3FzrNmrUqOM+P4iu0IV7XqZbAACA4xDzkLxo0SJlZWVp2LBh2rlzp55//nnrWG1trYqLi8PGh57X1tb2Oab38d7vO9qY4cOHhx1PTU1VQUHBMb+n93dEWrx4sRobG63brl27+joVGEShOclcuAcAAI7HgEPyHXfcIYfD0edt06ZN1vjvfe97ev/99/XXv/5VKSkpuvrqq2WMieofwi5ut1sejyfshqGhZ51kOskAAGDgUgf6httuu03XXnttn2PGjh1rPS4sLFRhYaEmTJigyZMna9SoUXrrrbdUWVmpkpIS1dXVhb039LykpMS6P9KY3sdDr5WWloaNmT59ujVm3759YZ/R1dWl+vr6Y35P7+9A/GAzEQAAcCIG3EkuKirSpEmT+rz1ntfbWyAQkCT5fD5JUmVlpd544w11dvZ0+1auXKmJEycqPz/fGrNq1aqwz1m5cqUqKyslSeXl5SopKQkb4/V6tWbNGmtMZWWlGhoatHbtWmvMK6+8okAgoIqKin7XgvjhYQk4AABwAmI2J3nNmjX6xS9+oXXr1umzzz7TK6+8oiuvvFLjxo2zwutVV10ll8uluXPnauPGjXrmmWf00EMPaeHChdbnfOc739HLL7+sn/3sZ9q0aZPuvfdevfvuu5o/f74kyeFwaMGCBbrvvvv0pz/9SR9++KGuvvpqlZWVafbs2ZKkyZMn68ILL9QNN9ygt99+W2+++abmz5+vK664QmVlZf2uBfEjFJLbOwPq6ArYXA0AAIg7sVpeY/369eb88883BQUFxu12m5NOOsncfPPN5vPPPw8b98EHH5izzz7buN1uM2LECHP//fcf9lnPPvusmTBhgnG5XGbq1KnmhRdeCDseCATMXXfdZYqLi43b7TYXXHCB2bx5c9iYgwcPmiuvvNJkZ2cbj8djrrvuOtPU1DTgWvrS3yVFEHtd/oAZs2iFGbNohTnQ1G53OQAAYIjob15zGJMgV9ENAV6vV7m5uWpsbOQiviFg6t0vq6XDr9e+e55OKsyyuxwAADAE9DevDdo6ycBg69mamov3AADAwBCSkbA8GSwDBwAAjg8hGQmrZ0MRQjIAABgYQjISVmitZHbdAwAAA0VIRsJiTjIAADhehGQkLLamBgAAx4uQjITloZMMAACOEyEZCcuak9xGJxkAAAwMIRkJy2NNt6CTDAAABoaQjIRlXbjno5MMAAAGhpCMhJVDJxkAABwnQjISlieDC/cAAMDxISQjYXHhHgAAOF6EZCQsNhMBAADHi5CMhBXqJHf4A2rv9NtcDQAAiCeEZCSsbFeqHI7gY7rJAABgIAjJSFhOp0PZ7u55yWxNDQAABoCQjITG1tQAAOB4EJKR0HrWSqaTDAAA+o+QjITGhiIAAOB4EJKR0HqmW9BJBgAA/UdIRkLr2VCETjIAAOg/QjISWg6dZAAAcBwIyUhoVieZOckAAGAACMlIaGxNDQAAjgchGQnNk8EScAAAYOAIyUhooU4yO+4BAICBICQjobFOMgAAOB6EZCQ0DyEZAAAcB0IyEhqbiQAAgONBSEZC6726hTHG5moAAEC8ICQjoYXmJHcFjNo6/TZXAwAA4gUhGQkt05WiFKdDEvOSAQBA/xGSkdAcDoey3ayVDAAABoaQjIQX2lCErakBAEB/EZKR8HLc3RuKtNFJBgAA/UNIRsJjQxEAADBQhGQkvN7LwAEAAPQHIRkJr2fXPaZbAACA/iEkI+F5MugkAwCAgSEkI+GF5iR76SQDAIB+IiQj4XHhHgAAGChCMhJez4V7dJIBAED/EJKR8DzdIZnNRAAAQH8RkpHwmG4BAAAGipCMhGdduMeOewAAoJ8IyUh4zEkGAAADRUhGwgttJtLs65IxxuZqAABAPCAkI+GFNhMJGKmlw29zNQAAIB4QkpHw3KlOpaU4JDHlAgAA9A8hGQnP4XBY85K9baxwAQAAjo2QjKTQswwcnWQAAHBshGQkBdZKBgAAA0FIRlLIz3RJkvY3+2yuBAAAxANCMpLCuKJsSdLm2iabKwEAAPGAkIykMKXUI0n6eK/X5koAAEA8ICQjKUwp6wnJbCgCAACOhZCMpDB+eLZSnA4dau1Urbfd7nIAAMAQR0hGUkhPS9G4oixJTLkAAADHRkhG0uiZl8zFewAAoG+EZCSNyd0h+aM9dJIBAEDfCMlIGpNZ4QIAAPQTIRlJIxSStx9sUWsHO+8BAICjIyQjaRTluFWU45Yx0iY2FQEAAH0gJCOpMOUCAAD0ByEZSYWd9wAAQH8QkpFUJpfmSGKFCwAA0DdCMpJKqJO8qbZJgQDbUwMAgCMjJCOplBdmyZ3qVGuHXzvrW+0uBwAADFGEZCSV1BSnJpZ0T7lgXjIAADgKQjKSzuQSLt4DAAB9IyQj6UwpIyQDAIC+EZKRdEJrJbPCBQAAOBpCMpLOpO5l4PY0tquhtcPmagAAwFBESEbS8aSnaVRBhiTp471sTw0AAA5HSEZSCl28xwoXAADgSAjJSEqT2Z4aAAD0gZCMpMQKFwAAoC+EZCSl0PbUW+qa1ekP2FwNAAAYagjJSEoj8zOU405Vhz+gbfub7S4HAAAMMYRkJCWHw8G8ZAAAcFSEZCStyd3rJbOpCAAAiERIRtLq6SSzVjIAAAhHSEbS6r3ChTHG5moAAMBQQkhG0ppQnCOnQzrY0qF9TT67ywEAAEMIIRlJKz0tRWOLsiWx8x4AAAhHSEZSm8IKFwAA4AgIyUhqoYv3WOECAAD0RkhGUgstA0cnGQAA9EZIRlILrXCx/UCL2jr8NlcDAACGCkIyktrwnHQVZrsUMNLmOtZLBgAAQYRkJD22pwYAAJEIyUh6rHABAAAiEZKR9FjhAgAARCIkI+mFQvKm2iYFAmxPDQAACMmAxhZlyZXqVLOvS58farO7HAAAMAQQkpH00lKcmlAc2p660eZqAADAUEBIBiRNLumel7yXZeAAAAAhGZDUs6kIK1wAAACJkAxIYoULAAAQjpAMqGe6xe6GNjW2ddpcDQAAsBshGZCUm5mmEXkZkqRNTLkAACDpEZKBbtaUC0IyAABJj5AMdJtSmiOJi/cAAAAhGbD0rHDBMnAAACQ7QjLQLTTdYnNdk7r8AZurAQAAdhqUkOzz+TR9+nQ5HA6tW7cu7Nj69et1zjnnKD09XaNGjdLSpUsPe//y5cs1adIkpaen65RTTtGLL74YdtwYo7vvvlulpaXKyMhQVVWVtmzZEjamvr5ec+bMkcfjUV5enubOnavm5uYB14LENSo/U9nuVHV0BfTpgRa7ywEAADYalJB8++23q6ys7LDXvV6vZs2apTFjxmjt2rV64IEHdO+99+qxxx6zxqxevVpXXnml5s6dq/fff1+zZ8/W7NmztWHDBmvM0qVL9fDDD2vZsmVas2aNsrKyVF1drfb2dmvMnDlztHHjRq1cuVIrVqzQG2+8oRtvvHFAtSCxOZ0OTSoJzktmvWQAAJKcibEXX3zRTJo0yWzcuNFIMu+//7517NFHHzX5+fnG5/NZry1atMhMnDjRev6Nb3zDXHzxxWGfWVFRYW666SZjjDGBQMCUlJSYBx54wDre0NBg3G63efrpp40xxnz00UdGknnnnXesMS+99JJxOBxm9+7d/a4lUnt7u2lsbLRuu3btMpJMY2PjQE4RhpA7//ihGbNohfnJCx/ZXQoAAIiBxsbGfuW1mHaS6+rqdMMNN+i3v/2tMjMzDzteU1Ojc889Vy6Xy3qturpamzdv1qFDh6wxVVVVYe+rrq5WTU2NJGn79u2qra0NG5Obm6uKigprTE1NjfLy8jRz5kxrTFVVlZxOp9asWdPvWiItWbJEubm51m3UqFEDOj8YekIX77EMHAAAyS1mIdkYo2uvvVY333xzWDjtrba2VsXFxWGvhZ7X1tb2Oab38d7vO9qY4cOHhx1PTU1VQUHBMb+n93dEWrx4sRobG63brl27jjgO8SN08R7LwAEAkNwGHJLvuOMOORyOPm+bNm3SI488oqamJi1evDgWdQ8JbrdbHo8n7Ib4NrE4R06HdKC5Q/ua2o/9BgAAkJBSB/qG2267Tddee22fY8aOHatXXnlFNTU1crvdYcdmzpypOXPm6Mknn1RJSYnq6urCjoeel5SUWPdHGtP7eOi10tLSsDHTp0+3xuzbty/sM7q6ulRfX3/M7+n9HUh8Ga4UlRdmadv+Fn28t0nDc9LtLgkAANhgwJ3koqIiTZo0qc+by+XSww8/rA8++EDr1q3TunXrrGXbnnnmGf34xz+WJFVWVuqNN95QZ2en9fkrV67UxIkTlZ+fb41ZtWpVWA0rV65UZWWlJKm8vFwlJSVhY7xer9asWWONqaysVENDg9auXWuNeeWVVxQIBFRRUdHvWpAcrO2pWeECAICkFbM5yaNHj9a0adOs24QJEyRJ48aN08iRIyVJV111lVwul+bOnauNGzfqmWee0UMPPaSFCxdan/Od73xHL7/8sn72s59p06ZNuvfee/Xuu+9q/vz5kiSHw6EFCxbovvvu05/+9Cd9+OGHuvrqq1VWVqbZs2dLkiZPnqwLL7xQN9xwg95++229+eabmj9/vq644gprabr+1ILkwLxkAAAw4OkW0ZSbm6u//vWvmjdvnmbMmKHCwkLdfffdYesXn3nmmXrqqad055136vvf/75OPvlkPffcc5o2bZo15vbbb1dLS4tuvPFGNTQ06Oyzz9bLL7+s9PSefyr/3e9+p/nz5+uCCy6Q0+nUZZddpocffnhAtSA59GxPTUgGACBZOYwxxu4iEoXX61Vubq4aGxu5iC+O1XnbVfGTVXI6pI9+eKHS01LsLgkAAERJf/PaoOy4B8ST4TluFWS5FDDSJ3VNdpcDAABsQEgGIjgcDk1hXjIAAEmNkAwcweTSHEmscAEAQLIiJANH0LPCBdMtAABIRoRk4Ah6r3DBta0AACQfQjJwBOOKsuVKcarJ16XPD7XZXQ4AABhkhGTgCNJSnBo/PFuS9BEX7wEAkHQIycBRsKkIAADJi5AMHEXo4j1WuAAAIPkQkoGjCC0D93EtIRkAgGRDSAaOIrShyK76NnnbO22uBgAADCZCMnAUeZkuleWmS5I2sV4yAABJhZAM9GEy21MDAJCUCMlAH1jhAgCA5ERIBvpgrXBBSAYAIKkQkoE+hELy5tomdfkDNlcDAAAGCyEZ6MOYgkxlulLk6wpox8EWu8sBAACDhJAM9MHpdGhSSXC95I1sKgIAQNIgJAPH0LPCBcvAAQCQLAjJwDGwwgUAAMmHkAwcAytcAACQfAjJwDFMKsmRwyHtb/LpQLPP7nIAAMAgICQDx5DpSlX5sCxJTLkAACBZEJKBfrCmXLDCBQAASYGQDPTD5NLgMnB0kgEASA6EZKAfela4YBk4AACSASEZ6IfQdIut+5vV3um3uRoAABBrhGSgH0o86crLTJM/YLR1X7Pd5QAAgBgjJAP94HA4NIX1kgEASBqEZKCfWOECAIDkQUgG+ikUklnhAgCAxEdIBvppSq+QbIyxuRoAABBLhGSgn8YPz1ZaikPe9i7tbmizuxwAABBDhGSgn1ypTo0rypbEeskAACQ6QjIwAD2bijAvGQCAREZIBgZgCitcAACQFAjJwABYK1zUEpIBAEhkhGRgAEIh+bODrdpxoMXmagAAQKwQkoEBKMhy6bSRuZKkr/+6hrnJAAAkKEIyMEC/uXqmJpXkaH+TT5f/ukbv7qi3uyQAABBlhGRggIZ70vXMjZWaOSZf3vYu/c//s0avbtpnd1kAACCKCMnAccjNTNNv51bovIlFau8M6Ib/eFfPr9ttd1kAACBKCMnAccpwpeg3V8/UJdPL1BUwWvDMOj25eofdZQEAgCggJAMnIC3FqQe/MV3XVI6RMdI9f9qon//tExlj7C4NAACcAEIycIKcTofu/cpULag6WZL0879t0b1/2qhAgKAMAEC8IiQDUeBwOLSgaoJ+8JWpkqQnaz7Trc+uU6c/YHNlAADgeBCSgSi65syT9NAV05XqdOj5dXt0w3+8q7YOv91lAQCAASIkA1F2yfQR+s3VM5We5tRrm/frm/9njRrbOu0uCwAADAAhGYiB8ycN13/OrZAnPVXvfnZIl/+6Rvu87XaXBQAA+omQDMTIzJMK9MxNlSrKcWtTbZO+tqxGOw+22l0WAADoB0IyEEOTSz36r5srNbogUzvrW3XZstX6eK/X7rIAAMAxEJKBGBszLEv/dXOlJpXkaH+TT5f/ukbv7qi3uywAANAHQjIwCIZ70vXMjZWaOSZf3vYu/c//s0avbtpnd1kAAOAoCMnAIMnNTNNv51bovIlFau8M6Ib/eFfPr9ttd1kAAOAICMnAIMpwpeg3V8/UJdPL1BUwWvDMOj362lY2HQEAYIghJAODLC3FqQe/MV3XVI6RMdLSlzdr1oNv6OUNe2UMW1kDADAUEJIBGzidDt37lala8tVTVJjt0vYDLbr5P9/T15bVaO1nXNQHAIDdHIbWVdR4vV7l5uaqsbFRHo/H7nIQJ5p9Xfr169v0m//+VO2dwWkXF00r0e0XTlJ5YZbN1QEAkFj6m9cIyVFESMaJqPO269//+omWr92lgJFSnQ79zy+M0S3/NF7Dst12lwcAQEIgJNuAkIxo2FTr1f0vbdJrm/dLknLcqbr5vHGae3a50tNSbK4OAID4Rki2ASEZ0fTm1gP6yYsfa+Oe4A59pbnpum3WRF36DyOU4nTYXB0AAPGJkGwDQjKiLRAwev6D3fq3v3yi3Q1tkoJbXX//S5N0zslFNlcHAED8ISTbgJCMWGnv9OuJ1Tv0y1e3qqm9S5J0zsmF+v6XJmtyKb81AAD6i5BsA0IyYu1QS4ceeWWrfvvWDnX6jRwO6bLTR+q2WRNUmpthd3kAAAx5hGQbEJIxWD472KKlf9msF9bvlSS5U52ae3a5bjp3nHIz02yuDgCAoYuQbANCMgbb+zsP6Scvfqx3dhySFAzL/3xqma6qGKXTR+fL4eACPwAAeiMk24CQDDsYY7Tyozr9+8pPtKm2yXp9UkmOrjxjtC49fYQ86XSXAQCQCMm2ICTDTsYYvbezQU+/vVMr1u+xdu9LT3Pqy6eW6aqK0Zo+Ko/uMgAgqRGSbUBIxlDR2NqpP77/uZ56e6c+qWu2Xp9c6tFVFaM1e3qZcuguAwCSECHZBoRkDDXGGK397JCeWrNTKz7cq46uYHc505Wir5wW7C6fOjLP3iIBABhEhGQbEJIxlDW0dugP7+3WU2s+07b9Ldbr00Z4dNUZY/SV6WXKdqfaWCEAALFHSLYBIRnxwBijd3Yc0lNrPtOLG2qt7nKWK0WX/MMIXXXGaE0bkWtzlQAAxAYh2QaEZMSbQy0d+sN7n+upNTv16YGe7vKpI3P1ldPKVD21RKMKMm2sEACA6CIk24CQjHhljNFbn9brqbd36uUNe9Xp7/lrYUqpR9VTS3ThtBJNKM5mdQwAQFwjJNuAkIxEcLDZpxXr9+ovG2u1Znu9/IGevyJOGpap6mklqp5aoukj8+R0EpgBAPGFkGwDQjISTX1Lh/72cZ3+urFWb2w5YM1flqRij1uzpgQ7zGeUFygtxWljpQAA9A8h2QaEZCSyZl+XXt+8Xy9vrNWrm/ap2ddlHcvNSFPV5GJVTy3WuROKlJ6WYmOlAAAcHSHZBoRkJAtfl1+rtx7UXzbWauVHdTrY0mEdy0hL0XkTi1Q9tUTnTxqu3Aw2LQEADB2EZBsQkpGM/AGjd3fU6+WNtfrrxjrtbmizjqWlOPSFscN0zsmFOmt8oSaXeJjHDACwFSHZBoRkJDtjjDbu8erlDbX6y8ZabdnXHHa8IMulynHDdNa4Qp01fphGF2SyWgYAYFARkm1ASAbCbd3XrNc279PqbQe15tODaunwhx0fmZ8RDMwnF+rMccNUmO22qVIAQLIgJNuAkAwcXac/oA92NejNrQf15tYDen/XobD1mCVpUkmOzhof7DKfUT6MbbIBAFFHSLYBIRnov9aOLr29vV5vbj2gN7ce1Ed7vWHHU50OTR+VpzPHF+rs8YWaPipPrlSWmQMAnBhCsg0IycDxO9jsU82nB61O88761rDjma4UzRiTr9NH5+v0MfmaPiqPlTMAAANGSLYBIRmInl31rcEu87aDWr31QNgyc5LkcEgnD88OhubR+Tp9TJ7GFmazegYAoE+EZBsQkoHYCASMNtc16d0d9XpvZ4Pe23lInx1sPWxcbkaapo/KszrOp43KVU463WYAQA9Csg0IycDgOdDs03ufHbJC8/rPG9TeGQgb43BIE4tz9A+j83X66GB4Li/MYtk5AEhihGQbEJIB+3T6A9q0t0nv7TyktZ8d0ns7D+nzQ22HjcvPTNM/jM7XqSNzNa0sV1NHeFTiSSc4A0CSICTbgJAMDC37mtr13mcNen/noe5uc6N8XYHDxg3LcmlKmUfTRuRqaplH08pyNbogk/nNAJCACMk2ICQDQ1tHV0Af7fXqvc8OacOeRn20x6st+5rlDxz+12C2O1VTyjxWaJ46wqPxRdlKTWEZOgCIZ4RkGxCSgfjT3unX5tombdjTqI17vNq4u1Ef1zap4wgdZ1eqU5NLcjSlLFfTRng0tSxXk0pylJ6WYkPlAIDjQUi2ASEZSAxd/oC27W/Rht3B4LxhT6M+3uNVk6/rsLEpTodOGpapCcU5Ork4RxOLczShOFsnFWYpja4zAAw5hGQbEJKBxBUIGO2sbw12m/c0akN31zly/eaQtBSHxhZm6+TibE0ozum+ZWvMsCylMNcZAGxDSLYBIRlILsYY7WvyaXNtkz6pa9KWumZtrmvSlromtXT4j/geV6pT44uyNaE4u1fnOUcj8zO4UBAABgEh2QaEZABSMDzvbmjTlrpmfVLX1B2cm7VlX9NhazmHZKSlaPzwbI0tytLYwmyVF2VpbGGWyguzlOVOHeQ/AQAkLkKyDQjJAPriDxh9fqhVn3SH5+CtWdv2NavDf+TwLEklnnSVF2ZpbFEwNI8rylZ5YZZG5mew2gYADBAh2QaEZADHo8sf0Gf1rdpS16RPD7Ro+/4WbT/Qok8PtKj+KHOepeC859EFmSovzNa47gA9tjtAF2a72CAFAI6AkGwDQjKAaGto7bCC86cHmoPhuTtEH2ljlJAcd6pGD8vU6ILuW/fjMQVZKstLpwMNIGkRkm1ASAYwWAIBo73edn26vyc4f3qgRZ/ub9buhjb19Td7itOhEXkZEeE5U6MKMjVmWKZy0tMG7w8CAIOMkGwDQjKAoaC9069d9a3aWd+qzw4G73vfjrRRSm/5mWkaPSyruwudoVH5mRqRn6EReRkqy8tg8xQAca2/eY1LpgEgwaSnpejk7s1NIgUCwWXrggG6RbvqW/VZKEAfbNXBlg4dau3UodYGfbCr4YifX5Tj1oi8DI3Iz9DI7vsRve7pRANIBHSSo4hOMoB41+zr0k6r+9yizw62andDm3YfatPuhja1HmX959486akakZ+pEXkZGhkRoMvyMjQsy8Wa0ABsQycZADBg2e5UTSnzaErZ4f/DYYxRQ2unPj/Upt0Nrd33PQF6d0ObGlo75W3vknevVx/v9R7xO9JSHCr2pKs0N12luRkqzU1XSW56932GynLTNSzbzc6EAGxFSAYA9IvD4VB+lkv5WS6dMjL3iGNafF1WcP68d4A+FOxI72vyqdNv9PmhNn1+qE3SoSN+TqozGKRLQgHak67SvPBAXZjtVhqrdACIEUIyACBqstypmtC91faRdPoD2t/k097GdtU2tmtvY1vY49rGdtU1+dQVMFZ3+mgcDmlYllvFHreG57hV7EnXcE+69bjYE7wfluViyTsAA0ZIBgAMmrQUp8q65yYfTZc/oAPNHVZo3ntYmG5XnbddXQGjA80+HWj2aWMf3+lwSIXZoTCd3uu+J1AX5rg0LMstVyphGkBQTEPySSedpM8++yzstSVLluiOO+6wnq9fv17z5s3TO++8o6KiIt1yyy26/fbbw96zfPly3XXXXdqxY4dOPvlk/fSnP9WXvvQl67gxRvfcc49+85vfqKGhQWeddZZ+9atf6eSTT7bG1NfX65ZbbtGf//xnOZ1OXXbZZXrooYeUnZ09oFoAALGVmuK0plkcTSBgVN/aoTpvu/Z5fdrX1K46r0913uD9/u7n+5t98geM9jf5tL/JJ+nI86RD8jPTVJjtVlGO27rv/bgw26WiHLeGZTFnGkh0Me8k//CHP9QNN9xgPc/J6fknOK/Xq1mzZqmqqkrLli3Thx9+qOuvv155eXm68cYbJUmrV6/WlVdeqSVLluif//mf9dRTT2n27Nl67733NG3aNEnS0qVL9fDDD+vJJ59UeXm57rrrLlVXV+ujjz5SenrwL9k5c+Zo7969WrlypTo7O3Xdddfpxhtv1FNPPdXvWgAAQ4PT6VBhdjC8Ti07+jh/wOhgi++wIL2vyad93p7nB1s65A+Y7uXvOrVlX3Of3x+c6uHqCdLZbhV23xdkuTQsO3hsWLZLBVkuuVNZWxqINzFdAu6kk07SggULtGDBgiMe/9WvfqV//dd/VW1trVwulyTpjjvu0HPPPadNmzZJki6//HK1tLRoxYoV1vu+8IUvaPr06Vq2bJmMMSorK9Ntt92m7373u5KkxsZGFRcX64knntAVV1yhjz/+WFOmTNE777yjmTNnSpJefvllfelLX9Lnn3+usrKyftUSyefzyefzWc+9Xq9GjRrFEnAAEGcCAaOGtk7tbwpO3+h9v78p2JEOvtahgy2+Pnc0PJIcd6qGZbs0LNutYd0heliW23qtMMulgu7X8jPTmEMNxNCQWQLu/vvv149+9CONHj1aV111lW699Valpga/tqamRueee64VSiWpurpaP/3pT3Xo0CHl5+erpqZGCxcuDPvM6upqPffcc5Kk7du3q7a2VlVVVdbx3NxcVVRUqKamRldccYVqamqUl5dnBWRJqqqqktPp1Jo1a3TppZf2q5ZIS5Ys0Q9+8IOonCcAgH2cTocKsoJd34k68kWHIf6AUX1LhxWeD0Tc17d06GB3mD7Y3KGugFGTr0tNvi7tONh6zFocDik/M1hLQaZL+VlpKshyWa9Z972OZ7tT5XAw/QOIppiG5H/5l3/R6aefroKCAq1evVqLFy/W3r179e///u+SpNraWpWXl4e9p7i42DqWn5+v2tpa67XeY2pra61xvd93tDHDhw8PO56amqqCgoKwMceqJdLixYvDAnyokwwASFwpToc1V/lYjDHytnUFA3NLhw42B7vR9aHH3fcHu1+rb+2QMQo+bunod02uFKfys9KOEKBdKshMU36WS7kZweP5mS7lZqbJk06wBvoy4JB8xx136Kc//WmfYz7++GNNmjQpLECeeuqpcrlcuummm7RkyRK53cf+y2Woc7vdCfHnAADEhsPhUG5mmnIz0zS26Njjg/OiO6zQfKi1+76lo3vL8J7XD7V0qr6lQ22dfnX4A93zq33H/pJuKU6H8jKCtQXDc5ryMl3KywiG6rzMNOVl9Hq9e1x6mpNwjaQw4JB822236dprr+1zzNixY4/4ekVFhbq6urRjxw5NnDhRJSUlqqurCxsTel5SUmLdH2lM7+Oh10pLS8PGTJ8+3Rqzb9++sM/o6upSfX39Mb+n93cAABBLKb0uSOyvtg6/FZ4jg3V99+OG7gsSG1qDj9s6/d0XNQbDt9TS7+9zpTqVm5Gm3Iy0YMjuDtphr3UHbE9GmvJ6HWPzF8STAYfkoqIiFRX14/8OH8G6devkdDqtqQ+VlZX613/9V3V2diotLU2StHLlSk2cONGa3lBZWalVq1aFXfy3cuVKVVZWSpLKy8tVUlKiVatWWaHY6/VqzZo1+ta3vmV9RkNDg9auXasZM2ZIkl555RUFAgFVVFT0uxYAAIaaDFeKMlx9rz0dqb3Tr4bWTjW0BTvSDa0damjr1KHuEN3Q2hEWqkOPuwJGHV2BXkvqDUyWK6U7VLuUm5EqT3qaPN0BOvg4tdfj7te7x2W6UuhgY1DFbHWLmpoarVmzRueff75ycnJUU1OjW2+9VRdddJGefPJJScFVKCZOnKhZs2Zp0aJF2rBhg66//no9+OCDYUvAffGLX9T999+viy++WL///e/1k5/8JGwJuJ/+9Ke6//77w5aAW79+fdgScBdddJHq6uq0bNkyawm4mTNnWkvA9aeWY+nv1ZIAAMQbY4yafV1qbOsM3lo7rccNofvWTnmt1zqs15rau074+1OdDnkygnOpI4O1Jz1NOempyul17+n13JOepuz0VNa2hqT+57WYheT33ntP3/72t7Vp0yb5fD6Vl5frm9/8phYuXBg2j7f3Bh6FhYW65ZZbtGjRorDPWr58ue68805rM5GlS5cecTORxx57TA0NDTr77LP16KOPasKECdaY+vp6zZ8/P2wzkYcffviom4kcrZa+EJIBADicP2DU1B4MzL1DtbetU972TnnbguE7+LhT3vau4H33uK5AdKJKlitFnoxjBepUZaenKtsdfJ7tTrXGZbtT2ZUxAdgekpMRIRkAgOgyxqit0y9vW5cVohsjw3VbsFvd5Avee9u71NQdtpvaO+XrCkStHleqMxik3cEwneNO674PhunIgJ3tTlVW97Esd6qy3CnKcadxAaSNhsw6yQAAAMfL4XAo05WqTFdqn1uV96WjK6Cm9p7Q3NR9HwrewefBx83tXWruXte6qdfz1g6/9VkHmjt0oLn/S/QdSYrToSxXihW2s9w9ofrwYJ2qbHeKslzhzzNDz10pbEATA4RkAACQ0FypzuBuhwNYNSRSlz+gFp9fTb5ONfu61NwdrJu6Hzf7esJ2c3fADo7vUkv3mBZfl5o7umRMcAqKt7vrrcYT/zO6U51WuM7sDt+hznVPuE7pDtXBMaGx1r0rVZnd4zPSUuRM8jnchGQAAIBjSE1xKjfTqdzMtBP6nEAgOH2kpbtb3WKF7ODt8Nf9avZ1qrXDbx1v8fnV0hF83OkPzpr1dQXk6wot6Rcdma5Qt7r73pWizO7OdWZ30M50pygzLTgmw5VivSf8vudxPIVvQjIAAMAgcTod1pSJ4ccefky+Lr9afd0BuqM7QIdCdvc0kVC4Dj1u7Qg+bu0O260dfut4S3enW1JwTIdfB5qjUGgvGWkpYQE7w5Wi8sIsPXj59Oh+0QkiJAMAAMQpd2qK3Kkpys9yReXzjDFq7wwEw7MVooPhu/d9s8+vtlDA7uh5HLz1fhx83tbpt8J3W6dfbZ1+Hey1h01b95zvoYSQDAAAAEnBCyWDG9SkSNnHHt9fvcN3W3d47v14KC6tR0gGAABATIWF7zgx9GI7AAAAYDNCMgAAABCBkAwAAABEICQDAAAAEQjJAAAAQARCMgAAABCBkAwAAABEICQDAAAAEQjJAAAAQARCMgAAABCBkAwAAABEICQDAAAAEQjJAAAAQARCMgAAABCBkAwAAABEICQDAAAAEQjJAAAAQARCMgAAABCBkAwAAABEICQDAAAAEQjJAAAAQARCMgAAABCBkAwAAABEICQDAAAAEVLtLiCRGGMkSV6v1+ZKAAAAcCShnBbKbUdDSI6ipqYmSdKoUaNsrgQAAAB9aWpqUm5u7lGPO8yxYjT6LRAIaM+ePcrJyZHD4Yj593m9Xo0aNUq7du2Sx+OJ+fchiPNuD867PTjv9uC824Pzbo/BPu/GGDU1NamsrExO59FnHtNJjiKn06mRI0cO+vd6PB7+Y7YB590enHd7cN7twXm3B+fdHoN53vvqIIdw4R4AAAAQgZAMAAAARCAkxzG326177rlHbrfb7lKSCufdHpx3e3De7cF5twfn3R5D9bxz4R4AAAAQgU4yAAAAEIGQDAAAAEQgJAMAAAARCMkAAABABEIyAAAAEIGQHMd++ctf6qSTTlJ6eroqKir09ttv211SQrv33nvlcDjCbpMmTbK7rITzxhtv6Mtf/rLKysrkcDj03HPPhR03xujuu+9WaWmpMjIyVFVVpS1btthTbAI51nm/9tprD/v9X3jhhfYUmyCWLFmif/zHf1ROTo6GDx+u2bNna/PmzWFj2tvbNW/ePA0bNkzZ2dm67LLLVFdXZ1PFiaE/5/2888477Pd+880321RxYvjVr36lU0891dpVr7KyUi+99JJ1fCj+1gnJceqZZ57RwoULdc899+i9997Taaedpurqau3bt8/u0hLa1KlTtXfvXuv297//3e6SEk5LS4tOO+00/fKXvzzi8aVLl+rhhx/WsmXLtGbNGmVlZam6ulrt7e2DXGliOdZ5l6QLL7ww7Pf/9NNPD2KFief111/XvHnz9NZbb2nlypXq7OzUrFmz1NLSYo259dZb9ec//1nLly/X66+/rj179uirX/2qjVXHv/6cd0m64YYbwn7vS5cutanixDBy5Ejdf//9Wrt2rd5991390z/9ky655BJt3LhR0hD9rRvEpTPOOMPMmzfPeu73+01ZWZlZsmSJjVUltnvuucecdtppdpeRVCSZP/7xj9bzQCBgSkpKzAMPPGC91tDQYNxut3n66adtqDAxRZ53Y4y55pprzCWXXGJLPcli3759RpJ5/fXXjTHB33ZaWppZvny5Nebjjz82kkxNTY1dZSacyPNujDFf/OIXzXe+8x37ikoS+fn55n//7/89ZH/rdJLjUEdHh9auXauqqirrNafTqaqqKtXU1NhYWeLbsmWLysrKNHbsWM2ZM0c7d+60u6Sksn37dtXW1ob99nNzc1VRUcFvfxC89tprGj58uCZOnKhvfetbOnjwoN0lJZTGxkZJUkFBgSRp7dq16uzsDPu9T5o0SaNHj+b3HkWR5z3kd7/7nQoLCzVt2jQtXrxYra2tdpSXkPx+v37/+9+rpaVFlZWVQ/a3nmrbN+O4HThwQH6/X8XFxWGvFxcXa9OmTTZVlfgqKir0xBNPaOLEidq7d69+8IMf6JxzztGGDRuUk5Njd3lJoba2VpKO+NsPHUNsXHjhhfrqV7+q8vJybdu2Td///vd10UUXqaamRikpKXaXF/cCgYAWLFigs846S9OmTZMU/L27XC7l5eWFjeX3Hj1HOu+SdNVVV2nMmDEqKyvT+vXrtWjRIm3evFn/7//9PxurjX8ffvihKisr1d7eruzsbP3xj3/UlClTtG7duiH5WyckA/100UUXWY9PPfVUVVRUaMyYMXr22Wc1d+5cGysDYu+KK66wHp9yyik69dRTNW7cOL322mu64IILbKwsMcybN08bNmzgOodBdrTzfuONN1qPTznlFJWWluqCCy7Qtm3bNG7cuMEuM2FMnDhR69atU2Njo/7rv/5L11xzjV5//XW7yzoqplvEocLCQqWkpBx21WddXZ1KSkpsqir55OXlacKECdq6davdpSSN0O+b3779xo4dq8LCQn7/UTB//nytWLFCr776qkaOHGm9XlJSoo6ODjU0NISN5/ceHUc770dSUVEhSfzeT5DL5dL48eM1Y8YMLVmyRKeddpoeeuihIftbJyTHIZfLpRkzZmjVqlXWa4FAQKtWrVJlZaWNlSWX5uZmbdu2TaWlpXaXkjTKy8tVUlIS9tv3er1as2YNv/1B9vnnn+vgwYP8/k+AMUbz58/XH//4R73yyisqLy8POz5jxgylpaWF/d43b96snTt38ns/Acc670eybt06SeL3HmWBQEA+n2/I/taZbhGnFi5cqGuuuUYzZ87UGWecoZ///OdqaWnRddddZ3dpCeu73/2uvvzlL2vMmDHas2eP7rnnHqWkpOjKK6+0u7SE0tzcHNat2b59u9atW6eCggKNHj1aCxYs0H333aeTTz5Z5eXluuuuu1RWVqbZs2fbV3QC6Ou8FxQU6Ac/+IEuu+wylZSUaNu2bbr99ts1fvx4VVdX21h1fJs3b56eeuopPf/888rJybHmXubm5iojI0O5ubmaO3euFi5cqIKCAnk8Ht1yyy2qrKzUF77wBZurj1/HOu/btm3TU089pS996UsaNmyY1q9fr1tvvVXnnnuuTj31VJurj1+LFy/WRRddpNGjR6upqUlPPfWUXnvtNf3lL38Zur9129bVwAl75JFHzOjRo43L5TJnnHGGeeutt+wuKaFdfvnlprS01LhcLjNixAhz+eWXm61bt9pdVsJ59dVXjaTDbtdcc40xJrgM3F133WWKi4uN2+02F1xwgdm8ebO9RSeAvs57a2urmTVrlikqKjJpaWlmzJgx5oYbbjC1tbV2lx3XjnS+JZnHH3/cGtPW1ma+/e1vm/z8fJOZmWkuvfRSs3fvXvuKTgDHOu87d+405557rikoKDBut9uMHz/efO973zONjY32Fh7nrr/+ejNmzBjjcrlMUVGRueCCC8xf//pX6/hQ/K07jDFmMEM5AAAAMNQxJxkAAACIQEgGAAAAIhCSAQAAgAiEZAAAACACIRkAAACIQEgGAAAAIhCSAQAAgAiEZAAAACACIRkAAACIQEgGAAAAIhCSAQAAgAj/HwD0Becc3Q9JAAAAAElFTkSuQmCC\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from torchvision.utils import make_grid\n", - "\n", - "def show_x(x):\n", - " x = rearrange(x, \"... (c h w) -> ... c h w\", c=1, h=28, w=28)\n", - " return data_config.show(torch.tensor(np.array(x)))\n", - "\n", - "aa = make_grid([rearrange(torch.tensor(show_x(x[0][0])), \"h w c -> c h w\") for x in allxs])\n", - "\n", - "plt.imshow(np.array(rearrange(aa, \"c h w -> h w c\")))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ff85a640-4be3-46d2-8f49-6308f476d6ed", - "metadata": {}, - "outputs": [], - "source": [ - "def fwd_energy(model, clamp_label:int, depth=4, dt=0.4, rng=None):\n", - " \"\"\"A pure function to extract desired information from the configured HAM, applied on batched inputs\"\"\"\n", - " # Initialize hidden states to our image\n", - " xs = model.init_states(1, rng=rng)\n", - " # xs[0] = jnp.array(rearrange(x, \"... c h w -> ... (c h w)\"))\n", - " \n", - " # Masks allow us to clamp our label data over time\n", - " masks = jtu.tree_map(lambda x: jnp.ones_like(x, dtype=jnp.int8), xs)\n", - "\n", - " xs[-1] = jnp.zeros_like(xs[-1]).at[...,clamp_label].set(1050.)\n", - " # xs[-1] = xs[-1].at[...,1].set(1000.)\n", - " print(xs[-1])\n", - " masks[-1] = jnp.zeros_like(masks[-1])\n", - "\n", - " # masks[0] = jnp.zeros_like(masks[0], dtype=jnp.int8) # Don't evolve images\n", - " all_xs = [xs]\n", - " energies = [model.venergy(xs)]\n", - "\n", - " for i in range(depth):\n", - " updates = model.vupdates(xs) # Calculate the updates\n", - " xs = model.step(\n", - " xs, updates, dt=dt, masks=masks\n", - " ) # Add them to our current states\n", - " all_xs.append(xs)\n", - " energies.append(model.venergy(xs))\n", - "\n", - " # All labels have a softmax activation function as the last layer, spitting out probabilities\n", - " return jnp.stack(energies), all_xs" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c06b24d3-02bc-49ee-9b8b-17332fa24ee6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Starting 0\n", - "Tracedwith\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:matplotlib.image:Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from torchvision.utils import make_grid\n", - "img_start = batch[0][:1]\n", - "\n", - "def show_x(x):\n", - " x = rearrange(x, \"... (c h w) -> ... c h w\", c=1, h=28, w=28)\n", - " return data_config.show(torch.tensor(np.array(x)))\n", - "\n", - "# aa = make_grid([rearrange(torch.tensor(show_x(x[0][0])), \"h w c -> c h w\") for x in allxs])\n", - "\n", - "quick_fwd = jax.jit(fwd_energy, static_argnames=(\"depth\"))\n", - "\n", - "# plt.imshow(np.array(rearrange(aa, \"c h w -> h w c\")))\n", - "for i in range(10):\n", - " print(f\"Starting {i}\")\n", - " energies, allxs = quick_fwd(loaded_model, clamp_label=i, dt=1e-6, depth=50)\n", - " aa = make_grid([rearrange(torch.tensor(show_x(x[0][0])), \"h w c -> c h w\") for x in allxs])\n", - " plt.imshow(np.array(rearrange(aa, \"c h w -> h w c\")))\n", - " plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "85ea4247-b2d2-4501-8e68-d429712a5fa5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "DeviceArray([0.48687777, 0.48687777, 0.00328056, 0.00328056, 0.00328056,\n", - " 0.00328056, 0.00328056, 0.00328056, 0.00328056, 0.00328056], dtype=float32)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "linit = jnp.zeros((10,)).at[1].set(1000.).at[0].set(1000.)\n", - "loaded_model.layers[-1].g(linit)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "03aa92d5-f3bd-43a4-81fd-f0d490d50ec2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from torchvision.utils import make_grid\n", - "\n", - "def show_x(x):\n", - " x = rearrange(x, \"... (c h w) -> ... c h w\", c=1, h=28, w=28)\n", - " return data_config.show(torch.tensor(np.array(x)))\n", - "\n", - "aa = make_grid([rearrange(torch.tensor(show_x(x[0][0])), \"h w c -> c h w\") for x in allxs])\n", - "\n", - "plt.imshow(np.array(rearrange(aa, \"c h w -> h w c\")))" - ] - }, - { - "cell_type": "markdown", - "id": "fe790065-05f8-4974-9f3a-762033760904", - "metadata": {}, - "source": [ - "# Archive" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ccb261ca-89e9-43d1-86a6-93b54dfc34a0", - "metadata": {}, - "outputs": [], - "source": [ - "# tvision_tfm = tfms.Compose(\n", - "# [\n", - "# tfms.ToTensor(),\n", - "# tfms.RandomAffine(degrees = 10, translate = (0.2, 0.2)),\n", - "# ]\n", - "# )\n", - "# def transforms(examples):\n", - "# examples[\"pixels\"] = torch.cat([tvision_tfm(image.convert(\"RGB\")) for image in examples[\"image\"]]).detach().cpu().numpy()[None]\n", - "# return examples\n", - "# ds_train.set_transform(transforms)\n", - "\n", - "\n", - "# import datasets\n", - "# import torchvision.transforms as tfms\n", - "# import torch\n", - "# x_train_fname = \"data/MNIST/mnist_train.trch\"\n", - "# x_val_fname = \"data/MNIST/mnist_val.trch\"\n", - "\n", - "# ds_train = datasets.load_dataset(\"mnist\", split=\"train\")\n", - "# ds_val = datasets.load_dataset(\"mnist\", split=\"test\")\n", - "\n", - "# def map_transforms(examples):\n", - "# examples[\"pixels\"] = [tfms.ToTensor()(image) for image in examples[\"image\"]]\n", - "# return examples\n", - "\n", - "# def save_matrix_mnist(ds, fname):\n", - "# ds = ds.map(map_transforms, remove_columns=[\"image\"], batched=True)\n", - "# X = torch.tensor(ds['pixels'])\n", - "# torch.save(X, fname)\n", - "# return X\n", - "\n", - "# def load_mnist():\n", - "# X_train = torch.load(x_train_fname)\n", - "# X_val = torch.load(x_val_fname)\n", - " \n", - "# return X_train.squeeze(1), X_val.squeeze(1)\n", - "\n", - "# X_train = save_matrix_mnist(ds_train, x_train_fname)\n", - "# X_val = save_matrix_mnist(ds_val, x_val_fname)\n", - "\n", - "# X_train, X_val = load_mnist()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:hamux]", - "language": "python", - "name": "conda-env-hamux-py" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/classification.py b/examples/classification.py deleted file mode 100644 index f9e3fa0..0000000 --- a/examples/classification.py +++ /dev/null @@ -1,343 +0,0 @@ -"""Training script for classification on MNIST - -We recreate the famous 2-layer Hopfield Network in our framework and compute best performance on MNIST classification. - -To speed up training, MNIST data is loaded with select (and simplified) augmentation strategies from the popular timm library. - -``` -python classification.py vectorized_chn_cifar ./_log_chn_cifar --device 1 --dataset cifar10 -python classification.py vectorized_chn_mnist ./_log_tchn_mnist --device 1 --dataset mnist -``` -""" - -## SETUP -import argparse - -parser = argparse.ArgumentParser() -parser.add_argument( - "model", type=str, help="Which model to load from default model registry" -) -parser.add_argument( - "--outdir", - type=str, - default=None, - help="Where to saved checkpoints and model information. If not provided use the current working directory", -) -parser.add_argument( - "--dataset", type=str, default="MNIST", help="One of [MNIST, CIFAR10]." -) -parser.add_argument( - "--device", type=int, default=0, help="GPU device on which to conduct the training" -) -parser.add_argument( - "--num_epochs", - type=int, - default=1000, - help="The number of epochs on which to run the training", -) -parser.add_argument("--batch_size", type=int, default=400, help="Batch Size") -parser.add_argument("--lr", type=float, default=0.001, help="Default learning rate") -parser.add_argument( - "--seed", - type=int, - default=34, - help="Seed the randomness of training and model initialization", -) -parser.add_argument( - "--filter_betas", - action="store_true", - help="Do not train betas in the softmax layers of the model", -) -parser.add_argument( - "--pct_dev_memory", - type=float, - default=None, - help="How much available memory to preallocate to jax on provided device", -) -parser.add_argument( - "--normal_init", - action="store_true", - help="If true, initialize all layer states as normal distributions rather than all 0s", -) -args = parser.parse_args() - -assert args.dataset.lower() in set(["mnist", "cifar10"]) -import os - -os.environ["CUDA_VISIBLE_DEVICES"] = str(args.device) -os.environ[ - "XLA_FLAGS" -] = "--xla_gpu_force_compilation_parallelism=1" # This is necessary for our environment's JAX installation -if args.pct_dev_memory is not None: - assert args.pct_dev_memory <= 1 and args.pct_dev_memory > 0.0 - os.environ["XLA_PYTHON_CLIENT_MEM_FRACTION"] = str(args.pct_dev_memory) - -from loguru import logger -from pathlib import Path -import jax -import jax.numpy as jnp -import numpy as np -import torch -import hamux as hmx -import treex as tx -from flax import linen as nn # For initializers -import optax -import jax.tree_util as jtu -from typing import * -from hamux.datasets import * -from tqdm import trange, tqdm -from dataclasses import dataclass -from hamux.utils import pytree_save, pytree_load, to_pickleable -import json -import sys - - -jax_key = jax.random.PRNGKey(args.seed) -torch.manual_seed(args.seed + 1) -np.random.seed(args.seed + 2) - -logdir = Path().absolute() if args.outdir is None else Path(args.outdir) -logdir.mkdir(parents=True, exist_ok=True) -logger.add(str(logdir / "stdlogs.log"), colorize=False) -logger.add(sys.stdout) - -# =========================================== -## Training code -# =========================================== - - -class TrainState(tx.Module): - model: tx.Module - optimizer: tx.Optimizer - apply_fn: Callable - filter_betas: bool - rng: jnp.ndarray = tx.Rng.node() - eval_rng: jnp.ndarray = tx.Rng.node() - - def __init__( - self, model, optimizer, apply_fn, rng, filter_betas=False, do_normal_init=False - ): - self.filter_betas = filter_betas - self.model = model - self.optimizer = tx.Optimizer(optimizer).init(self.params) - self.apply_fn = apply_fn - self.rng, self.eval_rng = jax.random.split(rng) - self.do_normal_init = do_normal_init - - @property - def params(self): - if self.filter_betas: - return self.model.filter(lambda x: "beta" not in x.name) - return self.model.filter(tx.Parameter) - - def apply_updates(self, grads): - new_params = self.optimizer.update(grads, self.params) - self.model = self.model.merge(new_params) - return self - - -def cross_entropy_loss(*, probs, labels): - n_classes = probs.shape[-1] - labels_onehot = jax.nn.one_hot(labels, num_classes=n_classes) - smoothed_labels = (0.1 / n_classes + labels_onehot) - smoothed_labels = smoothed_labels / jnp.abs(smoothed_labels).sum(-1, keepdims=True) - - stable_probs = (probs + 1e-6) / (1+(1e-6)*n_classes) - loss = -jnp.sum(smoothed_labels * jnp.log(stable_probs), axis=-1).mean() - return loss - - -def compute_metrics(*, probs, labels): - loss = cross_entropy_loss(probs=probs, labels=labels) - accuracy = jnp.mean(jnp.argmax(probs, -1) == labels) - metrics = { - "probs_min": probs.min(), - 'probs_max': probs.max(), - 'loss': loss, - 'accuracy': accuracy, - } - return metrics - - -@jax.jit -def train_step(state, batch): - if state.do_normal_init: - rng, state.rng = jax.random.split(state.rng) - else: - rng = None - - def loss_fn(params): - state.model = state.model.merge(params) - x = batch["image"] - probs = state.apply_fn(state.model, x, rng=rng) - loss = cross_entropy_loss(probs=probs, labels=batch["label"]) - return loss, (probs, state) - - grad_fn = jax.value_and_grad(loss_fn, has_aux=True) - (_, (probs, state)), grads = grad_fn(state.params) - - state = state.apply_updates(grads) - metrics = compute_metrics(probs=probs, labels=batch["label"]) - return state, metrics - -@jax.jit -def eval_step(state, batch): - x = batch["image"] - if state.do_normal_init: - rng = state.eval_rng - else: - rng = None - probs = state.apply_fn(state.model, x, rng=rng) - return compute_metrics(probs=probs, labels=batch['label']) - -def train_epoch(state, train_dl, epoch): - """Train for a single epoch.""" - batch_metrics = [] - bs = train_dl.batch_size - for i, batch in enumerate(tqdm(train_dl, leave=False)): - batch = {"image": jnp.array(batch[0]), "label": jnp.array(batch[1])} - state, metrics = train_step(state, batch) - batch_metrics.append(metrics) - - # compute mean of metrics across each batch in epoch. - batch_metrics_np = jax.device_get(batch_metrics) - epoch_metrics_np = { - k: np.mean([metrics[k] for metrics in batch_metrics_np]) - for k in batch_metrics_np[0] - } - return state, epoch_metrics_np["loss"], epoch_metrics_np["accuracy"] - - -def eval_model(state, test_dl): - batch_metrics = [] - - for i, batch in enumerate(test_dl): - batch = {"image": jnp.array(batch[0]), "label": jnp.array(batch[1])} - - metrics = eval_step(state, batch) - batch_metrics.append(metrics) - batch_metrics_np = jax.device_get(batch_metrics) - summary = { - k: np.mean([metrics[k] for metrics in batch_metrics_np]) - for k in batch_metrics_np[0] - } - - return summary["loss"], summary["accuracy"] - - -# =========================================== -## Dataloaders -# =========================================== -if args.dataset.lower() == "mnist": - dl_args = DataloadingArgs( - dataset="torch/MNIST", - aa=None, - reprob=0.1, - vflip=0.0, - hflip=0.0, - scale=(0.9, 1.0), - batch_size=args.batch_size, - color_jitter=0.4, - validation_batch_size=2 * args.batch_size, - ) - data_config = DataConfigMNIST(input_size=(1, 28, 28)) -elif args.dataset.lower() == "cifar10": - dl_args = DataloadingArgs( - dataset="torch/CIFAR10", - # aa="rand", - aa=None, - reprob=0.2, - vflip=0.0, - hflip=0.5, - scale=(0.2, 1.0), - batch_size=args.batch_size, - color_jitter=0.5, - validation_batch_size=2 * args.batch_size, - ) - data_config = DataConfigCIFAR10(input_size=(3, 32, 32)) - -train_dl, eval_dl = create_dataloaders(dl_args, data_config) - -# =========================================== -## Model Configuration -# =========================================== -k1, jax_key = jax.random.split(jax_key) -ham, forward_classification = hmx.create_model(args.model) -states, ham = ham.init_states_and_params(k1, bs=1) - -optimizer = optax.adamw(args.lr) -state = TrainState( - ham, - optimizer, - forward_classification, - rng=jax_key, - filter_betas=args.filter_betas, - do_normal_init=args.normal_init, -) - - -def get_nparams(model): - params, meta = jtu.tree_flatten(model.parameters()) - - def get_nel(x): - try: - return x.size - except AttributeError: # float - return 1 - - return sum([get_nel(p) for p in params]) - - -def escape_ansi(line): - import re - - ansi_escape = re.compile(r"(?:\x1B[@-_]|[\x80-\x9F])[0-?]*[ -/]*[@-~]") - return ansi_escape.sub("", line) - - -logger.info(f"NParams={get_nparams(state.model)}") -logger.info(escape_ansi(state.model.tabulate())) - -# =========================================== -## Training -# =========================================== -@dataclass -class CkptTracker: - base_name: str - model: tx.Module = None - epoch: int = -1 - best_acc: float = -1 - - def get_save_name(self): - return f"{self.base_name}_epoch-{self.epoch}_acc-{100*self.best_acc:.3f}.pckl" - - -train_acc_list = [] -test_acc_list = [] -ckpt_tracker = CkptTracker(args.model) - - -with trange(1, args.num_epochs + 1, unit="epochs") as pbar: - for epoch in pbar: - state, train_loss, train_acc = train_epoch(state, train_dl, epoch) - test_loss, test_acc = eval_model(state, eval_dl) - if test_acc > ckpt_tracker.best_acc: - old_ckpt_name = str(logdir / ckpt_tracker.get_save_name()) - try: - os.remove(old_ckpt_name) - except Exception as e: - logger.debug(f"Couldn't remove {old_ckpt_name}, {e}") - pass - ckpt_tracker.model = state.model - ckpt_tracker.epoch = epoch - ckpt_tracker.best_acc = test_acc - to_save = jtu.tree_map(to_pickleable, ckpt_tracker.model.to_dict()) - ckpt_name = str(logdir / ckpt_tracker.get_save_name()) - pytree_save(to_save, ckpt_name, overwrite=True) - desc = f"[{epoch}/{args.num_epochs}] | BestAcc: {100*ckpt_tracker.best_acc:.3f} | TrainLoss: {train_loss:.2f} | TrainAcc: {100*train_acc:.2f}" - addition = f"curr_val_acc={100*test_acc:0.2f}" - logger.info(desc + " | " + addition) - pbar.set_description(desc) - pbar.set_postfix( - train_acc=f"{100*train_acc:0.2f}", val_acc=f"{100*test_acc:0.2f}" - ) \ No newline at end of file diff --git a/examples/launch_classification.py b/examples/launch_classification.py deleted file mode 100644 index e54c2d1..0000000 --- a/examples/launch_classification.py +++ /dev/null @@ -1,63 +0,0 @@ -from pathlib import Path -import subprocess -import multiprocessing as mp -from fastcore.script import * -from typing import * - - -gpus = [1,2,3,4,5,6] - -pct_mem_per_gpu = 0.6 -test_only = True -max_epochs = 600 -logdir = Path().absolute() / "_dummylogs" / "log01" -do_normal_init = False -logdir.mkdir(parents=True, exist_ok=True) - -mnames_flags = [ - ("hn_relu_mnist", "--dataset mnist"), - ("hn_repu5_mnist", "--dataset mnist"), - ("hn_softmax_mnist", "--dataset mnist"), - - ("conv_ham_avgpool_mnist", "--dataset mnist"), - ("conv_ham_maxpool_mnist", "--dataset mnist"), - ("energy_attn_mnist", "--dataset mnist"), - - ("hn_relu_cifar", "--dataset cifar10"), - ("hn_repu5_cifar", "--dataset cifar10"), - ("hn_softmax_cifar", "--dataset cifar10"), - ("conv_ham_avgpool_cifar", "--dataset cifar10"), - ("conv_ham_maxpool_cifar", "--dataset cifar10"), - ("energy_attn_cifar", "--dataset cifar10"), -] - -assert len(mnames_flags) >= len(gpus) - -grouped_runs = [[] for _ in gpus] -for i, info in enumerate(mnames_flags): - gpui = i % len(gpus) - gpu = gpus[gpui] - grouped_runs[gpui].append(info + (gpu,)) - -def submit_run(mname, flags, device): - outdir = logdir / mname - # outdir.mkdir(parents=True, exist_ok=False) - cmd = f"python classification.py {mname} {flags} --outdir {outdir} --device {device}" - if test_only: - cmd += " --num_epochs=2" - else: - cmd += f" --num_epochs={max_epochs}" - - if do_normal_init: - cmd += " --normal_init" - print(cmd) - subprocess.run(cmd, shell=True) - -def submit_runs(runs): - """Where `runs` is a list of (mname, flags). Submit all commands to run sequentially on specified device""" - for mname, flags, device in runs: - submit_run(mname, flags, device) - - -with mp.Pool(len(gpus)) as p: - p.map(submit_runs, grouped_runs) diff --git a/hamux/CONTRIBUTING.md b/hamux/CONTRIBUTING.md deleted file mode 100644 index af666d6..0000000 --- a/hamux/CONTRIBUTING.md +++ /dev/null @@ -1,46 +0,0 @@ -# How to contribute - -## Getting Started - -HAMUX uses the [`nbdev`](https://github.com/fastai/nbdev) to build software. It comes with the following advantages: - -- All major code is written, documented, and tested entirely within Jupyter Notebooks. This makes it easy to ensure these interdependent components of a library are in sync -- `nbdev` comes with nice out-of-the-box support for distributing software, e.g., publishing to `pip`/`conda` and serving your documentation site on github pages. - - -However, it also increases the overhead for potential contributors. After cloning and setting up the environment according to the README, do the following: - -1. install the git hooks that run notebook cleaning and tests on every commit: - ``` - nbdev_install_hooks - ``` -2. If your edits touch any `*.ipynb` file (and they should, since that's where the logic, documentation, and tests live), run the following command before making your commit: - ``` - nbdev_prepare - ``` -3. After pushing, check that all tests pass on your fork of the github before submitting a PR. - - -## Did you find a bug? - -Submit an issue! We can solve it together and improve documentation+tests at the same time. Please include a description on how you expected the code to behave and error messages, if relevant. - - -#### Did you write a patch that fixes a bug? - -* Open a new GitHub pull request with the patch. -* Ensure that your PR includes a test that fails without your patch, and pass with it. - -## On Style - -HAMUX is a rapidly evolving library -- there is no other deep learning library that operates like it. As such, the API is highly subject to change and a consistent coding style is not particularly important. - -That said, we do follow `nbdev` [best practices](https://www.youtube.com/watch?v=67FdzLSt4aA). For us coders, it requires shifting our thinking from building insular, minimally documented python modules to thinking in terms of [Literate Programming](https://www-cs-faculty.stanford.edu/~knuth/lp.html) where the functional code is interspersed with explanation and tests for expected behavior. - -Submit a PR and we can work out the functional style together. - -## Roadmap - -- JAX + Treex is a powerful and intuitive combo... for me; it is not a combination that many DL researchers use. Thus we need to port HAMUX to, at the minimum, [`pytorch`](https://pytorch.org/) and [`flax`](https://github.com/google/flax). These are long term goals, and help on them would be appreciated. -- HAMUX right now is a very powerful theoretical abstraction for memory. We demonstrate equivalent performance to the single layer HN. However, we don't have the architecture+training paradigm to prove that its hierarchical form is substantially better. We need to build better architectures that solve real tasks. - diff --git a/hamux/__init__.py b/hamux/__init__.py index 6b451e0..cbff6cc 100644 --- a/hamux/__init__.py +++ b/hamux/__init__.py @@ -1,6 +1,4 @@ -__version__ = "0.1.1" -from .ham import * -from .synapses import * -from .layers import * -import hamux.lagrangians as lagrangians -from .registry import create_model, register_model \ No newline at end of file +__version__ = "0.2.1" + +from .core import * +from .lagrangians import * \ No newline at end of file diff --git a/hamux/core.py b/hamux/core.py index 6552cc5..91c5d8a 100644 --- a/hamux/core.py +++ b/hamux/core.py @@ -1,7 +1,285 @@ -# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/00_core.ipynb. +"""The building blocks of energy-based Associative Memory""" + +# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/00_core.qmd. # %% auto 0 -__all__ = ['foo'] +__all__ = ['NeuronLayer', 'legendre_transform', 'LinearSynapse', 'LinearSynapseWithBias', 'BiasSynapse', 'ConvSynapse', 'HAM', + 'VectorizedHAM'] + +# %% ../nbs/00_core.qmd 2 +from typing import * +import equinox as eqx +import jax, jax.numpy as jnp, jax.random as jr, jax.tree_util as jtu +from fastcore.basics import * +import functools as ft + +# %% ../nbs/00_core.qmd 5 +class NeuronLayer(eqx.Module): + """Neuron layers represent dynamic variables that evolve during inference (i.e., memory retrieval/error correction)""" + lagrangian: Callable # The scalar-valued Lagrangian function: x |-> R + shape: Tuple[int] # The shape of the neuron layer + +# %% ../nbs/00_core.qmd 7 +@patch +def activations(self: NeuronLayer, x): + """Use autograd to compute the activations of the neuron layer from the Lagrangian""" + return jax.grad(self.lagrangian)(x) + +# %% ../nbs/00_core.qmd 12 +@patch +def init(self: NeuronLayer, bs: Optional[int] = None): + """Return an empty initial neuron state""" + if bs is None or bs == 0: return jnp.zeros(self.shape) # No batch dimension + return jnp.zeros((bs, *self.shape)) + +# %% ../nbs/00_core.qmd 16 +def legendre_transform( + F: Callable # The function to transform + ): + "Transform scalar F(x) into the dual Fhat(xhat, x) using the Legendre transform" + + # We define custom gradient rules to give jax some autograd shortcuts + @jax.custom_jvp + def Fhat(xhat, x): return jnp.multiply(xhat, x).sum() - F(x) + + @Fhat.defjvp + def Fhat_jvp(primals, tangents): + (xhat, x), (dxhat, dx) = primals, tangents + o, do = Fhat(xhat, x), jnp.multiply(x, dxhat).sum() + return o, do + + return Fhat + +# %% ../nbs/00_core.qmd 20 +@patch +def energy(self: NeuronLayer, xhat, x): + """The energy of the neuron layer is the Legendre transform of the Lagrangian""" + return legendre_transform(self.lagrangian)(xhat, x) + +# %% ../nbs/00_core.qmd 24 +NeuronLayer.sigma = NeuronLayer.activations +NeuronLayer.E = NeuronLayer.energy + +# %% ../nbs/00_core.qmd 26 +@patch +def __repr__(self: NeuronLayer): + """Look nice when inspected""" + return f"NeuronLayer(lagrangian={self.lagrangian}, shape={self.shape})" + +@patch +def __post_init__(self: NeuronLayer): + """Ensure the neuron shape is a tuple""" + print("Post init") + if isinstance(self.shape, int): self.shape = (self.shape,) + +# %% ../nbs/00_core.qmd 28 +class LinearSynapse(eqx.Module): + """The energy synapse corrolary of the linear layer in standard neural networks""" + W: jax.Array + def __call__(self, xhat1:jax.Array, xhat2:jax.Array): + "Compute the interaction energy between activations `xhat1` and `xhat2`." + # Best to use batch-dim agnostic operations + return -jnp.einsum("...c,...d,cd->...", xhat1, xhat2, self.W) + + @classmethod + def rand_init(cls, key: jax.Array, x1_dim: int, x2_dim: int): + Winit = 0.02 * jr.normal(key, (x1_dim, x2_dim)) + return cls(W=Winit) + +# %% ../nbs/00_core.qmd 32 +class LinearSynapseWithBias(eqx.Module): + """A linear synapse with a bias""" + W: jax.Array + b: jax.Array + def __call__(self, xhat1:jax.Array, xhat2:jax.Array): + "Compute the interaction energy between activations `xhat1` and `xhat2`." + return -jnp.einsum("...c,...d,cd->...", xhat1, xhat2, self.W) - jnp.multiply(xhat2, self.b).sum() + + @classmethod + def rand_init(cls, key: jax.Array, x1_dim: int, x2_dim: int): + Winit = 0.02 * jr.normal(key, (x1_dim, x2_dim)) + binit = 0.02 * jr.normal(key, (x2_dim,)) + return cls(W=Winit, b=binit) + +class BiasSynapse(eqx.Module): + """Energy defines constant input to a neuron layer""" + b: jax.Array + def __call__(self, xhat:jax.Array): + "Compute the interaction energy between activations `xhat` and the bias `b`." + return -jnp.einsum("...c,c->...", xhat, self.b) + +# %% ../nbs/00_core.qmd 35 +class ConvSynapse(eqx.Module): + """The energy corrolary of a convolutional layer in standard neural networks""" + W: jax.Array + window_strides: Tuple[int, int] + padding: str + + @classmethod + def from_conv_params(cls, + key, # Random weight generation seed + channels_out:int, # nfilters + channels_in:int, # Channels in input + filter_shape:Tuple[int,int], # (h,w) size of filter + window_strides:Tuple[int,int], # (h, w) size of each step + padding="SAME", + mu=0.5, # Mean of W initialization + sigma=0.01, # stdev of W initialization + ): + "Initialize the ConvSynapse from the convolution parameters" + W = jr.normal(key, (channels_out, channels_in, *filter_shape)) * sigma + mu + return cls(W=W, window_strides=window_strides, padding=padding) + + def forward_conv(self, xhat1): + return jax.lax.conv_general_dilated(xhat1, self.W, window_strides=self.window_strides, padding=self.padding, dimension_numbers=("NHWC", "OIHW", "NHWC")) # in (1, H2, W2, Cout) + + def __call__(self, xhat1, xhat2): + """Energy of convolution is defined only for a single input""" + assert len(xhat1.shape)== 3, f"Shape should be (H,W,C), no batch dimension. Got `{xhat1.shape}` for xhat1" + assert len(xhat2.shape)== 3, f"Shape should be (H,W,C), no batch dimension. Got `{xhat2.shape}` for xhat2" + + xhat1 = xhat1[None] # Add batch dimension + xhat2 = xhat2[None] # Add batch dimension + + sig1_into_2 = self.forward_conv(xhat1) + return -jnp.multiply(xhat2, sig1_into_2).sum() + +# %% ../nbs/00_core.qmd 39 +class HAM(eqx.Module): + "A Hypergraph wrapper connecting all dynamic states (neurons) and learnable parameters (synapses) for our associative memory" + neurons: Dict[str, NeuronLayer] + hypersynapses: Dict[str, eqx.Module] + connections: List[Tuple[Tuple, str]] + +# %% ../nbs/00_core.qmd 43 +@patch(as_prop=True) +def n_neurons(self:HAM) -> int: + "Total number of neurons" + return len(self.neurons) + +@patch(as_prop=True) +def n_hypersynapses(self:HAM) -> int: + "Total number of hypersynapses" + return len(self.hypersynapses) + +@patch(as_prop=True) +def n_connections(self:HAM) -> int: + "Total number of connections" + return len(self.connections) + +# %% ../nbs/00_core.qmd 44 +@patch +def init_states(self: HAM, bs: Optional[int] = None): + """Initialize all neuron states""" + if bs is not None and bs > 0: warn("Vectorize with `ham.vectorize()` before processing batched states") + xs = {k: v.init(bs) for k, v in self.neurons.items()} + return xs + +# %% ../nbs/00_core.qmd 50 +@patch +def activations(self: HAM, xs): + """Convert hidden states of each neuron into their activations""" + xhats = {k: v.sigma(xs[k]) for k, v in self.neurons.items()} + return xhats + +# %% ../nbs/00_core.qmd 53 +@patch +def neuron_energies(self: HAM, xhats, xs): + """Retrieve the energies of each neuron in the HAM""" + return {k: self.neurons[k].energy(xhats[k], xs[k]) for k in self.neurons.keys()} + +@patch +def connection_energies(self: HAM, xhats): + """Get the energy for each connection""" + def get_energy(neuron_set, s): + neighbor_xhats = [xhats[k] for k in neuron_set] + return self.hypersynapses[s](*neighbor_xhats) + return [get_energy(neuron_set, s) for neuron_set, s in self.connections] + +@patch +def energy_tree(self: HAM, xhats, xs): + """Return energies for each individual component""" + neuron_energies = self.neuron_energies(xhats, xs) + connection_energies = self.connection_energies(xhats) + return {"neurons": neuron_energies, "connections": connection_energies} + +@patch +def energy(self: HAM, xhats, xs): + """The complete energy of the HAM""" + energy_tree = self.energy_tree(xhats, xs) + return jtu.tree_reduce(lambda E, acc: acc + E, energy_tree, 0) + +# %% ../nbs/00_core.qmd 57 +@patch +def dEdact(self: HAM, xhats, xs, return_energy=False): + """Calculate gradient of system energy w.r.t. each activation""" + if return_energy: return jax.value_and_grad(self.energy)(xhats, xs) + return jax.grad(self.energy)(xhats, xs) + +# %% ../nbs/00_core.qmd 59 +def _docstring_from(source_func): + """Decorator that copies the docstring from source_func to the decorated function""" + def decorator(target_func): + if source_func.__doc__: target_func.__doc__ = source_func.__doc__ + return target_func + return decorator + +# %% ../nbs/00_core.qmd 60 +class VectorizedHAM(eqx.Module): + """Re-expose HAM API with vectorized inputs. No new HAM behaviors should be implemented in this class.""" + _ham: eqx.Module + @property + def neurons(self): return self._ham.neurons + @property + def hypersynapses(self): return self._ham.hypersynapses + @property + def connections(self): return self._ham.connections + @property + def n_neurons(self): return self._ham.n_neurons + @property + def n_hypersynapses(self): return self._ham.n_hypersynapses + @property + def n_connections(self): return self._ham.n_connections + + @property + def _batch_axes(self: HAM): + """A helper function to tell vmap to batch along the 0'th dimension of each state in the HAM.""" + return {k: 0 for k in self._ham.neurons.keys()} + + @_docstring_from(HAM.init_states) + def init_states(self, bs=None): + if bs is None or bs == 0: warn("Vectorized HAMs should be initialized with a batch size") + xs = {k: v.init(bs) for k, v in self.neurons.items()} + return xs + + @_docstring_from(HAM.activations) + def activations(self, xs): return jax.vmap(self._ham.activations, in_axes=(self._batch_axes,))(xs) + + @_docstring_from(HAM.connection_energies) + def connection_energies(self, xhats): return jax.vmap(self._ham.connection_energies, in_axes=(self._batch_axes,))(xhats) + + @_docstring_from(HAM.neuron_energies) + def neuron_energies(self, xhats, xs): return jax.vmap(self._ham.neuron_energies, in_axes=(self._batch_axes, self._batch_axes))(xhats, xs) + + @_docstring_from(HAM.energy_tree) + def energy_tree(self, xhats, xs): return jax.vmap(self._ham.energy_tree, in_axes=(self._batch_axes, self._batch_axes))(xhats, xs) + + @_docstring_from(HAM.energy) + def energy(self, xhats, xs): return jax.vmap(self._ham.energy, in_axes=(self._batch_axes, self._batch_axes))(xhats, xs) + + @_docstring_from(HAM.dEdact) + def dEdact(self, xhats, xs, return_energy=False): return jax.vmap(self._ham.dEdact, in_axes=(self._batch_axes, self._batch_axes, None))(xhats, xs, return_energy) + + def unvectorize(self): return self._ham + def vectorize(self): return self + +# %% ../nbs/00_core.qmd 61 +@patch +def vectorize(self: HAM): + """Vectorize to work on batches of inputs""" + return VectorizedHAM(self) -# %% ../nbs/00_core.ipynb 3 -def foo(): pass +@patch +def unvectorize(self: HAM): + """Unvectorize to work on single inputs""" + return self diff --git a/hamux/datasets.py b/hamux/datasets.py deleted file mode 100644 index 89886e5..0000000 --- a/hamux/datasets.py +++ /dev/null @@ -1,212 +0,0 @@ -""" -Example Usage: - -``` -from datasets import DataloadingArgs, DataConfigMNIST - -args = DataloadingArgs( - dataset="torch/MNIST", - aa=None, - reprob=0.0, - vflip=0., - hflip=0., - scale=(0.8,1.), - batch_size=10, - color_jitter=0., - validation_batch_size=10_000, -) -data_config = DataConfigMNIST(input_size=(1,28,28)) -loader_train, loader_eval = create_dataloaders(args, data_config) -``` -""" - -import timm -import torch -import numpy as np -from einops import rearrange -from timm.data import create_dataset, create_loader -from dataclasses import dataclass -from pathlib import Path -from typing import * - -class ShowImgMixin(): - def show(self, x): - x = rearrange(x, "... c h w -> ... h w c") - x = x * torch.tensor(self.std) + torch.tensor(self.mean) - return np.array(x) - -@dataclass -class DataConfigMNIST(ShowImgMixin): - """ - Mean/std from https://stackoverflow.com/questions/66678052/how-to-calculate-the-mean-and-the-std-of-cifar10-data - """ - input_size:Tuple[int,int,int]=(1,28,28) - mean:Tuple[float,float,float]=0. - std:Tuple[float,float,float]=1. - interpolation:str='bicubic' - crop_pct:float=0.875 - n_classes:int=10 - -@dataclass -class DataConfigCIFAR10(ShowImgMixin): - """ - Mean/std from https://stackoverflow.com/questions/66678052/how-to-calculate-the-mean-and-the-std-of-cifar10-data - """ - input_size:Tuple[int,int,int]=(3,32,32) - mean:Tuple[float,float,float]=(0.49139968, 0.48215827 ,0.44653124) - std:Tuple[float,float,float]=(0.24703233, 0.24348505, 0.26158768) - interpolation:str='bicubic' - crop_pct:float=0.875 - n_classes:int=10 - -@dataclass -class DataConfigImageNet(ShowImgMixin): - """ - """ - input_size:Tuple[int,int,int]=(3,224,224) - mean:Tuple[float,float,float]=(0.485, 0.456, 0.406) - std:Tuple[float,float,float]=(0.229, 0.224, 0.225) - interpolation:str='bicubic' - crop_pct:float=0.875 - n_classes:int=100 - -@dataclass -class DataloadingArgs: - data_dir:str=str(Path.home() / "datasets/timm-datasets") - dataset:str="" - class_map:str="" - train_split:str="" - dataset_download:bool=True - val_split:str="validation" - train_split:str="train" - batch_size:int=32 - epoch_repeats:int=0 - prefetcher:bool=False - no_aug:bool=False - reprob:float=0. - remode:str="pixel" - recount:int=1 - resplit:bool=False - scale:Tuple[float,float]=(0.2, 1.0) # Random resize aspect ratio - ratio:Tuple[float,float]=(3./4., 4./3.) - hflip:float=0.5 - vflip:float=0.5 - color_jitter:float=0.4 - aa:Optional[str]=None - # aa="rand" - aug_repeats:int=0 - workers:int=4 - distributed:bool=False - pin_mem:bool=False - use_multi_epochs_loader:bool=False - worker_seeding:str='all' - validation_batch_size:Optional[int]=None - -def create_dataloaders(args, data_config): - vbatch_size = args.validation_batch_size or args.batch_size - dataset_train = create_dataset( - args.dataset, root=args.data_dir, split=args.train_split, is_training=True, - class_map=args.class_map, - download=args.dataset_download, - batch_size=args.batch_size, - repeats=args.epoch_repeats) - - dataset_eval = create_dataset( - args.dataset, root=args.data_dir, split=args.val_split, is_training=False, - class_map=args.class_map, - download=args.dataset_download, - batch_size=vbatch_size) - - loader_train = create_loader( - dataset_train, - input_size=data_config.input_size, - batch_size=args.batch_size, - is_training=True, - use_prefetcher=args.prefetcher, - no_aug=args.no_aug, - re_prob=args.reprob, - re_mode=args.remode, - re_count=args.recount, - re_split=args.resplit, - scale=args.scale, - ratio=args.ratio, - hflip=args.hflip, - vflip=args.vflip, - color_jitter=args.color_jitter, - auto_augment=args.aa, - num_aug_repeats=args.aug_repeats, - # num_aug_splits=num_aug_splits, - # interpolation=train_interpolation, - mean=data_config.mean, - std=data_config.std, - num_workers=args.workers, - distributed=args.distributed, - # collate_fn=collate_fn, - pin_memory=args.pin_mem, - use_multi_epochs_loader=args.use_multi_epochs_loader, - worker_seeding=args.worker_seeding, - ) - - loader_eval = create_loader( - dataset_eval, - input_size=data_config.input_size, - batch_size=vbatch_size, - is_training=False, - use_prefetcher=args.prefetcher, - interpolation=data_config.interpolation, - mean=data_config.mean, - std=data_config.std, - num_workers=1, - distributed=args.distributed, - crop_pct=data_config.crop_pct, - pin_memory=args.pin_mem, - ) - - return loader_train, loader_eval - - -""" Example initializations of datasets: - -``` -## CIFAR10 -args = DataloadingArgs( - dataset="torch/CIFAR10", - aa=None, - reprob=0.2, - vflip=0.2, - hflip=0.5, - batch_size=128, - validation_batch_size=10_000, # Get the entire validation set at once -) -data_config = DataConfigCIFAR10() - - -## ImageNet -args = DataloadingArgs( - data_dir=Path.home()/"datasets/timm-datasets/ImageNet100", - aa=None, - reprob=0.1, - vflip=0.0, - hflip=0.5, - batch_size=256, - validation_batch_size=500 -) -data_config = DataConfigImageNet(input_size=(3,128,128)) # Feel free to change the input size of our dataset! - - -## MNIST -args = DataloadingArgs( - dataset="torch/MNIST", - aa=None, - reprob=0.1, - vflip=0., - hflip=0., - scale=(0.7,1.), - batch_size=100, - # batch_size=2000, - color_jitter=0.4, - validation_batch_size=1000, -) -data_config = DataConfigMNIST(input_size=(1,28,28)) -``` -""" \ No newline at end of file diff --git a/hamux/ham.py b/hamux/ham.py deleted file mode 100644 index 07f727a..0000000 --- a/hamux/ham.py +++ /dev/null @@ -1,200 +0,0 @@ -# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/03_ham.ipynb. - -# %% auto 0 -__all__ = ['HAM'] - -# %% ../nbs/03_ham.ipynb 6 -import jax -import jax.numpy as jnp -from typing import * -import treex as tx -from .layers import Layer -from .synapses import Synapse -import jax.tree_util as jtu -from .utils import pytree_save, pytree_load, to_pickleable, align_with_state_dict -import pickle -import functools as ft -from fastcore.utils import * -from abc import ABC, abstractmethod, abstractproperty -import hypernetx as hnetx - -# %% ../nbs/03_ham.ipynb 8 -class HAM(tx.Module): - layers: List[Layer] - synapses: List[Synapse] - connections: List[Tuple[Tuple, int]] - - def __init__(self, layers, synapses, connections): - self.layers = layers - self.synapses = synapses - self.connections = connections - - @property - def n_layers(self): return len(self.layers) - @property - def n_synapses(self): return len(self.synapses) - @property - def n_connections(self): return len(self.connections) - @property - def layer_taus(self): return [layer.tau for layer in self.layers] - def alphas(self, dt): return [dt / tau for tau in self.layer_taus] - -# %% ../nbs/03_ham.ipynb 9 -@patch -def activations(self:HAM, - xs:jnp.ndarray): # Collection of states for each layer - """Turn a collection of states into a collection of activations""" - gs = [self.layers[i].g(xs[i]) for i in range(len(xs))] - return gs - -# %% ../nbs/03_ham.ipynb 10 -@patch -def layer_energy(self:HAM, - xs:jnp.ndarray): # Collection of states for each layer - """The total contribution of the layers' contribution to the energy of the HAM""" - energies = jnp.stack([self.layers[i].energy(x) for i, x in enumerate(xs)]) - return jnp.sum(energies) - -@patch -def synapse_energy(self:HAM, - gs:jnp.ndarray): # Collection of activations of each layer - """The total contribution of the synapses' contribution to the energy of the HAM. - - A function of the activations `gs` rather than the states `xs` - """ - def get_energy(lset, k): - mygs = [gs[i] for i in lset] - synapse = self.synapses[k] - return synapse.energy(*mygs) - energies = jnp.stack([get_energy(lset, k) for lset, k in self.connections]) - return jnp.sum(energies) - -@patch -def energy(self:HAM, - xs:jnp.ndarray): # Collection of states for each layer - """The complete energy of the HAM""" - gs = self.activations(xs) - energy = self.layer_energy(xs) + self.synapse_energy(gs) - return energy - -# %% ../nbs/03_ham.ipynb 12 -@patch -def init_states(self:HAM, - bs=None, # Batch size of the states to initialize, if needed - rng=None): # RNG seed for random initialization of the states, if non-zero initializations are desired - """Initialize the states of every layer in the network""" - if rng is not None: - keys = jax.random.split(rng, self.n_layers) - return [layer.init_state(bs, rng=key) for layer, key in zip(self.layers, keys)] - return [layer.init_state(bs) for layer in self.layers] - -@patch -def init_states_and_params(self:HAM, - param_key, # RNG seed for random initialization of the parameters - bs=None, # Batch size of the states to initialize, if needed - state_key=None): # RNG seed for random initialization of the states, if non-zero initializations are desired - """Initialize the states and parameters of every layer and synapse in the network""" - # params don't need a batch size to initialize - params = self.init(param_key, self.init_states(), call_method="energy") - states = self.init_states(bs, rng=state_key) - return states, params - -# %% ../nbs/03_ham.ipynb 23 -@patch -def dEdg(self:HAM, - xs:jnp.ndarray): - """Calculate the gradient of system energy wrt. the activations - - Notice that we use an important mathematical property of the Legendre transform to take a mathematical shortcut, - where dE_layer / dg = x - """ - gs = self.activations(xs) - return jtu.tree_map( - lambda x, s: x + s, xs, jax.grad(self.synapse_energy)(gs) - ) - -@patch -def updates(self:HAM, - xs:jnp.ndarray): # Collection of states for each layer - """The negative of our dEdg, computing the update direction each layer should descend""" - return jtu.tree_map(lambda dg: -dg, self.dEdg(xs)) - -# %% ../nbs/03_ham.ipynb 29 -@patch -def step(self:HAM, - xs: List[jnp.ndarray], # Collection of current states for each layer - updates: List[jnp.ndarray], # Collection of update directions for each state - dt: float = 0.1, # Stepsize to take in direction of updates - masks: Optional[List[jnp.ndarray]] = None, # Boolean mask, 0 if clamped neuron, and 1 elsewhere. A pytree identical to `xs`. Optional. -): - """A discrete step down the energy using step size `dt` scaled by the `tau` of each layer""" - taus = self.layer_taus - alphas = [dt / tau for tau in taus] # Scaling factor of the update size of each layer - if masks is not None: - next_xs = jtu.tree_map(lambda x, u, m, alpha: x + alpha * u * m, xs, updates, masks, alphas) - else: - next_xs = jtu.tree_map(lambda x, u, alpha: x + alpha * u, xs, updates, alphas) - return next_xs - -# %% ../nbs/03_ham.ipynb 31 -@patch -def _statelist_batch_axes(self:HAM): - """A helper function to tell vmap to batch along the 0'th dimension of each state in the HAM.""" - return ([0 for _ in range(self.n_layers)],) - -@patch -def vactivations(self:HAM, - xs: List[jnp.ndarray]): # Collection of states for each layer - """A vectorized version of `activations`""" - return jax.vmap(self.activations, in_axes=self._statelist_batch_axes())(xs) - -@patch -def venergy(self:HAM, - xs: List[jnp.ndarray]): # Collection of states for each layer - """A vectorized version of `energy`""" - return jax.vmap(self.energy, in_axes=self._statelist_batch_axes())(xs) - -@patch -def vdEdg(self:HAM, - xs: List[jnp.ndarray]): # Collection of states for each layer - """A vectorized version of `dEdg`""" - return jax.vmap(self.dEdg, in_axes=self._statelist_batch_axes())(xs) - -@patch -def vupdates(self:HAM, - xs: List[jnp.ndarray]): # Collection of states for each layer - """A vectorized version of `updates`""" - return jax.vmap(self.updates, in_axes=self._statelist_batch_axes())(xs) - -# %% ../nbs/03_ham.ipynb 38 -@patch -def load_state_dict(self:HAM, - state_dict:Any): # The dictionary of all parameters, saved by `save_state_dict` - """Load the state dictionary for a HAM""" - if not self.initialized: - _, self = self.init_states_and_params(jax.random.PRNGKey(0), 1) - self.connections = state_dict["connections"] - self.layers = align_with_state_dict(self.layers, state_dict["layers"]) - self.synapses = align_with_state_dict(self.synapses, state_dict["synapses"]) - return self - -@patch -def to_state_dict(self:HAM): - """Convert HAM to state dictionary of parameters and connections""" - return jtu.tree_map(to_pickleable, self.to_dict()) - -@patch -def save_state_dict(self:HAM, - fname:Union[str, Path], # Filename of checkpoint to save - overwrite:bool=True): # Overwrite an existing file of the same name? - """Save the state dictionary for a HAM""" - to_save = self.to_state_dict() - pytree_save(to_save, fname, overwrite=overwrite) - -@patch -def load_ckpt(self:HAM, - ckpt_f:Union[str, Path]): # Filename of checkpoint to load - """Load from file name""" - with open(ckpt_f, "rb") as fp: - state_dict = pickle.load(fp) - return self.load_state_dict(state_dict) diff --git a/hamux/lagrangians.py b/hamux/lagrangians.py index ea27426..2ee5742 100644 --- a/hamux/lagrangians.py +++ b/hamux/lagrangians.py @@ -1,72 +1,84 @@ -# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/00_lagrangians.ipynb. +"""The well-behaved dynamics of associative memories is described by the Lagrangians of the neurons.""" + +# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/01_lagrangians.qmd. # %% auto 0 -__all__ = ['lagr_identity', 'lagr_repu', 'lagr_relu', 'lagr_softmax', 'lagr_softmax_unstable', 'lagr_exp', 'lagr_rexp', - 'lagr_tanh', 'lagr_sigmoid', 'lagr_layernorm', 'lagr_spherical_norm', 'LIdentity', 'LRepu', 'LRelu', - 'LSigmoid', 'LSoftmax', 'LSoftmaxUnstable', 'LExp', 'LRexp', 'LTanh', 'LLayerNorm', 'LSphericalNorm'] +__all__ = ['Scalar', 'Tensor', 'lagr_identity', 'lagr_repu', 'lagr_relu', 'lagr_exp', 'lagr_rexp', 'lagr_tanh', 'lagr_sigmoid', + 'lagr_softmax', 'lagr_layernorm', 'lagr_spherical_norm', 'lagr_ghostmax', 'ghostmax'] -# %% ../nbs/00_lagrangians.ipynb 3 -import jax.numpy as jnp +# %% ../nbs/01_lagrangians.qmd 3 +import equinox as eqx +from typing import Union, Callable, Tuple, Dict, List, Optional import jax +import jax.numpy as jnp +import jax.tree_util as jtu +import jax.random as jr +from jax import lax +from jax._src.numpy.reductions import _reduction_dims +from jax._src.numpy.util import promote_args_inexact import numpy as np -from fastcore.test import * -import functools as ft -from typing import * -import treex as tx -from dataclasses import dataclass -from typing import * - -# %% ../nbs/00_lagrangians.ipynb 7 -def lagr_identity(x): +from jaxtyping import Float, Array + +Scalar = Float[Array, ""] +Tensor = Float[Array, "..."] + +# %% ../nbs/01_lagrangians.qmd 5 +def lagr_identity(x: Array, # Input tensor + ) -> Float: # Output scalar """The Lagrangian whose activation function is simply the identity.""" - return 1 / 2 * jnp.power(x, 2) + return 0.5 * jnp.power(x, 2).sum() -# %% ../nbs/00_lagrangians.ipynb 9 -def lagr_repu(x, - n): # Degree of the polynomial in the power unit - """Rectified Power Unit of degree `n`""" - return 1 / n * jnp.power(jnp.maximum(x, 0), n) +# %% ../nbs/01_lagrangians.qmd 8 +def _repu(x: Array, # Input tensor + n: float # Degree of the polynomial in the power unit + ) -> Float: # Output scalar + return jnp.maximum(x, 0) ** n -# %% ../nbs/00_lagrangians.ipynb 12 -def lagr_relu(x): - """Rectified Linear Unit. Same as repu of degree 2""" - return lagr_repu(x, 2) -# %% ../nbs/00_lagrangians.ipynb 15 -def lagr_softmax(x, - beta:float=1.0, # Inverse temperature - axis:int=-1): # Dimension over which to apply logsumexp - """The lagrangian of the softmax -- the logsumexp""" - return (1/beta * jax.nn.logsumexp(beta * x, axis=axis, keepdims=True)) +def lagr_repu(x: Array, # Input tensor + n: float # Degree of the polynomial in the power unit + ) -> Float: # Output scalar + """Rectified Power Unit of degree `n`""" + return 1 / n * jnp.power(jnp.maximum(x, 0), n).sum() -def lagr_softmax_unstable(x, - beta:float=1.0, # Inverse temperature - axis:int=-1): # Dimension over which to apply logsumexp - """The lagrangian of the softmax -- the logsumexp. However, code the `log(sum(exp(...)))` part manually, which can lead to instabilities - - The benefit is in porting HAMUX models into the browser, because [TensorFlowJS](https://github.com/tensorflow/tfjs) does not currently support - JAX logsumexp - """ - return 1/beta * jnp.log(jnp.sum(jnp.exp(beta * x), axis=axis, keepdims=True)) +# %% ../nbs/01_lagrangians.qmd 11 +def lagr_relu(x: Array, # Input tensor + ) -> Float: # Output scalar + """Rectified Linear Unit. Same as `lagr_repu` of degree 2""" + return lagr_repu(x, 2) -# %% ../nbs/00_lagrangians.ipynb 18 -def lagr_exp(x, - beta:float=1.0): # Inverse temperature +# %% ../nbs/01_lagrangians.qmd 13 +def lagr_exp(x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar """Exponential activation function, as in [Demicirgil et al.](https://arxiv.org/abs/1702.01929). Operates elementwise""" - return 1 / beta * jnp.exp(beta * x) + return 1 / beta * jnp.exp(beta * x).sum() -# %% ../nbs/00_lagrangians.ipynb 21 -def lagr_rexp(x, - beta:float=1.0): # Inverse temperature +# %% ../nbs/01_lagrangians.qmd 16 +def _rexp( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature +) -> Float: # Output scalar """Rectified exponential activation function""" xclipped = jnp.maximum(x, 0) - return (1 / beta * jnp.exp(beta * xclipped)-xclipped) + return jnp.exp(beta * xclipped) - 1 + + +def lagr_rexp(x: Array, + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar + """Lagrangian of the Rectified exponential activation function""" + xclipped = jnp.maximum(x, 0) + return (jnp.exp(beta * xclipped) / beta - xclipped).sum() -# %% ../nbs/00_lagrangians.ipynb 25 +# %% ../nbs/01_lagrangians.qmd 17 @jax.custom_jvp -def _lagr_tanh(x, beta=1.0): +def _lagr_tanh(x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar return 1 / beta * jnp.log(jnp.cosh(beta * x)) + @_lagr_tanh.defjvp def _lagr_tanh_defjvp(primals, tangents): x, beta = primals @@ -75,264 +87,184 @@ def _lagr_tanh_defjvp(primals, tangents): tangent_out = jnp.tanh(beta * x) * x_dot return primal_out, tangent_out -def lagr_tanh(x, - beta=1.0): # Inverse temperature + +def lagr_tanh(x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar """Lagrangian of the tanh activation function""" - return _lagr_tanh(x, beta) + return _lagr_tanh(x, beta).sum() -# %% ../nbs/00_lagrangians.ipynb 29 +# %% ../nbs/01_lagrangians.qmd 19 @jax.custom_jvp -def _lagr_sigmoid(x, - beta=1.0, # Inverse temperature - scale=1.0): # Amount to stretch the range of the sigmoid's lagrangian +def _lagr_sigmoid( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar """The lagrangian of a sigmoid that we can define custom JVPs of""" - return scale / beta * jnp.log(jnp.exp(beta * x) + 1) + return 1. / beta * jnp.log(jnp.exp(beta * x) + 1) + + +def _sigmoid( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar + """The basic sigmoid""" + return 1. / (1 + jnp.exp(-beta * x)) -def _tempered_sigmoid(x, - beta=1.0, # Inverse temperature - scale=1.0): # Amount to stretch the range of the sigmoid - """The basic sigmoid, but with a scaling factor""" - return scale / (1 + jnp.exp(-beta * x)) @_lagr_sigmoid.defjvp def _lagr_sigmoid_jvp(primals, tangents): - x, beta, scale = primals - x_dot, beta_dot, scale_dot = tangents - primal_out = _lagr_sigmoid(x, beta, scale) - tangent_out = _tempered_sigmoid(x, beta=beta, scale=scale) * x_dot # Manually defined sigmoid + x, beta = primals + x_dot, beta_dot = tangents + primal_out = _lagr_sigmoid(x, beta) + tangent_out = ( + _sigmoid(x, beta=beta) * x_dot + ) # Manually defined sigmoid return primal_out, tangent_out -def lagr_sigmoid(x, - beta=1.0, # Inverse temperature - scale=1.0): # Amount to stretch the range of the sigmoid's lagrangian + +def lagr_sigmoid( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature +) -> Float: # Output scalar """The lagrangian of the sigmoid activation function""" - return _lagr_sigmoid(x, beta=beta, scale=scale) - -# %% ../nbs/00_lagrangians.ipynb 32 -def _simple_layernorm(x:jnp.ndarray, - gamma:float=1.0, # Scale the stdev - delta:Union[float, jnp.ndarray]=0., # Shift the mean - axis=-1, # Which axis to normalize - eps=1e-5, # Prevent division by 0 - ): + return _lagr_sigmoid(x, beta=beta).sum() + +# %% ../nbs/01_lagrangians.qmd 22 +def lagr_softmax( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + axis: int = -1, # Dimension over which to apply logsumexp +) -> Float: # Output scalar + """The lagrangian of the softmax -- the logsumexp""" + return 1 / beta * jax.nn.logsumexp(beta * x, axis=axis, keepdims=False) + +# %% ../nbs/01_lagrangians.qmd 25 +def _simple_layernorm( + x: Array, # Input tensor + gamma: float = 1.0, # Scale the stdev + delta: Union[float, Array] = 0.0, # Shift the mean + axis: int = -1, # Which axis to normalize + eps: float = 1e-5, # Prevent division by 0 +) -> Array: # Layer normalized `x` """Layer norm activation function""" xmean = x.mean(axis, keepdims=True) xmeaned = x - xmean denominator = jnp.sqrt(jnp.power(xmeaned, 2).mean(axis, keepdims=True) + eps) return gamma * xmeaned / denominator + delta -def lagr_layernorm(x:jnp.ndarray, - gamma:float=1.0, # Scale the stdev - delta:Union[float, jnp.ndarray]=0., # Shift the mean - axis=-1, # Which axis to normalize - eps=1e-5, # Prevent division by 0 - ): - """Lagrangian of the layer norm activation function""" + +def lagr_layernorm( + x: Array, # Input tensor + gamma: float = 1.0, # Scale the stdev + delta: Union[float, Array] = 0.0, # Shift the mean + axis: int = -1, # Which axis to normalize + eps: float = 1e-5, # Prevent division by 0 +) -> Float: # Output scalar + """Lagrangian of the layer norm activation function. + + `gamma` must be a float, not a vector. + """ D = x.shape[axis] if axis is not None else x.size xmean = x.mean(axis, keepdims=True) xmeaned = x - xmean y = jnp.sqrt(jnp.power(xmeaned, 2).mean(axis, keepdims=True) + eps) - return D * gamma * y + (delta * x).sum() - - -# %% ../nbs/00_lagrangians.ipynb 34 -def _simple_spherical_norm(x:jnp.ndarray, - axis=-1, # Which axis to normalize - ): + return (D * gamma * y + (delta * x).sum()).sum() + +# %% ../nbs/01_lagrangians.qmd 27 +def _simple_spherical_norm( + x: Array, # Input tensor + gamma: float = 1.0, # Scale the stdev + delta: Union[float, Array] = 0.0, # Shift the mean + axis: int = -1, # Which axis to normalize + eps=1e-5, # Prevent division by 0 +): """Spherical norm activation function""" - xmean = x.mean(axis, keepdims=True) - xmeaned = x - xmean - denominator = jnp.sqrt(jnp.power(xmeaned, 2).mean(axis, keepdims=True) + eps) - return gamma * xmeaned / denominator + delta - -def lagr_spherical_norm(x:jnp.ndarray, - gamma:float=1.0, # Scale the stdev - delta:Union[float, jnp.ndarray]=0., # Shift the mean - axis=-1, # Which axis to normalize - eps=1e-5, # Prevent division by 0 - ): - """Lagrangian of the spherical norm activation function""" + xnorm = jnp.sqrt(jnp.power(x, 2).sum(axis, keepdims=True) + eps) + return gamma * x / xnorm + delta + + +def lagr_spherical_norm( + x: Array, # input tensor + gamma: float = 1.0, # Scale the stdev + delta: Union[float, jnp.ndarray] = 0.0, # Shift the mean + axis: int=-1, # Which axis to normalize + eps: float=1e-5, # Prevent division by 0 +) -> Float: # Output scalar + """Lagrangian of the spherical norm (L2 norm) activation function""" y = jnp.sqrt(jnp.power(x, 2).sum(axis, keepdims=True) + eps) - return gamma * y + (delta * x).sum() - - -# %% ../nbs/00_lagrangians.ipynb 37 -class LIdentity(tx.Module): - """Reduced Lagrangian whose activation function is the identity function""" - def __init__(self): pass - def __call__(self, x): - return lagr_identity(x).sum() - -class LRepu(tx.Module): - """Reduced Lagrangian whose activation function is the rectified polynomial unit of specified degree `n`""" - n: float = 2 - - # Need a default for `n` to work with layer creation - def __init__(self, - n=2.): # The degree of the RePU. By default, set to the ReLU configuration - self.n = n - - def __call__(self, x): - return lagr_repu(x, self.n).sum() - -class LRelu(tx.Module): - """Reduced Lagrangian whose activation function is the rectified linear unit""" - def __init__(self): pass - def __call__(self, x): - return lagr_relu(x).sum() - -class LSigmoid(tx.Module): - """Reduced Lagrangian whose activation function is the sigmoid - - Parameterized by (beta) - """ - beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0) - scale: float = tx.Parameter.node(default=1.0) - min_beta: float = 1e-6 - - def __init__(self, - beta=1., # Inverse temperature - scale=1., # Amount to stretch the sigmoid. - min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive. - self.beta = beta - self.scale = scale - self.min_beta = min_beta - - def __call__(self, x): - return lagr_sigmoid(x, beta=jnp.clip(self.beta, self.min_beta), scale=self.scale).sum() - -class LSoftmax(tx.Module): - """Reduced Lagrangian whose activation function is the softmax - - Parameterized by (beta) - """ - beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0) - axis: int = -1 - min_beta: float = 1e-6 - - def __init__(self, - beta=1., # Inverse temperature - axis=-1, # Axis over which to apply the softmax - min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive. - self.beta = beta - self.axis = axis - self.min_beta = min_beta - - def __call__(self, x): - return lagr_softmax(x, beta=jnp.clip(self.beta, self.min_beta), axis=self.axis).sum() - - -class LSoftmaxUnstable(tx.Module): - """Reduced Lagrangian whose activation function is the softmax, using manually coded `logsumexp` for browser compatibility - - Parameterized by (beta) - """ - beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0) - axis: int = -1 - min_beta: float = 1e-6 - - def __init__(self, - beta=1., # Inverse temperature - axis=-1, # Axis over which to apply the softmax - min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive. - self.beta = beta - self.axis = axis - self.min_beta = min_beta - - def __call__(self, x): - return lagr_softmax_unstable(x, beta=jnp.clip(self.beta, self.min_beta), axis=self.axis).sum() - + return (gamma * y + (delta * x).sum()).sum() + +# %% ../nbs/01_lagrangians.qmd 29 +# Enable this function, but don't document it for now +def lagr_ghostmax( + a: Array, # Input tensor + axis: Optional[int] = None, # Axis along which the sum to be computed. If None, the sum is computed along all the axes. + b: Union[Array, None] = None, # Scaling factors for the exponentials. Must be broadcastable to the shape of a. + keepdims: bool = False, # If `True`, the axes that are reduced are left in the output as dimensions of size 1. + return_sign: bool = False, # If `True`, the output will be a (result, sign) pair, where sign is the sign of the sums and result contains the logarithms of their absolute values. If False only result is returned and it will contain NaN values if the sums are negative. + ) -> Union[Array, Tuple[Array, Array]]: # Either an array result or a pair of arrays (result, sign), depending on the value of the return_sign argument. + """ A strictly convex version of logsumexp that concatenates 0 to the array before passing to logsumexp. Code adapted from `jax.nn.logsumexp` (documentation below) -class LExp(tx.Module): - """Reduced Lagrangian whose activation function is the exponential function - - Parameterized by (beta) - """ - beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0) - min_beta: float = 1e-6 - - def __init__(self, - beta=1., # Inverse temperature, for the sharpness of the exponent - min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive. - self.beta = beta - self.min_beta = min_beta + """ + jax.nn.logsumexp.__doc__ + if b is not None: + a_arr, b_arr = promote_args_inexact("logsumexp", a, b) + a_arr = jnp.where(b_arr != 0, a_arr, -jnp.inf) + else: + a_arr, = promote_args_inexact("logsumexp", a) + b_arr = a_arr # for type checking + pos_dims, dims = _reduction_dims(a_arr, axis) + amax = jnp.max(a_arr, axis=dims, keepdims=keepdims) + amax = lax.max(amax, 0.) + amax = lax.stop_gradient(lax.select(jnp.isfinite(amax), amax, lax.full_like(amax, 0))) + amax_with_dims = amax if keepdims else lax.expand_dims(amax, pos_dims) + + # fast path if the result cannot be negative. + if b is None and not np.issubdtype(a_arr.dtype, np.complexfloating): + out = lax.add(lax.log(jnp.sum(lax.exp(lax.sub(a_arr, amax_with_dims)), + axis=dims, keepdims=keepdims) + lax.exp(-amax)), + amax) + sign = jnp.where(jnp.isnan(out), out, 1.0) + sign = jnp.where(jnp.isneginf(out), 0.0, sign).astype(out.dtype) + else: + expsub = lax.exp(lax.sub(a_arr, amax_with_dims)) + if b is not None: + expsub = lax.mul(expsub, b_arr) + + expsub = expsub + lax.exp(-amax_with_dims) + sumexp = jnp.sum(expsub, axis=dims, keepdims=keepdims) + + sign = lax.stop_gradient(jnp.sign(sumexp)) + if np.issubdtype(sumexp.dtype, np.complexfloating): + if return_sign: + sumexp = sign*sumexp + out = lax.add(lax.log(sumexp), amax) + else: + out = lax.add(lax.log(lax.abs(sumexp)), amax) + if return_sign: + return (out, sign) + if b is not None: + if not np.issubdtype(out.dtype, np.complexfloating): + with jax.debug_nans(False): + out = jnp.where(sign < 0, jnp.array(np.nan, dtype=out.dtype), out) + return out + return out + +def ghostmax(a, axis=None): + """Properly implemented ghostmax, robust to input scale. A softmax with additional `1+__` in the denominator. The derivative of `lseplus`""" + if axis is None: + og_shape = a.shape + a = jnp.pad(a.ravel(), ((1,0),), constant_values=0.) + a = jax.nn.softmax(a) + return a[1:].reshape(og_shape) + else: + pad_widths = [(0,0) for _ in range(len(a.shape))] + pad_widths[axis] = (1,0) + pad_width = tuple(pad_widths) - def __call__(self, x): - return lagr_exp(x, beta=jnp.clip(self.beta, self.min_beta)).sum() - -class LRexp(tx.Module): - """Reduced Lagrangian whose activation function is the rectified exponential function - - Parameterized by (beta) - """ - beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0) - min_beta: float = 1e-6 - - def __init__(self, - beta=1., # Inverse temperature, for the sharpness of the exponent - min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive. - self.beta = beta - self.min_beta = min_beta + a = jnp.pad(a, pad_width, constant_values=0.) + a = jax.nn.softmax(a, axis=axis) - def __call__(self, x): - return lagr_rexp(x, beta=jnp.clip(self.beta, self.min_beta)).sum() - - -class LTanh(tx.Module): - """Reduced Lagrangian whose activation function is the tanh - - Parameterized by (beta) - """ - beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0) - min_beta: float = 1e-6 - - def __init__(self, - beta=1., # Inverse temperature, for the sharpness of the exponent - min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive. - self.beta = beta - self.min_beta = min_beta - - def __call__(self, x): - return lagr_tanh(x, beta=jnp.clip(self.beta,self.min_beta)).sum() - -class LLayerNorm(tx.Module): - """Reduced Lagrangian whose activation function is the layer norm - - Parameterized by (gamma, delta), a scale and a shift - """ - gamma: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0) - delta: Union[float, jnp.ndarray] = tx.Parameter.node(default=0.) - eps: float = 1e-5 - - def __init__(self, - gamma=1., # Inverse temperature, for the sharpness of the exponent - delta=0., - eps = 1e-5 - ): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive. - self.gamma = gamma - self.delta = delta - self.eps = eps - - def __call__(self, x): - return lagr_layernorm(x, gamma=self.gamma, delta=self.delta, eps=self.eps).sum() - -class LSphericalNorm(tx.Module): - """Reduced Lagrangian whose activation function is the spherical L2 norm - - Parameterized by (gamma, delta), a scale and a shift - """ - # gamma: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0) - # delta: Union[float, jnp.ndarray] = tx.Parameter.node(default=0.) - eps: float = 1e-5 - - def __init__(self, - gamma=1., # Inverse temperature, for the sharpness of the exponent - delta=0., - eps = 1e-5 - ): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive. - self.gamma = gamma - self.delta = delta - self.eps = eps - - def __call__(self, x): - return lagr_spherical_norm(x, gamma=self.gamma, delta=self.delta, eps=self.eps).sum() + out_idxer = [slice(None) for _ in range(len(a.shape))] + out_idxer[axis] = slice(1, None) + return a[tuple(out_idxer)] diff --git a/hamux/layers.py b/hamux/layers.py deleted file mode 100644 index 1ca14df..0000000 --- a/hamux/layers.py +++ /dev/null @@ -1,120 +0,0 @@ -# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/01_layers.ipynb. - -# %% auto 0 -__all__ = ['IdentityLayer', 'RepuLayer', 'ReluLayer', 'SoftmaxLayer', 'SigmoidLayer', 'TanhLayer', 'ExpLayer', 'RexpLayer', - 'LayerNormLayer', 'Layer', 'MakeLayer'] - -# %% ../nbs/01_layers.ipynb 9 -import jax -import jax.numpy as jnp -from typing import * -import treex as tx -from abc import ABC, abstractmethod -from flax import linen as nn -from .lagrangians import * -import functools as ft -from fastcore.meta import delegates -from fastcore.utils import * -from fastcore.basics import * - -# %% ../nbs/01_layers.ipynb 10 -class Layer(tx.Module): - """The energy building block of any activation in our network that we want to hold state over time""" - lagrangian: tx.Module - shape: Tuple - tau: float - use_bias: bool - bias: jnp.ndarray = tx.Parameter.node(default=None) - - def __init__(self, - lagrangian:tx.Module, # Factory function creating lagrangian module describing - # lagrangian:Union[Callable, tx.Module], Either a factory function or the module itself depending on `init_lagr's` value - shape:Tuple[int], # Number and shape of neuron assembly - tau:float=1.0, # Time constant - use_bias:bool=False, # Add bias? - init_lagrangian=False, # Initialize the lagrangian with kwargs? - name:str=None, # Overwrite default class name, if provided - **kwargs, # Passed to lagranigan factory - ): - self.lagrangian = lagrangian(**kwargs) if init_lagrangian else lagrangian - self.shape = shape - assert tau > 0.0, "Tau must be positive and non-zero" - self.tau = tau - self.use_bias = use_bias - - if name is not None: - self.name = name - - def energy(self, x): - """The predefined energy of a layer, defined for any lagrangian""" - if self.initializing(): - if self.use_bias: - self.bias = nn.initializers.normal(0.02)(tx.next_key(), self.shape) - x2 = x - self.bias if self.use_bias else x # Is this an issue? - - # When jitted, this is no slower than the optimized `@` vector multiplication - return jnp.multiply(self.g(x), x2).sum() - self.lagrangian(x2) - - def __call__(self, x): - """Alias for `self.energy`. Helps simplify treex's `.init` method""" - return self.energy(x) - - def activation(self, x): - """The derivative of the lagrangian is our activation or Gain function `g`. - - Defined to operate over input states `x` of shape `self.shape` - """ - if self.initializing(): - if self.use_bias: - self.bias = nn.initializers.normal(0.02)(tx.next_key(), self.shape) - x2 = x - self.bias if self.use_bias else x - return jax.grad(self.lagrangian)(x2) - - def g(self, x): - """Alias for `self.activation`""" - return self.activation(x) - - def init_state(self, - bs: int = None, # Batch size - rng=None): # If given, initialize states from a normal distribution with this key - """Initialize the states of this layer, with correct shape. - - If `bs` is provided, return tensor of shape (bs, *self.shape), otherwise return self.shape - By default, initialize layer state to all 0. - """ - layer_shape = self.shape if bs is None else (bs, *self.shape) - if rng is not None: - return jax.random.normal(rng, layer_shape) - return jnp.zeros(layer_shape) - -# %% ../nbs/01_layers.ipynb 20 -def MakeLayer(lagrangian_factory:Callable, - name:Optional[str]=None): # Name of the new class - """Hack to make it easy to create new layers from `Layer` utility class. - - `delegates` modifies the signature for all Layers. We want a different signature for each type of layer. - - So we redefine a local version of layer and delegate that for type inference. - """ - global Layer - - @delegates(lagrangian_factory, keep=True) - class Layer(Layer): - __doc__ = Layer.__doc__ - - out = partialler(Layer, lagrangian_factory, init_lagrangian=True, name=name) - out.__doc__ = Layer.__doc__ - - return out - -# %% ../nbs/01_layers.ipynb 21 -# Some reason, docstrings are not showing the new kwargs, and the docs for these are broken. -IdentityLayer = MakeLayer(LIdentity, "identity_layer") -RepuLayer = MakeLayer(LRepu, "repu_layer") -ReluLayer = MakeLayer(LRelu, "relu_layer") -SoftmaxLayer = MakeLayer(LSoftmax, "softmax_layer") -SigmoidLayer = MakeLayer(LSigmoid, "sigmoid_layer") -TanhLayer = MakeLayer(LTanh, "tanh_layer") -ExpLayer = MakeLayer(LExp, "exp_layer") -RexpLayer = MakeLayer(LRexp, "rexp_layer") -LayerNormLayer = MakeLayer(LLayerNorm, "layernorm_layer") diff --git a/hamux/registry.py b/hamux/registry.py deleted file mode 100644 index ebd277c..0000000 --- a/hamux/registry.py +++ /dev/null @@ -1,262 +0,0 @@ -# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/04_registry.ipynb. - -# %% auto 0 -__all__ = ['hn_relu', 'hn_repu5', 'hn_softmax', 'register_model', 'create_model', 'named_partial', 'simple_fwd', 'fwd_vec', - 'fwd_conv', 'hn', 'hn_relu_mnist', 'hn_relu_cifar', 'hn_repu5_mnist', 'hn_repu5_cifar', 'hn_softmax_mnist', - 'hn_softmax_cifar', 'conv_ham', 'conv_ham_avgpool_mnist', 'conv_ham_maxpool_mnist', 'conv_ham_avgpool_cifar', - 'conv_ham_maxpool_cifar', 'energy_attn', 'energy_attn_mnist', 'energy_attn_cifar'] - -# %% ../nbs/04_registry.ipynb 3 -import hamux as hmx -from typing import * -import functools as ft -from fastcore.utils import * -import jax -import jax.numpy as jnp -import jax.tree_util as jtu -import treex as tx -from einops import rearrange - -# %% ../nbs/04_registry.ipynb 7 -__MODELS = {} - -def register_model(fgen:Callable): # Function that returns a HAM with desired config - """Register a function that returns a model configuration factory function. - The name of the function acts as the retrieval key and must be unique across models""" - __MODELS[fgen.__name__] = fgen - return fgen - -def create_model(mname:str, # Retrieve this stored model name - *args, # Passed to retrieved factory function - **kwargs): # Passed to retrieved factory function - """Retrieve the model name from all registered models, passing `args` and `kwargs` to the factory function""" - assert mname in __MODELS, f"Model '{mname}' has not been registered" - return __MODELS[mname](*args, **kwargs) - -def named_partial(f, *args, new_name=None, order=None, **kwargs): - """Like `functools.partial` but also copies over function name and docstring. - - If new_name is not None, use that as the name - """ - fnew = ft.partial(f,*args,**kwargs) - fnew.__doc__ = f.__doc__ - name = new_name if new_name is not None else f.__name__ - fnew.__name__ = name - if order is not None: fnew.order=order - elif hasattr(f,'order'): fnew.order=f.order - return fnew - -# %% ../nbs/04_registry.ipynb 13 -def simple_fwd(model:hmx.HAM, # HAM where layer[0] is the image input and layer[-1] are the labels - x: jnp.ndarray, # Starting point for clamped layer[0] - depth: int, # Number of iterations for which to run the model - dt: float, # Step size through time - rng: Optional[jnp.ndarray]=None): # If provided, initialize states to random instead of 0 - """A simple version of the forward function for showing in the paper. - - All time constants `tau` are set to be 1 in our architecture, but this is variable - """ - # Initialize hidden states to our image - xs = model.init_states(x.shape[0], rng=rng) - xs[0] = jnp.array(x) - - # Masks allow us to clamp our visible data over time - masks = jtu.tree_map(lambda x: jnp.ones_like(x, dtype=jnp.int8), xs) - masks[0] = jnp.zeros_like(masks[0], dtype=jnp.int8) # Don't evolve images - - for i in range(depth): - updates = model.vupdates(xs) # Calculate the updates - xs = model.step( - xs, updates, dt=dt, masks=masks - ) # Add them to our current states - - # All labels have a softmax activation function as the last layer, spitting out probabilities - return model.layers[-1].g(xs[-1]) - -def fwd_vec(model:hmx.HAM, # HAM where layer[0] is the image input and layer[-1] are the labels - x: jnp.ndarray, # Starting point for clamped layer[0] - depth: int, # Number of iterations for which to run the model - dt: float, # Step size through time - rng: Optional[jnp.ndarray]=None): # If provided, initialize states to random instead of 0 - """Where the image input is vectorized""" - x = rearrange(x, "... c h w -> ... (c h w)") - return simple_fwd(model, x, depth, dt, rng) - -def fwd_conv(model:hmx.HAM, # HAM where layer[0] is the image input and layer[-1] are the labels - x: jnp.ndarray, # Starting point for clamped layer[0] - depth: int, # Number of iterations for which to run the model - dt: float, # Step size through time - rng: Optional[jnp.ndarray]=None): # If provided, initialize states to random instead of 0 - """Where the image input is kept as a 3 channel image""" - x = rearrange(x, "... c h w -> ... h w c") - return simple_fwd(model,x, depth,dt, rng) - - -# %% ../nbs/04_registry.ipynb 16 -@register_model -def hn(hidden_lagrangian:tx.Module, - img_shape: Tuple, # Shape of image input to model - label_shape: Tuple, # Shape of label probabilities,typically (NLABELS,) - nhid:int=1000, # Number of units in hidden layer - do_norm:bool=False): # If provided, enforce that all weights are standardized - """Create a Classical Hopfield Network that is intended to be applied on vectorized inputs""" - layers = [ - hmx.TanhLayer(img_shape), - hmx.SoftmaxLayer(label_shape), - ] - - synapses = [ - hmx.DenseMatrixSynapseWithHiddenLayer(nhid, hidden_lagrangian=hidden_lagrangian, do_norm=do_norm), - ] - - connections = [ - ((0, 1), 0), - ] - - ham = hmx.HAM(layers, synapses, connections) - - forward = ft.partial(fwd_vec, depth=4, dt=0.4) - - return ham, forward - -hn_relu = named_partial(hn, hmx.lagrangians.LRelu(), new_name="hn_relu") -register_model(hn_relu) - -hn_repu5 = named_partial(hn, hmx.lagrangians.LRepu(n=5), new_name="hn_repu5") -register_model(hn_repu5) - -hn_softmax = named_partial(hn, hmx.lagrangians.LSoftmax(), new_name="hn_softmax") -register_model(hn_softmax) - -@register_model -def hn_relu_mnist(nhid:int=1000): # Number of units in the single hidden layer - """Vectorized HN on flattened MNIST""" - return hn_relu(img_shape=(784,), label_shape=(10,), nhid=nhid) - -@register_model -def hn_relu_cifar(nhid:int=6000): # Number of units in the single hidden layer - """Vectorized HN on flattened CIFAR10""" - return hn_relu(img_shape=(3072,), label_shape=(10,), nhid=nhid) - -@register_model -def hn_repu5_mnist(nhid=1000): - """Vectorized DAM on flattened MNIST""" - return hn_repu5(img_shape=(784,), label_shape=(10,), nhid=nhid) - -@register_model -def hn_repu5_cifar(nhid=6000): - """Vectorized DAM on flattened CIFAR""" - return hn_repu5(img_shape=(3072,), label_shape=(10,), nhid=nhid) - -@register_model -def hn_softmax_mnist(nhid=1000): - return hn_softmax(img_shape=(784,), label_shape=(10,), nhid=nhid, do_norm=True) - -@register_model -def hn_softmax_cifar(nhid=6000): - return hn_softmax(img_shape=(3072,), label_shape=(10,), nhid=nhid, do_norm=True) - - -# %% ../nbs/04_registry.ipynb 21 -@register_model -def conv_ham(s1, s2, s3, pool_type, nhid=1000): - layers = [ - hmx.TanhLayer(s1, tau=1.0), - hmx.TanhLayer(s2, tau=1.0), - hmx.TanhLayer(s3, tau=1.0), - hmx.SoftmaxLayer((10,), tau=1.0), - ] - synapses = [ - hmx.ConvSynapseWithPool( - (4, 4), - strides=(2, 2), - padding=(2, 2), - pool_window=(2, 2), - pool_stride=(2, 2), - pool_type=pool_type, - ), - hmx.ConvSynapseWithPool( - (3, 3), - strides=(1, 1), - padding=(0, 0), - pool_window=(2, 2), - pool_stride=(2, 2), - pool_type=pool_type, - ), - hmx.DenseMatrixSynapseWithHiddenLayer(nhid), - ] - connections = [ - ((0, 1), 0), - ((1, 2), 1), - ((2, 3), 2) - ] - - ham = hmx.HAM(layers, synapses, connections) - - forward = ft.partial(fwd_conv, depth=7, dt=0.3) - return ham, forward - - -@register_model -def conv_ham_avgpool_mnist(nhid=1000): - return conv_ham((28, 28, 1), (7, 7, 64), (2, 2, 128), pool_type="avg", nhid=nhid) - - -@register_model -def conv_ham_maxpool_mnist(nhid=1000): - return conv_ham((28, 28, 1), (7, 7, 64), (2, 2, 128), pool_type="max", nhid=nhid) - - -@register_model -def conv_ham_avgpool_cifar(nhid=1000): - return conv_ham((32, 32, 3), (8, 8, 90), (3, 3, 180), pool_type="avg", nhid=nhid) - - -@register_model -def conv_ham_maxpool_cifar(nhid=1000): - return conv_ham((32, 32, 3), (8, 8, 90), (3, 3, 180), pool_type="max", nhid=nhid) - -# %% ../nbs/04_registry.ipynb 24 -@register_model -def energy_attn(s1, s2, nheads_self, nheads_cross): - layers = [ - hmx.TanhLayer(s1, tau=1.0), - hmx.TanhLayer(s2, tau=1.0, use_bias=True), - hmx.SoftmaxLayer((10,), tau=1.0), - ] - - synapses = [ - hmx.ConvSynapse((4, 4), strides=(4, 4), padding=(0, 0)), - hmx.AttentionSynapse(num_heads=nheads_cross, zspace_dim=64, stdinit=0.002), - hmx.AttentionSynapse(num_heads=nheads_self, zspace_dim=64, stdinit=0.002), - ] - - connections = [( - (0, 1), 0), - ((2, 1), 1), - ((1, 1), 2) - ] - ham = hmx.HAM(layers, synapses, connections) - forward = ft.partial(fwd_conv, depth=5, dt=0.4) - - return ham, forward - - -@register_model -def energy_attn_mnist(): - return energy_attn( - (28, 28, 1), - (7, 7, 128), - nheads_self=4, - nheads_cross=2, - ) - - -@register_model -def energy_attn_cifar(): - return energy_attn( - (32, 32, 3), - (8, 8, 224), - nheads_self=4, - nheads_cross=2, - ) diff --git a/hamux/synapses.py b/hamux/synapses.py deleted file mode 100644 index a03666f..0000000 --- a/hamux/synapses.py +++ /dev/null @@ -1,383 +0,0 @@ -# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/02_synapses.ipynb. - -# %% auto 0 -__all__ = ['Synapse', 'SimpleDenseSynapse', 'DenseSynapse', 'DenseTensorSynapseWithHiddenLayer', - 'DenseMatrixSynapseWithHiddenLayer', 'ConvSynapse', 'ConvSynapseWithPool', 'AttentionSynapse', - 'SelfAttentionSynapse', 'BinaryMixerSynapse'] - -# %% ../nbs/02_synapses.ipynb 6 -import jax -import jax.numpy as jnp -from typing import * -import treex as tx -from abc import ABC, abstractmethod -from flax import linen as nn -from .lagrangians import * -import functools as ft -from fastcore.meta import delegates -from fastcore.utils import * -from fastcore.basics import * -from string import ascii_letters -from flax.linen.pooling import max_pool, avg_pool -from einops import rearrange - -# %% ../nbs/02_synapses.ipynb 8 -class Synapse(tx.Module, ABC): - """The simple interface class for any synapse. Define an alignment function through `__call__` that returns a scalar. - - The energy is simply the negative of this function. - """ - - def energy(self, *gs): - return -self(*gs) - - @abstractmethod - def __call__(self, *gs): - """The alignment function of a synapse""" - pass - -# %% ../nbs/02_synapses.ipynb 11 -class SimpleDenseSynapse(Synapse): - """The simplest of dense synapses that connects two layers (with vectorized activations) together""" - W: jnp.ndarray = tx.Parameter.node() # treex's preferred way of declaring an attribute as a parameter - def __call__(self, g1, g2): - if self.initializing(): - self.W = nn.initializers.normal(0.02)(tx.next_key(), g1.shape + g2.shape) - return g1 @ self.W @ g2 - -# %% ../nbs/02_synapses.ipynb 15 -class DenseSynapse(Synapse): - """A dense synapse that aligns the representations of any number of `gs`. - - The one learnable parameter `W` is a tensor with a dimension for each connected layer. - In the case of 2 layers, this is the traditional learnable matrix synapse. - In cases `N>2` layers this is a new kind of layer where the learnable parameter is an N dimensional tensor. - - By default, this will flatten all inputs as needed to treat all activations as vectors. - - The number of layers we can align with this synapse is capped at the number of ranks that JAX stores (<255), - but you'll probably run out of memory first.. - """ - - W: jnp.ndarray = tx.Parameter.node() - stdinit: float = 0.02 - flatten_args: bool = True - - def __init__(self, stdinit: float = 0.02, flatten_args=True): - self.stdinit = stdinit - self.flatten_args = flatten_args - - def __call__(self, *gs): - if self.initializing(): - ndims_total = jnp.sum(jnp.array([len(g.shape) for g in gs])) - assert ( - ndims_total <= 52 - ), f"We are limited to english ASCII letters. We cannot connect more than 52 dimensions. Got {ndims_total} total dimensions." - if self.flatten_args: - gshapes = tuple([g_.size for g_ in gs]) - else: - gshapes = tuple([g_.shape[-1] for g_ in gs]) - self.W = nn.initializers.normal(self.stdinit)(tx.next_key(), gshapes) - if self.flatten_args: - gs = [g_.ravel() for g_ in gs] - abcs = ascii_letters[: len(gs)] - einsum_arg = ",".join([abcs, ",".join(abcs)]) + "->" - return jnp.einsum(einsum_arg, self.W, *gs) - else: - # Design the einsum to take letter positions corresponding to the - Wabcs = "" - gabcs = [] - i = 0 - for g in gs: - ndims = len(g.shape) - Wabcs += ascii_letters[(i - 1) + ndims] - gabcs.append(ascii_letters[i : i + ndims]) - i = i + ndims - einsum_arg = ",".join([Wabcs, ",".join(gabcs)]) + "->" - return jnp.einsum(einsum_arg, self.W, *gs) - -# %% ../nbs/02_synapses.ipynb 18 -class DenseTensorSynapseWithHiddenLayer(Synapse): - """A generalized DenseTensorSynapse that has a hidden lagrangian (non-linearity). - - We can specify a Lagrangian non-linearity for the hidden neuron layer with tau=0 and shape `(nhid,)`. - - The lagrangian can have its own learnable parameters, for example: - - ``` - from hamux.core.lagrangians import * - - syn = DenseTerminusSynapse(20, hidden_lagrangian=LSoftmax(beta_init=0.2)).init(jax.random.PRNGKey(0), tuple(gs)) - ``` - """ - - W: jnp.ndarray = tx.Parameter.node() - hidden_lagrangian: Optional[tx.Module] # An already initialized lagrangian function - - def __init__( - self, - nhid: int, - num_heads=1, - stdinit: float = 0.02, - hidden_lagrangian: tx.Module = LRelu(), - ): - self.nhid = nhid - self.stdinit = stdinit - self.num_heads = num_heads - self.hidden_lagrangian = hidden_lagrangian - - def __call__(self, *gs): - if self.initializing(): - assert ( - len(gs) <= 52 - ), "We are limited to english ASCII letters. We cannot connect more than 50 layers if you include our hidden layer and number of heads" - key = tx.next_key() - gshapes = (self.num_heads, self.nhid) + tuple([g_.size for g_ in gs]) - self.W = nn.initializers.normal(self.stdinit)(key, gshapes) - - gs = [g_.ravel() for g_ in gs] - abcs = ascii_letters[: len(gs)] - einsum_arg = ( - ",".join(["YZ" + abcs, ",".join(abcs)]) + "->YZ" - ) # We call the nhid dimension "Z" and number of heads "Y" - x = jnp.einsum(einsum_arg, self.W, *gs) - return self.hidden_lagrangian(x).sum() - -# %% ../nbs/02_synapses.ipynb 19 -class DenseMatrixSynapseWithHiddenLayer(Synapse): - """A modified DenseSynapse that has a hidden lagrangian (non-linearity). - - We can specify a Lagrangian non-linearity for the hidden neuron layer with tau=0 and shape `(nhid,)`. - - Unlike the DenseTensorSynapseWithHiddenLayer, treat layers as if they are concatenated on the same - visible layer dimension instead of giving each its own dimension of the tensor space. - """ - - Ws: List[jnp.ndarray] = tx.Parameter.node() - hidden_lagrangian: Optional[tx.Module] # An already initialized lagrangian function - - def __init__( - self, nhid: int, stdinit: float = 0.02, hidden_lagrangian: tx.Module = LRelu(), do_ravel=True, do_norm=False, - ): - self.nhid = nhid - self.stdinit = stdinit - self.hidden_lagrangian = hidden_lagrangian - self.do_ravel = do_ravel - self.do_norm = do_norm - - def __call__(self, *gs): - if self.initializing(): - def initw(g): - if self.do_ravel: - gsize = g.size - else: - gsize = g.shape[-1] - return nn.initializers.normal(self.stdinit)(tx.next_key(), (gsize, self.nhid)) - self.Ws = [initw(g_) for g_ in gs] - - if self.do_ravel: - gs = [g_.ravel() for g_ in gs] - if self.do_norm: - Ws = [W / jnp.sqrt((W**2).sum(0,keepdims=True)) for W in self.Ws] - else: - Ws = self.Ws - hid_state = jnp.stack([g @ W for (W, g) in zip(Ws, gs)]).sum(0) - return self.hidden_lagrangian(hid_state) - -# %% ../nbs/02_synapses.ipynb 20 -class ConvSynapse(Synapse): - """A convolutional, binary synapse. Can automatically detect the number of output features from the 2 layers it connects""" - - conv: tx.Conv - # Delegate arguments to conv EXCEPT the features_out, which we calculate from the output layer - - @delegates(tx.Conv) - def __init__(self, kernel_size: Union[int, Iterable[int]], **kwargs): - # assert pool_type in ["max", "avg"] - self.kernel_size = kernel_size - conv_kwargs = {"use_bias": False} - conv_kwargs.update(kwargs) - self.conv_kwargs = conv_kwargs - - def example_output(self, g1, features_out=1): - """Test the shape output of the convolutional layer. If unspecified, output features are 1""" - conv = tx.Conv(features_out, self.kernel_size, **self.conv_kwargs).init( - jax.random.PRNGKey(0), g1 - ) - return conv(g1) - - def __call__(self, g1, g2): - """The convolutional operation. g2 is assumed to be the "output" of the convolution""" - if self.initializing(): - features_out = g2.shape[-1] - self.conv = tx.Conv( - features_out, self.kernel_size, **self.conv_kwargs - ).init(tx.next_key(), g1) - return jnp.multiply(self.conv(g1), g2).sum() - -# %% ../nbs/02_synapses.ipynb 22 -class ConvSynapseWithPool(Synapse): - """A convolutional, binary synapse. Can automatically detect the number of output features from the 2 layers it connects""" - - conv: tx.Conv - # Delegate arguments to conv EXCEPT the features_out, which we calculate from the output layer - - @delegates(tx.Conv) - def __init__( - self, - kernel_size: Union[int, Iterable[int]], - pool_window=(5, 5), - pool_stride=(2, 2), - pool_type="avg", - **kwargs, - ): - # assert pool_type in ["max", "avg"] - self.kernel_size = kernel_size - self.conv_kwargs = kwargs - self.pool_window = pool_window - self.pool_stride = pool_stride - self.pool_type = pool_type - - self.pooler = max_pool if self.pool_type == "max" else avg_pool - # self.conv = None - - def example_output(self, g1, features_out=1): - """Test the shape output of the convolutional layer. If unspecified, output features are 1""" - conv = tx.Conv(features_out, self.kernel_size, **self.conv_kwargs).init( - jax.random.PRNGKey(0), g1 - ) - output = self.pooler(conv(g1), self.pool_window, strides=self.pool_stride) - return output - - def __call__(self, g1, g2): - """The convolutional operation. g2 is assumed to be the "output" of the convolution""" - if self.initializing(): - features_out = g2.shape[-1] - self.conv = tx.Conv( - features_out, self.kernel_size, **self.conv_kwargs - ).init(tx.next_key(), g1) - output = self.pooler(self.conv(g1), self.pool_window, strides=self.pool_stride) - return jnp.multiply(output, g2).sum() - - -# %% ../nbs/02_synapses.ipynb 24 -class AttentionSynapse(Synapse): - """A generalized synapse of quadratic order, whose update rule looks very similar to the Attention operation of Transformers. - - We can specify any Lagrangian non-linearity for the hidden neuron layer (which operates with tau=0), but we default to the Softmax Lagrangian. - - To replicate similar configuration to the famous BERT-base models and "Attention is all you need" paper: - - ``` - zspace = 64 - syn = AttentionSynapse(zspace_dim=zspace, num_heads=12, hidden_lagrangian=LSoftmax(beta=1/jnp.sqrt(zspace))) - ``` - - Connecting two layers of shapes: ((Nq, Dq), (Nk, Dk)) and layernorm lagrangians - """ - - Wk: jnp.ndarray = tx.Parameter.node() - Wq: jnp.ndarray = tx.Parameter.node() - hidden_lagrangian: Optional[tx.Module] # An already initialized lagrangian function - qk_norm: Optional[tx.Module] - - def __init__( - self, - num_heads: int = 1, - zspace_dim: int = 64, - stdinit: float = 0.02, - hidden_lagrangian: tx.Module = LSoftmax(), - do_qk_norm: bool = False, - ): - self.zspace_dim = zspace_dim - self.num_heads = num_heads - self.stdinit = stdinit - self.hidden_lagrangian = hidden_lagrangian - self.do_qk_norm = do_qk_norm - - def __call__(self, gq, gk): - """Align the queries in gq with the keys in gk""" - if self.initializing(): - self.Wq = nn.initializers.normal(self.stdinit)( - tx.next_key(), (gq.shape[-1], self.num_heads, self.zspace_dim) - ) - self.Wk = nn.initializers.normal(self.stdinit)( - tx.next_key(), (gk.shape[-1], self.num_heads, self.zspace_dim) - ) - if self.do_qk_norm: - self.qk_norm = tx.LayerNorm().init( - tx.next_key(), jnp.ones(self.zspace_dim) - ) - - if len(gq.shape) == 1: - gq = gq[..., None, :] - if len(gk.shape) == 1: - gk = gk[..., None, :] - if len(gq.shape) > 2: - gq = rearrange(gq, "... d -> (...) d") - if len(gk.shape) > 2: - gk = rearrange(gk, "... d -> (...) d") - Q = jnp.einsum("qd,dhz->qhz", gq, self.Wq) - K = jnp.einsum("kd,dhz->khz", gk, self.Wk) - # QK = jnp.einsum("qhz,khz->hqk", Q, K) - if self.do_qk_norm: - Q = self.qk_norm(Q) - K = self.qk_norm(K) - QK = jnp.einsum("qhz,khz->hqk", Q, K) - - # print("MAX QK: ", QK.max()) - # print("MIN QK: ", QK.min()) - # , QK.min(), gk.max(), gq.max()) - attn = self.hidden_lagrangian(QK) # h,q - return attn.sum() - - -class SelfAttentionSynapse(AttentionSynapse): - """A special case of the AttentionSynapse where both inputs are of the same layer""" - - def __call__(self, g): - return super().__call__(g, g) - - -class BinaryMixerSynapse(Synapse): - """A generalized binary synapse of quadratic order. This synapse is very similar to the Attention synapse but uses a single - weight matrix instead of a query and key matrix. - - We can specify any Lagrangian non-linearity for the hidden neuron layer (which operates with tau=0), but we default to the Softmax Lagrangian. - - """ - - W: jnp.ndarray = tx.Parameter.node() - hidden_lagrangian: Optional[tx.Module] # An already initialized lagrangian function - - def __init__( - self, - num_heads: int = 1, - zspace_dim: int = 64, - stdinit: float = 0.02, - hidden_lagrangian: tx.Module = LSoftmax(), - ): - self.num_heads = num_heads - self.zspace_dim=zspace_dim - self.stdinit = stdinit - self.hidden_lagrangian = hidden_lagrangian - - def __call__(self, ga, gb): - """Align the activations ga with gb""" - if self.initializing(): - self.W = nn.initializers.normal(self.stdinit)( - tx.next_key(), (self.num_heads, self.zspace_dim, ga.shape[-1], gb.shape[-1]) - ) - - if len(ga.shape) == 1: - ga = ga[...,None,:] - if len(gb.shape) == 1: - gb = gb[...,None,:] - if len(ga.shape) > 2: - ga = rearrange(ga, "... d -> (...) d") - if len(gb.shape) > 2: - gb = rearrange(gb, "... d -> (...) d") - - AB = jnp.einsum("hzab,...a,...b->hz", self.W, ga, gb) - attn = self.hidden_lagrangian(AB) # h - return attn.sum() diff --git a/hamux/tfjs_helpers.py b/hamux/tfjs_helpers.py deleted file mode 100644 index b04b711..0000000 --- a/hamux/tfjs_helpers.py +++ /dev/null @@ -1,129 +0,0 @@ -# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/05_tfjs.ipynb. - -# %% auto 0 -__all__ = ['DType', 'PolyShape', 'Array', 'convert_jax'] - -# %% ../nbs/05_tfjs.ipynb 5 -import tensorflowjs as tfjs -import tensorflow as tf -import tempfile -from tensorflowjs.converters import tf_saved_model_conversion_v2 as saved_model_conversion -from jax.experimental import jax2tf -from typing import * - -# %% ../nbs/05_tfjs.ipynb 7 -DType = Any -PolyShape = jax2tf.shape_poly.PolyShape -Array = Any -_TF_SERVING_KEY = tf.saved_model.DEFAULT_SERVING_SIGNATURE_DEF_KEY - -# %% ../nbs/05_tfjs.ipynb 8 -class _ReusableSavedModelWrapper(tf.train.Checkpoint): - """Wraps a function and its parameters for saving to a SavedModel. - Implements the interface described at - https://www.tensorflow.org/hub/reusable_saved_models. - """ - - def __init__(self, tf_graph, param_vars): - """Args: - tf_graph: a tf.function taking one argument (the inputs), which can be - be tuples/lists/dictionaries of np.ndarray or tensors. The function - may have references to the tf.Variables in `param_vars`. - param_vars: the parameters, as tuples/lists/dictionaries of tf.Variable, - to be saved as the variables of the SavedModel. - """ - super().__init__() - # Implement the interface from https://www.tensorflow.org/hub/reusable_saved_models - self.variables = tf.nest.flatten(param_vars) - self.trainable_variables = [v for v in self.variables if v.trainable] - # If you intend to prescribe regularization terms for users of the model, - # add them as @tf.functions with no inputs to this list. Else drop this. - self.regularization_losses = [] - self.__call__ = tf_graph - -# %% ../nbs/05_tfjs.ipynb 9 -def convert_jax( - apply_fn: Callable[..., Any], - *, - input_signatures: Sequence[Tuple[Sequence[Union[int, None]], DType]], - model_dir: str, - polymorphic_shapes: Optional[Sequence[Union[str, PolyShape]]] = None): - """Converts a JAX function `apply_fn` to a TensorflowJS model. - Works with `functools.partial` style models if we don't need to access the variables in the frontend. - - Example usage for an arbitrary function: - - ``` - import functools as ft - ... - def predict_fn(model, input): - return model.predict(input) - - fn = ft.partial(predict_fn, trained_model) - - convert_jax( - apply_fn=fn, - input_signatures=[((D1, D2,), np.float32)], - model_dir=tfjs_model_dir) - ``` - - Note that when using dynamic shapes, an additional argument - `polymorphic_shapes` should be provided specifying values for the dynamic - ("polymorphic") dimensions). See here for more details: - https://github.com/google/jax/tree/main/jax/experimental/jax2tf#shape-polymorphic-conversion - - This is an adaption of the original implementation in jax2tf here: - https://github.com/google/jax/blob/main/jax/experimental/jax2tf/examples/saved_model_lib.py - - Arguments: - apply_fn: A JAX function that has one or more arguments, of which the first - argument are the model parameters. This function typically is the forward - pass of the network (e.g., `Module.apply()` in Flax). - input_signatures: the input signatures for the second and remaining - arguments to `apply_fn` (the input). A signature must be a - `tensorflow.TensorSpec` instance, or a (nested) tuple/list/dictionary - thereof with a structure matching the second argument of `apply_fn`. - model_dir: Directory where the TensorflowJS model will be written to. - polymorphic_shapes: If given then it will be used as the - `polymorphic_shapes` argument for the second parameter of `apply_fn`. In - this case, a single `input_signatures` is supported, and should have - `None` in the polymorphic (dynamic) dimensions. - """ - - tf_fn = jax2tf.convert( - apply_fn, - # Gradients must be included as 'PreventGradient' is not supported. - with_gradient=True, - polymorphic_shapes=polymorphic_shapes, - # Do not use TFXLA Ops because these aren't supported by TFjs, but use - # workarounds instead. More information: - # https://github.com/google/jax/tree/main/jax/experimental/jax2tf#tensorflow-xla-ops - enable_xla=False) - - # Create tf.Variables for the parameters. If you want more useful variable - # names, you can use `tree.map_structure_with_path` from the `dm-tree` - # package. - # For HAMUX we presume that the variables are inaccessible, for now - param_vars = [] - # param_vars = tf.nest.map_structure( - # lambda param: tf.Variable(param, trainable=False), params) - # Do not use TF's jit compilation on the function. - tf_graph = tf.function( - lambda *xs: tf_fn(*xs), autograph=False, jit_compile=False) - - # This signature is needed for TensorFlow Serving use. - signatures = { - _TF_SERVING_KEY: tf_graph.get_concrete_function(*input_signatures) - } - - wrapper = _ReusableSavedModelWrapper(tf_graph, param_vars) - saved_model_options = tf.saved_model.SaveOptions( - experimental_custom_gradients=True) - - with tempfile.TemporaryDirectory() as saved_model_dir: - tf.saved_model.save( - wrapper, - saved_model_dir, - signatures=signatures, - options=saved_model_options) - saved_model_conversion.convert_tf_saved_model(saved_model_dir, model_dir, skip_op_check=True) diff --git a/hamux/utils.py b/hamux/utils.py deleted file mode 100644 index 5d2e691..0000000 --- a/hamux/utils.py +++ /dev/null @@ -1,74 +0,0 @@ -import pickle -from pathlib import Path -from typing import Union, Any -from copy import deepcopy -import flax.traverse_util as ftu -from flax.core import freeze -from loguru import logger -import types - -suffixes = ['.pckl', ".pickle", ".pkl"] - -def pytree_save(data: Any, path: Union[str, Path], overwrite: bool = False): - path = Path(path) - if path.suffix not in suffixes: - path = path.with_suffix(suffixes[0]) - path.parent.mkdir(parents=True, exist_ok=True) - if path.exists(): - if overwrite: - path.unlink() - else: - raise RuntimeError(f'File {path} already exists.') - with open(path, 'wb') as file: - pickle.dump(data, file) - - -def pytree_load(path: Union[str, Path]) -> Any: - path = Path(path) - if not path.is_file(): - raise ValueError(f'Not a file: {path}') - if path.suffix not in suffixes: - raise ValueError(f'Not a pickle file: {path}') - with open(path, 'rb') as file: - data = pickle.load(file) - return data - -def to_pickleable(x): - if callable(x): - return x.__name__ - return x - - -def align_with_state_dict(list_curr, list_new): - """Load the saved list into the current list. - - Important for loading checkpoints because our HAM is composed of a list of layers and list of synapses - """ - list_curr = deepcopy(list_curr) - frozen_list_new = [ftu.flatten_dict(freeze(mod)) for mod in list_new] - for myobj, newobj in zip(list_curr, frozen_list_new): - for ktup, value in newobj.items(): - item = myobj - for k in ktup[:-1]: - try: - item = getattr(item, k) - except AttributeError as e: - logger.debug(f"Intermediate access key `{k}` in state dict but not in model. Skipping") - - - if "shape" == ktup[-1]: - # assign to a tuple since saving turns tuples into lists - value = tuple(value) - try: - oldval = getattr(item, ktup[-1]) - if isinstance(value, str) and isinstance(oldval, types.FunctionType): - logger.debug(f"New value is a string, but old value is a callable. Setting {ktup[-1]} in new object to be the callable") - value = oldval - elif isinstance(value, list) and isinstance(oldval, tuple): - logger.debug(f"New value is a list, but old value is a tuple. Setting {ktup[-1]} in new object to be a tuple") - value = tuple(value) - - setattr(item, ktup[-1], value) - except AttributeError as e: - logger.debug(f"Leaf key `{ktup[-1]}` in state dict but not in model. Skipping") - return list_curr \ No newline at end of file diff --git a/nbs/.gitignore b/nbs/.gitignore deleted file mode 100644 index 075b254..0000000 --- a/nbs/.gitignore +++ /dev/null @@ -1 +0,0 @@ -/.quarto/ diff --git a/nbs/00_core.qmd b/nbs/00_core.qmd new file mode 100644 index 0000000..df6bc24 --- /dev/null +++ b/nbs/00_core.qmd @@ -0,0 +1,773 @@ +# Building HAMUX +> The building blocks of energy-based Associative Memory + +We develop a *modular energy* perspective of Associative Memories where the energy of any model from this family can be decomposed into standardized components: [**neuron layers**](#sec-neurons) that encode dynamic variables, and [**hypersynapses**](#sec-hypersynapses) that encode their interactions. + +**The total energy of the system is the sum of the individual component energies subtracted by the energies of all the layers and all the interactions between those layers.** + +In computer science terms, neurons and synapses form a [**hypergraph**](https://en.wikipedia.org/wiki/Hypergraph), where each neuron layer is a node and each hypersynapse is a hyperedge. + +This framework of energy-based building blocks for memory not only clarifies how existing methods for building Associative Memories relate to each other (e.g., the Classical Hopfield Network [@hopfield1982neural, @hopfield1984Neurons], Dense Associative Memory [@krotov2016dense]), but it also provides a systematic language for designing new architectures (e.g., Energy Transformers [@hoover2024energy], Neuron-Astrocyte Networks [@kozachkov2023neuron]). + +We begin by introducing the building blocks of Associative Memory: [**neurons**](#sec-neurons) and [**hypersynapses**](#sec-hypersynapses). + +# Neurons {#sec-neurons} +> Neurons turn [Lagrangians](./01_lagrangians.ipynb) into the dynamic building blocks of memory. + +:::{.callout-note} +## TL;DR + +1. A *neuron* is a fancy term to describe the dynamic (fast moving) variables in an associative memory. +2. Every neuron has an internal state $\mathbf{x}$ that evolves over time and an activation $\hat{\mathbf{x}}$ that affects the rest of the network. +3. In the complete hypergraph of Associative Memory, our neurons are the *nodes* while our [hypersynapses](#sec-hypersynapses) are the *hyperedges* (since a synapse can connect more than two nodes, they cannot be regular "edges"). +4. A neuron is just a Lagrangian assigned to a tensor of data. +::: + +```{python} +#| default_exp core +``` + +```{python} +#| export +#| hide +from typing import * +import equinox as eqx +import jax, jax.numpy as jnp, jax.random as jr, jax.tree_util as jtu +from fastcore.basics import * +import functools as ft +``` + +```{python} +#| hide +from nbdev import show_doc +from fastcore.test import * +from warnings import warn +``` + +![A neuron layer is a Lagrangian function on top of data, where the Lagrangian defines the activations of that neuron](figures/NeuronOverview.png){width=350px} + +A **neuron layer** (node of the Associative Memory) is a fancy term to describe the dynamic variables in AM. Each neuron layer has an **internal state** $\mathbf{x}$ which evolves over time and an **activation** $\hat{\mathbf{x}}$ that forwards a signal to the rest of the network. Think of neurons like the *activation functions* of standard neural networks, where $\mathbf{x}$ are the *pre-activations* and $\hat{\mathbf{x}}$ (the outputs) are the *activations* e.g., $\hat{\mathbf{x}} = \texttt{ReLU}(\mathbf{x})$. + + +In order to define neuron layer's energy, AMs employ two mathematical tools from physics: convex **Lagrangian functions** and the **Legendre transform**. For each neuron layer, we define a convex, scalar-valued Lagrangian $\mathcal{L}_x(\mathbf{x})$. The Legendre transform $\mathcal{T}$ of this Lagrangian produces the dual variable $\hat{\mathbf{x}}$ (our activations) and the dual energy $E_x(\hat{\mathbf{x}})$ (our new energy) as in: + +$$ +\begin{align} + \hat{\mathbf{x}} &= \nabla \mathcal{L}_x(\mathbf{x}) \quad \text{(activation function)} \\ + E_x(\hat{\mathbf{x}}) = \mathcal{T}(\mathcal{L}_x) &= \langle \mathbf{x}, \hat{\mathbf{x}} \rangle - \mathcal{L}_x(\mathbf{x}) \quad \text{(dual energy)} +\end{align} +$${#eq-neuron-legendre-transform} + +where $\langle \cdot, \cdot \rangle$ is the element-wise inner product. Because $\mathcal{L}_x$ is convex, the Jacobian of the activations $\frac{\partial \hat{\mathbf{x}}}{\partial \mathbf{x}} = \nabla^2 \mathcal{L}_x(\mathbf{x})$ (i.e., the Hessian of the Lagrangian) is positive definite. + + +:::{.callout-tip} +## Notational conventions + +There are lots of named components inside the neuron layer. As a notational convention, each neuron layer is identified by a single letter (e.g., $\mathsf{X}$ or $\mathsf{Y}$). We say a neuron layer $\mathsf{X}$ has a internal state $\mathbf{x} \in \hat{\mathcal{X}}$ and Lagrangian $\mathcal{L}_x(\mathbf{x})$, alongside an activation $\hat{\mathbf{x}} \in \hat{\mathcal{X}}$ and total energy $E_x(\hat{\mathbf{x}})$ constrained through the Legendre transform of the Lagrangian. Meanwhile, neuron layer $\mathsf{Y}$ has a internal state $\mathbf{y} \in \mathcal{Y}$ and Lagrangian $\mathcal{L}_y(\mathbf{y})$, alongside an activation $\hat{\mathbf{y}} \in \hat{\mathcal{Y}}$ and total energy $E_y(\hat{\mathbf{y}})$. + +Because it is often nice to think of the activations as being a non-linear function of the internal states, we can also write $\hat{\mathbf{x}} = \sigma_x(\mathbf{x})$, where $\sigma_x(\cdot) := \nabla \mathcal{L}_x (\cdot)$. +::: + +The dual energy $E_x(\hat{\mathbf{x}})$ has another nice property: *its gradient equals the internal states*. Thus, when we minimize the energy of our neurons (in the absence of any other signal), we observe exponential decay. This is nice to keep the dynamic behavior of our system bounded and well-behaved, especially for very large values of $\mathbf{x}$. + +$$ +\frac{d \mathbf{x}}{dt} = - \nabla_{\hat{\mathbf{x}}} E_x(\hat{\mathbf{x}}) = - \mathbf{x}. +$${#eq-exponential-decay} + +## Neurons as Code {#sec-neuron-implementation} + +The methods to implement neurons are remarkably simple: + +```{python} +#| exports +class NeuronLayer(eqx.Module): + """Neuron layers represent dynamic variables that evolve during inference (i.e., memory retrieval/error correction)""" + lagrangian: Callable # The scalar-valued Lagrangian function: x |-> R + shape: Tuple[int] # The shape of the neuron layer +``` + +Remember that, at its core, a `NeuronLayer` object is nothing more than a Lagrangian (see [example Lagrangians](./01_lagrangians.ipynb) for examples) function on top of (shaped) data. All the other methods of the `NeuronLayer` class just provide conveniences on top of this core functionality. + +```{python} +#| exports +@patch +def activations(self: NeuronLayer, x): + """Use autograd to compute the activations of the neuron layer from the Lagrangian""" + return jax.grad(self.lagrangian)(x) +``` + +The `NeuronLayer.activations` is the gradient of the Lagrangian with respect to the states. This is easily computed via jax autograd. + +:::{.callout-note collapse="true"} + +## Test the activations + +For example, we can test the activations of a few different Lagrangians. + +```{python} +from hamux.lagrangians import lagr_relu, lagr_softmax, lagr_sigmoid, lagr_identity +from pprint import pp +``` + +```{python} +D = 10 + +# Identity activation +nn = NeuronLayer(lagrangian=lambda x: jnp.sum(0.5 * x**2), shape=(D,)) # Identity activation +xtest = jr.normal(jr.key(0), (D,)) +assert jnp.allclose(nn.activations(xtest), xtest) + +# ReLU activation +nn = NeuronLayer(lagrangian=lagr_relu, shape=(D,)) +xtest = jr.normal(jr.key(1), (D,)) +assert jnp.allclose(nn.activations(xtest), jnp.maximum(0, xtest)) + +# Softmax activation +nn = NeuronLayer(lagrangian=lagr_softmax, shape=(D,)) +xtest = jr.normal(jr.key(2), (D,)) +assert jnp.allclose(nn.activations(xtest), jax.nn.softmax(xtest)) +``` + +::: + + +```{python} +#| exports +@patch +def init(self: NeuronLayer, bs: Optional[int] = None): + """Return an empty initial neuron state""" + if bs is None or bs == 0: return jnp.zeros(self.shape) # No batch dimension + return jnp.zeros((bs, *self.shape)) +``` + +The `NeuronLayer.init` method is a convenience method that initializes an empty collection of neuron layer states. We generally want to populate this state with values from some piece of data. + +It's used like: + +```{python} +D = 784 # e.g., rasterized MNIST image size +nn = NeuronLayer(lagrangian=lambda x: 0.5 * x**2, shape=(D,)) +x_unbatched = nn.init() +print("Unbatched shape:", x_unbatched.shape) +x_batched = nn.init(bs=2) +print("Batched shape:", x_batched.shape) +``` + +## Legendre transform and Neuron Energy + +The energy is the Legendre transform of the Lagrangian. Consider some scalar-valued function $F: \mathcal{X} \mapsto \mathbb{R}$ for which we want to compute it's dual representation $\hat{F}: \hat{\mathcal{X}} \mapsto \mathbb{R}$ under the Legendre Transform. The Legendre transform $\mathcal{T}$ of $F$ transforms both the function $F$ and its argument $\mathbf{x}$ into a dual formulation $\hat{F}$ and $\hat{\mathbf{x}} = \sigma(\mathbf{x}) = \nabla F(\mathbf{x})$. The transform is defined as: + +$$ +\hat{F}(\hat{\mathbf{x}}) = \langle \mathbf{x}, \hat{\mathbf{x}} \rangle - F(\mathbf{x}). +$$ + +Note that $\hat{F}$ is only a function of $\hat{\mathbf{x}}$ ($\mathbf{x}$ is computed as $\mathbf{x} = \sigma^{(-1)}(\hat{\mathbf{x}})$. You can confirm this for yourself by trying to compute $\frac{\partial \hat{F}}{\partial \mathbf{x}}$ and checking that the answer is $0$). + +The code for the Legendre transform is easy to implement in jax as a higher order function. We'll assume that we always have the original variable $\mathbf{x}$ so that we don't need to compute $\sigma^{(-1)}$. + + +```{python} +#| exports +def legendre_transform( + F: Callable # The function to transform + ): + "Transform scalar F(x) into the dual Fhat(xhat, x) using the Legendre transform" + + # We define custom gradient rules to give jax some autograd shortcuts + @jax.custom_jvp + def Fhat(xhat, x): return jnp.multiply(xhat, x).sum() - F(x) + + @Fhat.defjvp + def Fhat_jvp(primals, tangents): + (xhat, x), (dxhat, dx) = primals, tangents + o, do = Fhat(xhat, x), jnp.multiply(x, dxhat).sum() + return o, do + + return Fhat +``` + +:::{.callout-note collapse="true"} + +## Test the Legendre transform + +Let's test if the `legendre_transform` automatic gradients are what we expect: + +```{python} +#| code-fold: true +#| code-summary: Test the Legendre transform +x = jnp.array([1., 2, 3]) +F = lagr_sigmoid +g = jax.nn.sigmoid(x) +Fhat = legendre_transform(F) + +assert jnp.allclose(jax.grad(Fhat)(g, x), x) +assert jnp.all(jax.grad(Fhat, argnums=1)(g, x) == 0.) + +x = jnp.array([1., 2, 3]) +F = lagr_identity +g = x +Fhat = legendre_transform(F) + +assert jnp.allclose(jax.grad(Fhat)(g, x), x) +assert jnp.all(jax.grad(Fhat, argnums=1)(g, x) == 0.) +``` +::: + +The Legendre transform is the final piece of the puzzle to describe the energy of a neuron layer. + + +```{python} +#| exports +@patch +def energy(self: NeuronLayer, xhat, x): + """The energy of the neuron layer is the Legendre transform of the Lagrangian""" + return legendre_transform(self.lagrangian)(xhat, x) +``` + +The energy is the Legendre transform of the Lagrangian: + +$$ +E_\text{neuron} = \langle \mathbf{x}, \hat{\mathbf{x}} \rangle - \mathcal{L}_x(\mathbf{x}) +$$ + +```{python} +#| code-fold: true +#| code-summary: Test the energy +nn = NeuronLayer(lagrangian=lagr_sigmoid, shape=(3,)) +x = jnp.array([1., 2, 3]) +xhat = nn.activations(x) +assert jnp.allclose(jax.grad(nn.energy, argnums=0)(xhat, x), x) +assert jnp.allclose(jax.grad(nn.energy, argnums=1)(xhat, x), 0.) +``` + +:::{.callout-note collapse="true"} + +## Additional methods + +We alias a few of the methods for convenience. + +```{python} +#| exports +NeuronLayer.sigma = NeuronLayer.activations +NeuronLayer.E = NeuronLayer.energy +``` + +And wrap a few other python conveniences. + +```{python} +#| export +@patch +def __repr__(self: NeuronLayer): + """Look nice when inspected""" + return f"NeuronLayer(lagrangian={self.lagrangian}, shape={self.shape})" + +@patch +def __post_init__(self: NeuronLayer): + """Ensure the neuron shape is a tuple""" + print("Post init") + if isinstance(self.shape, int): self.shape = (self.shape,) +``` +::: + +# Hypersynapses {#sec-hypersynapses} +> Hypersynapses modulate signals between one or more neuron layers. + +![A hypersynapse is a scalar valued energy function defined on top of the activations of connected neuron layers](figures/HypersynapseOverview.png){width=400px} + +The activations of one `NeuronLayer` are sent to other neurons via communication channels called **hypersynapses**. At its most general, a hypersynapse is a scalar valued energy function defined on top of the activations of connected neuron layers. For example, a hypersynapse connecting neuron layers $\mathsf{X}$ and $\mathsf{Y}$ has an **interaction energy** $E_{xy}(\hat{\mathbf{x}}, \hat{\mathbf{y}}; \mathbf{\Xi})$, where $\mathbf{\Xi}$ represents the **synaptic weights** or learnable parameters. + +$E_{xy}(\hat{\mathbf{x}}, \hat{\mathbf{y}}; \mathbf{\Xi})$ encodes the desired relationship between activations $\hat{\mathbf{x}}$ and $\hat{\mathbf{y}}$. When this energy is low, the activations satisfy the relationship encoded by the synaptic weights $\mathbf{\Xi}$. +During energy minimization, the system adjusts the activations to reduce all energy terms, which means synapses effectively *pull* the connected neuron layers toward configurations encoded in the parameters that minimize their interaction energy. + +:::{.callout-note} +## Hypersynapse notation conventions + +For synapses connecting multiple layers, we subscript with the identifiers of all connected layers. For example: + +- $E_{xy}$ --- synapse connecting layers $\mathsf{X}$ and $\mathsf{Y}$ +- $E_{xyz}$ --- synapse connecting layers $\mathsf{X}$, $\mathsf{Y}$, and $\mathsf{Z}$. +- $E_{xyz\ldots}$ --- synapses connecting more than three layers are possible, but rare. + +However, synapses can also connect a layer to itself (self-connections). To avoid confusion with neuron layer energy $E_x$, we use curly brackets for synaptic self-connections. For example, $E_{\{x\}}$ represents the interaction energy of a synapse that connects layer $\mathsf{X}$ to itself. +::: + + +### How biological are hypersynapses? + +Hypersynapses in `hamux` differ from biological synapses in two fundamental ways: + +- **Hypersynapses can connect any number of layers simultaneously**, while biological synapses connect only two neurons. This officially makes hypersynapses "hyperedges" in graph theory terms. +- **Hypersynapses are undirected**, meaning that all connected layers influence each other bidirectionally during energy minimization. Meanwhile, biological synapses are unidirectional, meaning signal flows from a presynaptic to postsynaptic neuron. + +Because of these differences, we choose the distinct term "hypersynapses" to distinguish them from biological synapses. + +![**Hypersynapses are represented as undirected (hyper)edges in a hypergraph.** Shown is an example pairwise synapse, which is a single energy function $E_{xy}(\hat{\mathbf{x}}, \hat{\mathbf{y}}; \mathbf{\Xi})$ defined on the activations $\hat{\mathbf{x}}$ and $\hat{\mathbf{y}}$ from connected nodes, which necessarily propagate signal to both connected nodes. Here, \textit{signal} is defined as the negative gradient of the interaction energy {w.r.t.} the connected layer's activations (e.g., layer $\mathsf{X}$ receives signal $\mathcal{I}_x = -\nabla_{\hat{\mathbf{x}}} E_{xy}(\hat{\mathbf{x}}, \hat{\mathbf{y}}; \mathbf{\Xi})$). This is in contrast to biological synapses which are directional and only propagate signal in one direction from layer $\mathsf{X}$ to $\mathsf{Y}$, needing a separate synapse to bring information back from $\mathsf{Y}$ to $\mathsf{X}$](figures/hamux-undirected-synapses.png){width=400px} + +The undirected nature of hypersynapses fundamentally distinguishes AM from traditional neural networks. Whereas feed-forward networks follow a directed computational graph with clear input-to-output flow, AMs have no inherent concept of "forward" or "backward" directions. All connected layers influence each other bidirectionally during energy minimization, with information propagating from deeper layers to shallower layers as readily as the other way around. + + +Unlike the `NeuronLayer`'s energies, the interaction energies of the hypersynapses are completely unconstrained: *any function* that takes activations as input and returns a scalar is admissable and will have well-behaved dynamics. +The interaction energy of a synapse may choose to introduce its own non-linearities beyond those handled by the neuron layers. When this occurs, the energy minimization dynamics must compute gradients through these "synaptic non-linearities", unlike the case where all non-linearities are abstracted into the `NeuronLayer` Lagrangians. + +:::{.callout-note} +## TL;DR + +1. A *hypersynapse* describes the "strain energy" between the activations of one or more neuron layers. The lower that energy, the more aligned the activations. +2. In the complete hypergraph of Associative Memory, our neurons are the nodes and our hypersynapses are the *hyperedges*. +::: + + +## Hypersynapse implementation {#sec-hypersynapse-implementation} +> **Hypersynapses are just callable `equinox.Module` with trainable parameters.** Any differentiable, scalar-valued function, implemented in a `__call__` method, will work. + +That's it. Many things can be hypersynapse energies. Here are two examples that may look familiar to those with a background in ML. + +```{python} +#| exports +class LinearSynapse(eqx.Module): + """The energy synapse corrolary of the linear layer in standard neural networks""" + W: jax.Array + def __call__(self, xhat1:jax.Array, xhat2:jax.Array): + "Compute the interaction energy between activations `xhat1` and `xhat2`." + # Best to use batch-dim agnostic operations + return -jnp.einsum("...c,...d,cd->...", xhat1, xhat2, self.W) + + @classmethod + def rand_init(cls, key: jax.Array, x1_dim: int, x2_dim: int): + Winit = 0.02 * jr.normal(key, (x1_dim, x2_dim)) + return cls(W=Winit) +``` + +Take the gradient w.r.t. either of the input activations and you have a linear layer. + +```{python} +syn = LinearSynapse.rand_init(jr.key(0), 10, 20) +xhat1 = jr.normal(jr.key(1), (10,)) +xhat2 = jr.normal(jr.key(2), (20,)) + +print("Energy:", syn(xhat1, xhat2)) +ff_compute = -jnp.einsum("...c,cd->...d", xhat1, syn.W) +fb_compute = -jnp.einsum("...d,cd->...c", xhat2, syn.W) +assert jnp.allclose(jax.grad(syn, argnums=1)(xhat1, xhat2), ff_compute) +assert jnp.allclose(jax.grad(syn, argnums=0)(xhat1, xhat2), fb_compute) +``` + +*The linear layer is trying to align the activations of its two connected layers, and taking the gradient w.r.t. either of the activations gives you the standard linear layer output.* + +We may want to add biases to the network. We can do so in two ways. + +```{python} +#| export +class LinearSynapseWithBias(eqx.Module): + """A linear synapse with a bias""" + W: jax.Array + b: jax.Array + def __call__(self, xhat1:jax.Array, xhat2:jax.Array): + "Compute the interaction energy between activations `xhat1` and `xhat2`." + return -jnp.einsum("...c,...d,cd->...", xhat1, xhat2, self.W) - jnp.multiply(xhat2, self.b).sum() + + @classmethod + def rand_init(cls, key: jax.Array, x1_dim: int, x2_dim: int): + Winit = 0.02 * jr.normal(key, (x1_dim, x2_dim)) + binit = 0.02 * jr.normal(key, (x2_dim,)) + return cls(W=Winit, b=binit) + +class BiasSynapse(eqx.Module): + """Energy defines constant input to a neuron layer""" + b: jax.Array + def __call__(self, xhat:jax.Array): + "Compute the interaction energy between activations `xhat` and the bias `b`." + return -jnp.einsum("...c,c->...", xhat, self.b) +``` + + +```{python} +D1, D2 = 10, 20 +W = 0.02 * jr.normal(jr.key(0), (D1, D2)) +b = jnp.arange(D2)+1 +linear_syn_with_bias = LinearSynapseWithBias(W, b) + +# Gradients match how linear layers work +xhat1 = jr.normal(jr.key(3), (D1,)) +xhat2 = jr.normal(jr.key(4), (D2,)) + +expected_forward = W.T @ xhat1 + b +expected_backward = W @ xhat2 + +forward_signal = -jax.grad(linear_syn_with_bias, argnums=1)(xhat1, xhat2) +backward_signal = -jax.grad(linear_syn_with_bias, argnums=0)(xhat1, xhat2) +assert jnp.allclose(forward_signal, expected_forward) +assert jnp.allclose(backward_signal, expected_backward) + +# Could also use a dedicated bias synapse +bias_syn = BiasSynapse(b=b) +assert jnp.allclose(-jax.grad(bias_syn)(xhat2), bias_syn.b) +``` + +Finally, we can consider even convolutional synapses. We have to get a bit creative to define the energy here to use efficient forward convolution implementations in jax. + +```{python} +#| export +#| +class ConvSynapse(eqx.Module): + """The energy corrolary of a convolutional layer in standard neural networks""" + W: jax.Array + window_strides: Tuple[int, int] + padding: str + + @classmethod + def from_conv_params(cls, + key, # Random weight generation seed + channels_out:int, # nfilters + channels_in:int, # Channels in input + filter_shape:Tuple[int,int], # (h,w) size of filter + window_strides:Tuple[int,int], # (h, w) size of each step + padding="SAME", + mu=0.5, # Mean of W initialization + sigma=0.01, # stdev of W initialization + ): + "Initialize the ConvSynapse from the convolution parameters" + W = jr.normal(key, (channels_out, channels_in, *filter_shape)) * sigma + mu + return cls(W=W, window_strides=window_strides, padding=padding) + + def forward_conv(self, xhat1): + return jax.lax.conv_general_dilated(xhat1, self.W, window_strides=self.window_strides, padding=self.padding, dimension_numbers=("NHWC", "OIHW", "NHWC")) # in (1, H2, W2, Cout) + + def __call__(self, xhat1, xhat2): + """Energy of convolution is defined only for a single input""" + assert len(xhat1.shape)== 3, f"Shape should be (H,W,C), no batch dimension. Got `{xhat1.shape}` for xhat1" + assert len(xhat2.shape)== 3, f"Shape should be (H,W,C), no batch dimension. Got `{xhat2.shape}` for xhat2" + + xhat1 = xhat1[None] # Add batch dimension + xhat2 = xhat2[None] # Add batch dimension + + sig1_into_2 = self.forward_conv(xhat1) + return -jnp.multiply(xhat2, sig1_into_2).sum() +``` + +The gradient w.r.t. `xhat2` is what we call a "forward convolution". The gradient w.r.t. `xhat1` is a ["transposed convolution"](https://docs.jax.dev/en/latest/_autosummary/jax.lax.conv_transpose.html)! + + +```{python} +#| code-fold: true +#| code-summary: Simple test for ConvSynapse +key = jr.key(42) +H, W, C_in, C_out = 8, 8, 3, 5 +filter_h, filter_w = 3, 3 + +# Create a ConvSynapse +conv_syn = ConvSynapse.from_conv_params( + key=key, + channels_out=C_out, + channels_in=C_in, + filter_shape=(filter_h, filter_w), + window_strides=(1, 1), + padding="SAME" +) + +# Create test activations +xhat1 = jr.normal(jr.key(1), (H, W, C_in)) # Input activation +xhat2 = jr.normal(jr.key(2), (H, W, C_out)) # Output activation + +# Test energy computation +energy = conv_syn(xhat1, xhat2) +print(f"Energy: {energy}") +assert isinstance(energy, jax.Array) and energy.shape == () + +# The negative gradient w.r.t. xhat2 is a standard convolution +conv_result = conv_syn.forward_conv(xhat1[None])[0] # Remove batch dim +grad_xhat2 = jax.grad(conv_syn, argnums=1)(xhat1, xhat2) +assert jnp.allclose(-grad_xhat2, conv_result) + +# Test that the conv_transpose is the same as the gradient w.r.t. xhat1 +conv_transpose_result = jax.lax.conv_transpose(xhat2[None], conv_syn.W, strides=conv_syn.window_strides, padding=conv_syn.padding, dimension_numbers=("NHWC", "OIHW", "NHWC"), transpose_kernel=True)[0] +grad_xhat1 = jax.grad(conv_syn, argnums=0)(xhat1, xhat2) +assert jnp.allclose(conv_transpose_result, -grad_xhat1) +``` + +# Energy Hypergraphs {#sec-energy-hypergraphs} + +The above sections have described the building blocks of an Associative Memory. What remains is to build the hypergraph that assembles them into a complete Associative Memory. + +The rules of the building blocks give us a **single total energy** where the update rules are **local** and the system's energy is **guaranteed to decrease**. See @fig-hamux-overview for a graphical depiction of the hypergraph of an Associative Memory. + +![`hamux` hypergraph diagrams are a graphical depiction of an AM whose total energy is the sum of the neuron layer (node) and hypersynapse (hyperedge) energies. Inference is done recurrently, modeled by a system of differential equations where each neuron layer’s hidden state updates to minimize the total energy. When all non-linearities are captured in the dynamic neurons, inference becomes a local computation that avoids differentiating through non-linearities.](./figures/hamux_overview.png){#fig-hamux-overview width=700px} + +The total energy is structured such that the activations of a neuron layer affect only connected hypersynapses and itself. Let $\hat{\mathbf{x}}_\ell$ and $\mathbf{x}_\ell$ represent the activations and internal states of neuron layer $\ell$, and let $\mathtt{N}(\ell)$ represent the set of hypersynapses that connect to neuron layer $\ell$. The following update rule describes how neuron internal states $\mathbf{x}_\ell$ minimize the total energy using only local signals: + +$$ +\tau_\ell\frac{d \mathbf{x}_\ell}{dt} = - \frac{\partial E_\text{total}}{\partial \hat{\mathbf{x}}_\ell} = - \left(\sum_{s \in \mathtt{N}(\ell)} \frac{\partial E^\text{synapse}_s}{\partial \hat{\mathbf{x}}_\ell}\right) - \frac{\partial E^\text{neuron}_\ell}{\partial \hat{\mathbf{x}}_\ell} = \mathcal{I}_{x_\ell} - \mathbf{x}_\ell, +$${#eq-hamux-local-update} + +where $\mathcal{I}_{x_\ell} := - \sum_{s \in \mathtt{N}(\ell)} \nabla_{\hat{\mathbf{x}}_\ell} E^\text{synapse}_s$ is the **total synaptic input current** to neuron layer $\ell$, which is fundamentally local and serves to minimize the energy of connected hypersynapses. See sections. The time constant for neurons in layer $\ell$ is denoted by $\tau_\ell$. + +The central result is that dynamical equations @eq-hamux-local-update decrease the global energy of the network. In order to demostrate this, consider the total time derivative of the energy + + +$$ +\frac{dE_\text{total}}{dt} = \sum\limits_{\ell=1}^L \frac{\partial E_\text{total}}{\partial \hat{\mathbf{x}}_\ell} \frac{\partial \hat{\mathbf{x}}_\ell}{\partial \mathbf{x}_\ell} \frac{d\mathbf{x}_\ell}{dt} = -\sum\limits_{\ell=1}^L \tau_\ell \frac{d \mathbf{x} _\ell }{dt} \frac{\partial^2 \mathcal{L}_x}{\partial \mathbf{x}_\ell \partial \mathbf{x}_\ell} \frac{d\mathbf{x}_\ell}{dt} \leq 0, +$$ + +where we expressed the partial of the energy w.r.t. the activations through the velocity of the neuron's internal states @eq-hamux-local-update. The Hessian matrix $\frac{\partial^2 \mathcal{L}_x}{\partial \mathbf{x}_\ell \partial \mathbf{x}_\ell}$ has the size number of neurons in layer $\ell$ multiplied by the number of neurons in layer $\ell$. As long as this matrix is positive semi-definite, a property resulting from the convexity of the Lagrangian, the total energy of the network is guaranteed to either decrease or stay constant --- increase of the energy is not allowed. + +Additionally, if the energy of the network is bounded from below, the dynamics in @eq-hamux-local-update are guaranteed to lead the trajectories to fixed manifolds corresponding to local minima of the energy. If the fixed manifolds have zero-dimension, i.e., they are fixed point attractors, the velocity field will vanish once the network arrives at the local minimum. This correspondes to Hessians being strictly positive definite. Alternatively, if the Lagrangians have zero modes, resulting in existence of zero eigenvalues of the Hessian matrices, the network may converge to the fixed manifolds, but the velocity fields may stay non-zero, while the network's state moves along that manifold. + +## Energy Hypergraph Implementation + +The local, summing structure of the $E^\text{total}$ is expressible in code as a hypergraph. We roll our own implementation in JAX to keep things simple. + + +```{python} +#| exports +class HAM(eqx.Module): + "A Hypergraph wrapper connecting all dynamic states (neurons) and learnable parameters (synapses) for our associative memory" + neurons: Dict[str, NeuronLayer] + hypersynapses: Dict[str, eqx.Module] + connections: List[Tuple[Tuple, str]] +``` + +We describe an HAM using plain python datastructures for our `neurons`, `hypersynapses` and edge list of `connections`. This makes each object fully compatible with `jax`'s tree mapping utilities, which will help keep our hypergraph code super succinct. + +For example, we can create a simple HAM with two neurons and one hypersynapse: + +```{python} +n1_dim, n2_dim = 10, 100 +neurons = { + "n1": NeuronLayer(lagrangian=lagr_sigmoid, shape=(n1_dim,)), + "n2": NeuronLayer(lagrangian=lambda x: lagr_softmax(x, axis=-1), shape=(n2_dim,)), +} +hypersynapses = { + "s1": LinearSynapse.rand_init(jax.random.key(0), n1_dim, n2_dim), +} +connections = [ + (("n1", "n2"), "s1"), # Read as: "Connect neurons n1 and n2 via synapse s1" +] +ham = HAM(neurons, hypersynapses, connections) +``` + +Let's start with some basic description of the hypergraph, describing the data object we want to create. + +```{python} +#| exports +@patch(as_prop=True) +def n_neurons(self:HAM) -> int: + "Total number of neurons" + return len(self.neurons) + +@patch(as_prop=True) +def n_hypersynapses(self:HAM) -> int: + "Total number of hypersynapses" + return len(self.hypersynapses) + +@patch(as_prop=True) +def n_connections(self:HAM) -> int: + "Total number of connections" + return len(self.connections) +``` + + +```{python} +#| exports +@patch +def init_states(self: HAM, bs: Optional[int] = None): + """Initialize all neuron states""" + if bs is not None and bs > 0: warn("Vectorize with `ham.vectorize()` before processing batched states") + xs = {k: v.init(bs) for k, v in self.neurons.items()} + return xs + +``` + + +Initialize all the dynamic neuron states at once, optionally with a batch size. This makes it easy to treat the whole collection of neuron states as a single tensor. + +```{python} +xs = ham.init_states() +print(jtu.tree_map(lambda x: f"Shape: {x.shape}", xs)) +``` + +Key into these empty states to replace the states with real data. + +```{python} +example_data = jr.normal(jr.key(4), xs['n1'].shape) +xs["n1"] = example_data +``` + +:::{.callout-tip} +## Variable naming conventions + +Throughout this code, we universally use the `xs` variable to refer to the collection of neuron internal states and the `xhats` variable to refer to the collection of neuron activations. + +Additionally, whenever a function `f` takes both `xs` and `xhats` as arguments, we assume the `xhats` are passed first in the argument order i.e., `f(xhats, xs, *args, **kwargs)`. This is because most AM operations do gradient descent on the activations, not the internal states, and the 0-th positional arg is the default argument for `jax.grad` +::: + +```{python} +#| exports +@patch +def activations(self: HAM, xs): + """Convert hidden states of each neuron into their activations""" + xhats = {k: v.sigma(xs[k]) for k, v in self.neurons.items()} + return xhats +``` + +From the states, we can compute the activations of each neuron as a single collection: + +```{python} +xhats = ham.activations(xs) +assert jnp.all(xhats['n1'] > 0) and jnp.all(xhats['n1'] < 1), "Sigmoid neurons should be between 0 and 1" +assert jnp.isclose(xhats['n2'].sum(), 1.0), "Softmax neurons should sum to 1" +``` + +```{python} +#| export +@patch +def neuron_energies(self: HAM, xhats, xs): + """Retrieve the energies of each neuron in the HAM""" + return {k: self.neurons[k].energy(xhats[k], xs[k]) for k in self.neurons.keys()} + +@patch +def connection_energies(self: HAM, xhats): + """Get the energy for each connection""" + def get_energy(neuron_set, s): + neighbor_xhats = [xhats[k] for k in neuron_set] + return self.hypersynapses[s](*neighbor_xhats) + return [get_energy(neuron_set, s) for neuron_set, s in self.connections] + +@patch +def energy_tree(self: HAM, xhats, xs): + """Return energies for each individual component""" + neuron_energies = self.neuron_energies(xhats, xs) + connection_energies = self.connection_energies(xhats) + return {"neurons": neuron_energies, "connections": connection_energies} + +@patch +def energy(self: HAM, xhats, xs): + """The complete energy of the HAM""" + energy_tree = self.energy_tree(xhats, xs) + return jtu.tree_reduce(lambda E, acc: acc + E, energy_tree, 0) +``` + +From the activations, we can collect all the energies of the neurons and the connections in the HAM. We can organize these into an energy tree from which we compute the total energy of the entire HAM.. + +The complete energy of the HAM is the sum of all the individual energies from the `HAM.energy_tree`. + +```{python} +xhats = ham.activations(xs) +pp(ham.energy_tree(xhats, xs)) +``` + +```{python} +pp(ham.energy(xhats, xs)) +``` + +```{python} +#|export +@patch +def dEdact(self: HAM, xhats, xs, return_energy=False): + """Calculate gradient of system energy w.r.t. each activation""" + if return_energy: return jax.value_and_grad(self.energy)(xhats, xs) + return jax.grad(self.energy)(xhats, xs) +``` + +A small helper function to make it easier to compute the gradient of the energy w.r.t. the activations. + +This energy is guaranteed to monotonically decrease over time, and be bounded from below. + +# Vectorizing the Energy + +To scale these models, we generally want to operate on batches of data and activations using the same model. We can do this by creating a `VectorizedHAM` object whose functions all expect a batch dimension in neuron state and activations. + +```{python} +#| export +#| hide +def _docstring_from(source_func): + """Decorator that copies the docstring from source_func to the decorated function""" + def decorator(target_func): + if source_func.__doc__: target_func.__doc__ = source_func.__doc__ + return target_func + return decorator +``` + + +```{python} +#| export +class VectorizedHAM(eqx.Module): + """Re-expose HAM API with vectorized inputs. No new HAM behaviors should be implemented in this class.""" + _ham: eqx.Module + @property + def neurons(self): return self._ham.neurons + @property + def hypersynapses(self): return self._ham.hypersynapses + @property + def connections(self): return self._ham.connections + @property + def n_neurons(self): return self._ham.n_neurons + @property + def n_hypersynapses(self): return self._ham.n_hypersynapses + @property + def n_connections(self): return self._ham.n_connections + + @property + def _batch_axes(self: HAM): + """A helper function to tell vmap to batch along the 0'th dimension of each state in the HAM.""" + return {k: 0 for k in self._ham.neurons.keys()} + + @_docstring_from(HAM.init_states) + def init_states(self, bs=None): + if bs is None or bs == 0: warn("Vectorized HAMs should be initialized with a batch size") + xs = {k: v.init(bs) for k, v in self.neurons.items()} + return xs + + @_docstring_from(HAM.activations) + def activations(self, xs): return jax.vmap(self._ham.activations, in_axes=(self._batch_axes,))(xs) + + @_docstring_from(HAM.connection_energies) + def connection_energies(self, xhats): return jax.vmap(self._ham.connection_energies, in_axes=(self._batch_axes,))(xhats) + + @_docstring_from(HAM.neuron_energies) + def neuron_energies(self, xhats, xs): return jax.vmap(self._ham.neuron_energies, in_axes=(self._batch_axes, self._batch_axes))(xhats, xs) + + @_docstring_from(HAM.energy_tree) + def energy_tree(self, xhats, xs): return jax.vmap(self._ham.energy_tree, in_axes=(self._batch_axes, self._batch_axes))(xhats, xs) + + @_docstring_from(HAM.energy) + def energy(self, xhats, xs): return jax.vmap(self._ham.energy, in_axes=(self._batch_axes, self._batch_axes))(xhats, xs) + + @_docstring_from(HAM.dEdact) + def dEdact(self, xhats, xs, return_energy=False): return jax.vmap(self._ham.dEdact, in_axes=(self._batch_axes, self._batch_axes, None))(xhats, xs, return_energy) + + def unvectorize(self): return self._ham + def vectorize(self): return self +``` + + +```{python} +#| exports +@patch +def vectorize(self: HAM): + """Vectorize to work on batches of inputs""" + return VectorizedHAM(self) + +@patch +def unvectorize(self: HAM): + """Unvectorize to work on single inputs""" + return self +``` + +Now our `HAM` logic works on batches of inputs using `jax.vmap`. + +```{python} +# Instead of this +ham = HAM(neurons=neurons, hypersynapses=hypersynapses, connections=connections) +test_warns(lambda: ham.init_states(bs=5), show=False) +vxs = ham.init_states(bs=5) +test_fail(ham.activations, args=vxs) +``` + +```{python} +# Do this +vham = ham.vectorize() +vxs = vham.init_states(bs=5) +vxhats = vham.activations(vxs) +assert all(g.shape[0] == 5 for g in vxhats.values()), "All activations should have batch dim" +``` \ No newline at end of file diff --git a/nbs/00_lagrangians.ipynb b/nbs/00_lagrangians.ipynb deleted file mode 100644 index b03aa1b..0000000 --- a/nbs/00_lagrangians.ipynb +++ /dev/null @@ -1,978 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Lagrangians\n", - "\n", - "> The well-behaved energy of associative memories is captured by the **Lagrangian** of the neurons" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We begin with the lagrangian, the fundamental unit of any neuron layer." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| default_exp lagrangians" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export \n", - "import jax.numpy as jnp\n", - "import jax\n", - "import numpy as np\n", - "from fastcore.test import *\n", - "import functools as ft\n", - "from typing import *\n", - "import treex as tx\n", - "from dataclasses import dataclass\n", - "from typing import *" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "from nbdev.showdoc import *\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import warnings\n", - "import os" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "warnings.filterwarnings('ignore')\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Functional interface\n", - "\n", - "The Lagrangian functions are central to understanding the energy that neuron layers provide to an associative memory, and they can be thought of as the integrand of common activation functions (e.g., `relu`s and `softmax`es). All lagrangians are functions of the form:\n", - "\n", - "$$\\mathcal{L}(x;\\ldots) \\mapsto \\mathbb{R}$$\n", - "\n", - "where $x \\in \\mathbb{R}^{D_1 \\times \\ldots \\times D_n}$ can be a tensor of arbitrary shape and $\\mathcal{L}$ can be optionally parameterized (e.g., the `LayerNorm`'s learnable bias and scale). It is important that our Lagrangians be convex and differentiable.\n", - "\n", - "We want to rely on JAX's autograd to automatically differentiate our Lagrangians into activation functions. For certain Lagrangians, the naively autodiff-ed function of the defined Lagrangian is numerically unstable (e.g., `lagr_sigmoid(x).sum()` and `lagr_tanh(x).sum()`). In these cases, we follow JAX's [documentation guidelines](https://jax.readthedocs.io/en/latest/notebooks/Custom_derivative_rules_for_Python_code.html) to define `custom_jvp`s to fix this behavior." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "def lagr_identity(x): \n", - " \"\"\"The Lagrangian whose activation function is simply the identity.\"\"\"\n", - " return 1 / 2 * jnp.power(x, 2)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-12-07 14:06:54.891743: E external/org_tensorflow/tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:267] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n", - "WARNING:jax._src.lib.xla_bridge:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "x = np.linspace(-2,2,100); ff = lagr_identity\n", - "llagr = lambda x: ff(x).sum()\n", - "y = jax.grad(llagr)(x)\n", - "y2 = ff(x)\n", - "fig, ax = plt.subplots(1)\n", - "ax.plot(x,y, 'b--', x,y2,'g-')\n", - "ax.set_title(\"Identity\")\n", - "ax.legend([\"activation\", \"lagrangian\"])\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "def lagr_repu(x, \n", - " n): # Degree of the polynomial in the power unit\n", - " \"\"\"Rectified Power Unit of degree `n`\"\"\"\n", - " return 1 / n * jnp.power(jnp.maximum(x, 0), n)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "x = np.linspace(-0.5,2,100)\n", - "ns = [2,4]\n", - "fig, ax = plt.subplots(1)\n", - "colors = 'bgr'\n", - "\n", - "legend = []\n", - "for i, n in enumerate(ns):\n", - " ff = ft.partial(lagr_repu, n=n)\n", - " llagr = lambda x: ff(x).sum()\n", - " act = jax.grad(llagr)(x)\n", - " lag = ff(x)\n", - " # ax.plot(x,act, 'b-', x,lag,'g--')\n", - " c = colors[i]\n", - " legend += [f\"activation (n={n})\", f\"lagrangian (n={n})\"]\n", - " ax.plot(x,act,f\"{c}--\", x,lag,f\"{c}-\")\n", - " ax.set_title(\"RePU\")\n", - "\n", - "ax.legend(legend)\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "$$\\frac{1}{n} \\max(x,0)^n$$" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "def lagr_relu(x):\n", - " \"\"\"Rectified Linear Unit. Same as repu of degree 2\"\"\"\n", - " return lagr_repu(x, 2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "$$\\frac{1}{2} \\max(x,0)^2$$" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "x = np.linspace(-3,3,100); ff = lagr_relu\n", - "llagr = lambda x: ff(x).sum()\n", - "y = jax.grad(llagr)(x)\n", - "y2 = ff(x)\n", - "fig, ax = plt.subplots(1)\n", - "ax.plot(x,y, 'b--', x,y2,'g-')\n", - "ax.set_title(\"ReLU\")\n", - "ax.legend([\"activation\", \"lagrangian\"])\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "def lagr_softmax(x,\n", - " beta:float=1.0, # Inverse temperature\n", - " axis:int=-1): # Dimension over which to apply logsumexp\n", - " \"\"\"The lagrangian of the softmax -- the logsumexp\"\"\"\n", - " return (1/beta * jax.nn.logsumexp(beta * x, axis=axis, keepdims=True))\n", - "\n", - "def lagr_softmax_unstable(x,\n", - " beta:float=1.0, # Inverse temperature\n", - " axis:int=-1): # Dimension over which to apply logsumexp\n", - " \"\"\"The lagrangian of the softmax -- the logsumexp. However, code the `log(sum(exp(...)))` part manually, which can lead to instabilities\n", - " \n", - " The benefit is in porting HAMUX models into the browser, because [TensorFlowJS](https://github.com/tensorflow/tfjs) does not currently support \n", - " JAX logsumexp\n", - " \"\"\"\n", - " return 1/beta * jnp.log(jnp.sum(jnp.exp(beta * x), axis=axis, keepdims=True))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "$$\\frac{1}{\\beta} \\log \\sum\\limits_i \\exp(\\beta x)$$" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We do not plot the `logsumexp` because it has an implicit summation" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "def lagr_exp(x, \n", - " beta:float=1.0): # Inverse temperature\n", - " \"\"\"Exponential activation function, as in [Demicirgil et al.](https://arxiv.org/abs/1702.01929). Operates elementwise\"\"\"\n", - " return 1 / beta * jnp.exp(beta * x)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "$$ \\frac{1}{\\beta} \\exp(\\beta x)$$" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1.2130613\n", - "0.36787945\n", - "0.14875345\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "x = np.linspace(-1,2,100)\n", - "betas = [0.5,1.,1.5]\n", - "# betas = [0.5]\n", - "fig, ax = plt.subplots(1)\n", - "colors = 'bgr'\n", - "\n", - "legend = []\n", - "for i, b in enumerate(betas):\n", - " ff = ft.partial(lagr_exp, beta=b)\n", - " llagr = lambda x: ff(x).sum()\n", - " act = jax.grad(llagr)(x)\n", - " lag = ff(x)\n", - " c = colors[i]\n", - " legend += [f\"activation (beta={b})\", f\"lagrangian (beta={b})\"]\n", - " ax.plot(x,act,f\"{c}--\", x,lag,f\"{c}-\")\n", - " ax.set_title(\"Exponential\")\n", - " print(lag.min())\n", - "\n", - "ax.legend(legend)\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|export\n", - "def lagr_rexp(x, \n", - " beta:float=1.0): # Inverse temperature\n", - " \"\"\"Rectified exponential activation function\"\"\"\n", - " xclipped = jnp.maximum(x, 0)\n", - " return (1 / beta * jnp.exp(beta * xclipped)-xclipped)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "$$\\frac{1}{\\beta} \\exp(\\beta \\bar{x}) - \\bar{x} \\ \\ \\ \\ \\text{where} \\ \\ \\bar{x} = \\max(x,0)$$" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "x = np.linspace(-1.5,2,100)\n", - "betas = [0.5,1.,1.5]\n", - "fig, ax = plt.subplots(1)\n", - "colors = 'bgr'\n", - "\n", - "legend = []\n", - "for i, b in enumerate(betas):\n", - " ff = ft.partial(lagr_rexp, beta=b)\n", - " llagr = lambda x: ff(x).sum()\n", - " act = jax.grad(llagr)(x)\n", - " lag = ff(x)\n", - " # ax.plot(x,act, 'b-', x,lag,'g--')\n", - " c = colors[i]\n", - " legend += [f\"activation (beta={b})\", f\"lagrangian (beta={b})\"]\n", - " ax.plot(x,act,f\"{c}--\", x,lag,f\"{c}-\")\n", - " ax.set_title(\"Rectified Exponential\")\n", - "\n", - "ax.legend(legend)\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The lagrangian of the `tanh` and the `sigmoid` are a bit more numerically unstable. We will need to define custom gradients for them. We show how this is done for the `tanh` case to forward to gradient compute to the optimized `jnp.tanh` function:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| exports\n", - "@jax.custom_jvp\n", - "def _lagr_tanh(x, beta=1.0):\n", - " return 1 / beta * jnp.log(jnp.cosh(beta * x))\n", - "\n", - "@_lagr_tanh.defjvp\n", - "def _lagr_tanh_defjvp(primals, tangents):\n", - " x, beta = primals\n", - " x_dot, beta_dot = tangents\n", - " primal_out = _lagr_tanh(x, beta)\n", - " tangent_out = jnp.tanh(beta * x) * x_dot\n", - " return primal_out, tangent_out\n", - "\n", - "def lagr_tanh(x, \n", - " beta=1.0): # Inverse temperature\n", - " \"\"\"Lagrangian of the tanh activation function\"\"\"\n", - " return _lagr_tanh(x, beta)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|hide\n", - "x = np.random.randn(4,20);beta=0.2; scale=1.3\n", - "llagr = lambda x: lagr_tanh(x, beta=beta).sum()\n", - "test_eq(jax.nn.tanh(beta*x), jax.grad(llagr)(x))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "x = np.linspace(-1.5,2,100)\n", - "betas = [0.5,1.,1.5]\n", - "fig, ax = plt.subplots(1)\n", - "colors = 'bgr'\n", - "\n", - "legend = []\n", - "for i, b in enumerate(betas):\n", - " ff = ft.partial(lagr_tanh, beta=b)\n", - " llagr = lambda x: ff(x).sum()\n", - " act = jax.grad(llagr)(x)\n", - " lag = ff(x)\n", - " # ax.plot(x,act, 'b-', x,lag,'g--')\n", - " c = colors[i]\n", - " legend += [f\"activation (beta={b})\", f\"lagrangian (beta={b})\"]\n", - " ax.plot(x,act,f\"{c}--\", x,lag,f\"{c}-\")\n", - " ax.set_title(\"Tanh\")\n", - "\n", - "ax.legend(legend)\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We define a similar custom JVP for the sigmoid, but its interface is simple." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "@jax.custom_jvp\n", - "def _lagr_sigmoid(x, \n", - " beta=1.0, # Inverse temperature\n", - " scale=1.0): # Amount to stretch the range of the sigmoid's lagrangian\n", - " \"\"\"The lagrangian of a sigmoid that we can define custom JVPs of\"\"\"\n", - " return scale / beta * jnp.log(jnp.exp(beta * x) + 1)\n", - "\n", - "def _tempered_sigmoid(x, \n", - " beta=1.0, # Inverse temperature\n", - " scale=1.0): # Amount to stretch the range of the sigmoid\n", - " \"\"\"The basic sigmoid, but with a scaling factor\"\"\"\n", - " return scale / (1 + jnp.exp(-beta * x))\n", - "\n", - "@_lagr_sigmoid.defjvp\n", - "def _lagr_sigmoid_jvp(primals, tangents):\n", - " x, beta, scale = primals\n", - " x_dot, beta_dot, scale_dot = tangents\n", - " primal_out = _lagr_sigmoid(x, beta, scale)\n", - " tangent_out = _tempered_sigmoid(x, beta=beta, scale=scale) * x_dot # Manually defined sigmoid\n", - " return primal_out, tangent_out\n", - "\n", - "def lagr_sigmoid(x, \n", - " beta=1.0, # Inverse temperature\n", - " scale=1.0): # Amount to stretch the range of the sigmoid's lagrangian\n", - " \"\"\"The lagrangian of the sigmoid activation function\"\"\"\n", - " return _lagr_sigmoid(x, beta=beta, scale=scale)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|hide\n", - "x = np.random.randn(4,20);beta=0.2; scale=1.3\n", - "llagr = lambda x: lagr_sigmoid(x, beta=beta, scale=scale).sum()\n", - "test_eq(_tempered_sigmoid(x, beta=beta, scale=scale), jax.grad(llagr)(x))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "x = np.linspace(-1,1,100)\n", - "betas = [0.5,1.,1.5]\n", - "fig, ax = plt.subplots(1)\n", - "colors = 'bgr'\n", - "\n", - "legend = []\n", - "for i, b in enumerate(betas):\n", - " ff = ft.partial(lagr_sigmoid, beta=b)\n", - " llagr = lambda x: ff(x).sum()\n", - " act = jax.grad(llagr)(x)\n", - " lag = ff(x)\n", - " # ax.plot(x,act, 'b-', x,lag,'g--')\n", - " c = colors[i]\n", - " legend += [f\"activation (beta={b})\", f\"lagrangian (beta={b})\"]\n", - " ax.plot(x,act,f\"{c}--\", x,lag,f\"{c}-\")\n", - " ax.set_title(\"Sigmoid\")\n", - "\n", - "ax.legend(legend)\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|export\n", - "def _simple_layernorm(x:jnp.ndarray, \n", - " gamma:float=1.0, # Scale the stdev\n", - " delta:Union[float, jnp.ndarray]=0., # Shift the mean\n", - " axis=-1, # Which axis to normalize\n", - " eps=1e-5, # Prevent division by 0\n", - " ): \n", - " \"\"\"Layer norm activation function\"\"\"\n", - " xmean = x.mean(axis, keepdims=True)\n", - " xmeaned = x - xmean\n", - " denominator = jnp.sqrt(jnp.power(xmeaned, 2).mean(axis, keepdims=True) + eps)\n", - " return gamma * xmeaned / denominator + delta\n", - "\n", - "def lagr_layernorm(x:jnp.ndarray, \n", - " gamma:float=1.0, # Scale the stdev\n", - " delta:Union[float, jnp.ndarray]=0., # Shift the mean\n", - " axis=-1, # Which axis to normalize\n", - " eps=1e-5, # Prevent division by 0\n", - " ): \n", - " \"\"\"Lagrangian of the layer norm activation function\"\"\"\n", - " D = x.shape[axis] if axis is not None else x.size\n", - " xmean = x.mean(axis, keepdims=True)\n", - " xmeaned = x - xmean\n", - " y = jnp.sqrt(jnp.power(xmeaned, 2).mean(axis, keepdims=True) + eps)\n", - " return D * gamma * y + (delta * x).sum()\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|hide\n", - "x = jax.random.normal(jax.random.PRNGKey(0), (4,20))\n", - "lnorm = tx.LayerNorm().init(jax.random.PRNGKey(0), x)\n", - "llagr = lambda x: lagr_layernorm(x, gamma=1., delta=0.).sum()\n", - "assert jnp.all(jnp.isclose(lnorm(x), jax.grad(llagr)(x)))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|export\n", - "def _simple_spherical_norm(x:jnp.ndarray, \n", - " axis=-1, # Which axis to normalize\n", - " ): \n", - " \"\"\"Spherical norm activation function\"\"\"\n", - " xmean = x.mean(axis, keepdims=True)\n", - " xmeaned = x - xmean\n", - " denominator = jnp.sqrt(jnp.power(xmeaned, 2).mean(axis, keepdims=True) + eps)\n", - " return gamma * xmeaned / denominator + delta\n", - "\n", - "def lagr_spherical_norm(x:jnp.ndarray, \n", - " gamma:float=1.0, # Scale the stdev\n", - " delta:Union[float, jnp.ndarray]=0., # Shift the mean\n", - " axis=-1, # Which axis to normalize\n", - " eps=1e-5, # Prevent division by 0\n", - " ): \n", - " \"\"\"Lagrangian of the spherical norm activation function\"\"\"\n", - " y = jnp.sqrt(jnp.power(x, 2).sum(axis, keepdims=True) + eps)\n", - " return gamma * y + (delta * x).sum()\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|hide\n", - "x = jax.random.normal(jax.random.PRNGKey(0), (4,20))\n", - "llagr = lambda x: lagr_spherical_norm(x, gamma=1., delta=0.).sum()\n", - "xnormed = jax.grad(llagr)(x)\n", - "assert jnp.all(jnp.isclose(jnp.power(xnormed, 2).sum(-1), 1))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Parameterized Lagrangians\n", - "\n", - "It is beneficial to consider lagrangians as modules with their own learnable parameters." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "class LIdentity(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the identity function\"\"\"\n", - " def __init__(self): pass\n", - " def __call__(self, x):\n", - " return lagr_identity(x).sum()\n", - "\n", - "class LRepu(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the rectified polynomial unit of specified degree `n`\"\"\"\n", - " n: float = 2\n", - " \n", - " # Need a default for `n` to work with layer creation\n", - " def __init__(self,\n", - " n=2.): # The degree of the RePU. By default, set to the ReLU configuration\n", - " self.n = n\n", - "\n", - " def __call__(self, x):\n", - " return lagr_repu(x, self.n).sum()\n", - " \n", - "class LRelu(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the rectified linear unit\"\"\"\n", - " def __init__(self): pass\n", - " def __call__(self, x):\n", - " return lagr_relu(x).sum()\n", - " \n", - "class LSigmoid(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the sigmoid\n", - " \n", - " Parameterized by (beta)\n", - " \"\"\"\n", - " beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0)\n", - " scale: float = tx.Parameter.node(default=1.0)\n", - " min_beta: float = 1e-6\n", - " \n", - " def __init__(self, \n", - " beta=1., # Inverse temperature\n", - " scale=1., # Amount to stretch the sigmoid.\n", - " min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive.\n", - " self.beta = beta\n", - " self.scale = scale\n", - " self.min_beta = min_beta\n", - "\n", - " def __call__(self, x):\n", - " return lagr_sigmoid(x, beta=jnp.clip(self.beta, self.min_beta), scale=self.scale).sum()\n", - " \n", - "class LSoftmax(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the softmax\n", - " \n", - " Parameterized by (beta)\n", - " \"\"\"\n", - " beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0)\n", - " axis: int = -1\n", - " min_beta: float = 1e-6\n", - "\n", - " def __init__(self, \n", - " beta=1., # Inverse temperature\n", - " axis=-1, # Axis over which to apply the softmax\n", - " min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive.\n", - " self.beta = beta\n", - " self.axis = axis\n", - " self.min_beta = min_beta\n", - "\n", - " def __call__(self, x):\n", - " return lagr_softmax(x, beta=jnp.clip(self.beta, self.min_beta), axis=self.axis).sum()\n", - " \n", - " \n", - "class LSoftmaxUnstable(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the softmax, using manually coded `logsumexp` for browser compatibility\n", - " \n", - " Parameterized by (beta)\n", - " \"\"\"\n", - " beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0)\n", - " axis: int = -1\n", - " min_beta: float = 1e-6\n", - "\n", - " def __init__(self, \n", - " beta=1., # Inverse temperature\n", - " axis=-1, # Axis over which to apply the softmax\n", - " min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive.\n", - " self.beta = beta\n", - " self.axis = axis\n", - " self.min_beta = min_beta\n", - "\n", - " def __call__(self, x):\n", - " return lagr_softmax_unstable(x, beta=jnp.clip(self.beta, self.min_beta), axis=self.axis).sum()\n", - " \n", - " \n", - "class LExp(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the exponential function\n", - " \n", - " Parameterized by (beta)\n", - " \"\"\"\n", - " beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0)\n", - " min_beta: float = 1e-6\n", - "\n", - " def __init__(self, \n", - " beta=1., # Inverse temperature, for the sharpness of the exponent\n", - " min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive.\n", - " self.beta = beta\n", - " self.min_beta = min_beta\n", - " \n", - " def __call__(self, x):\n", - " return lagr_exp(x, beta=jnp.clip(self.beta, self.min_beta)).sum()\n", - " \n", - "class LRexp(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the rectified exponential function\n", - " \n", - " Parameterized by (beta)\n", - " \"\"\"\n", - " beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0)\n", - " min_beta: float = 1e-6\n", - "\n", - " def __init__(self, \n", - " beta=1., # Inverse temperature, for the sharpness of the exponent\n", - " min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive.\n", - " self.beta = beta\n", - " self.min_beta = min_beta\n", - " \n", - " def __call__(self, x):\n", - " return lagr_rexp(x, beta=jnp.clip(self.beta, self.min_beta)).sum()\n", - " \n", - " \n", - "class LTanh(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the tanh\n", - " \n", - " Parameterized by (beta)\n", - " \"\"\"\n", - " beta: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0)\n", - " min_beta: float = 1e-6\n", - "\n", - " def __init__(self, \n", - " beta=1., # Inverse temperature, for the sharpness of the exponent\n", - " min_beta=1e-6): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive.\n", - " self.beta = beta\n", - " self.min_beta = min_beta\n", - "\n", - " def __call__(self, x):\n", - " return lagr_tanh(x, beta=jnp.clip(self.beta,self.min_beta)).sum()\n", - " \n", - "class LLayerNorm(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the layer norm\n", - " \n", - " Parameterized by (gamma, delta), a scale and a shift\n", - " \"\"\"\n", - " gamma: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0)\n", - " delta: Union[float, jnp.ndarray] = tx.Parameter.node(default=0.)\n", - " eps: float = 1e-5\n", - "\n", - " def __init__(self, \n", - " gamma=1., # Inverse temperature, for the sharpness of the exponent\n", - " delta=0.,\n", - " eps = 1e-5\n", - " ): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive.\n", - " self.gamma = gamma\n", - " self.delta = delta\n", - " self.eps = eps\n", - "\n", - " def __call__(self, x):\n", - " return lagr_layernorm(x, gamma=self.gamma, delta=self.delta, eps=self.eps).sum()\n", - " \n", - "class LSphericalNorm(tx.Module):\n", - " \"\"\"Reduced Lagrangian whose activation function is the spherical L2 norm\n", - " \n", - " Parameterized by (gamma, delta), a scale and a shift\n", - " \"\"\"\n", - " # gamma: Union[float, jnp.ndarray] = tx.Parameter.node(default=1.0)\n", - " # delta: Union[float, jnp.ndarray] = tx.Parameter.node(default=0.)\n", - " eps: float = 1e-5\n", - "\n", - " def __init__(self, \n", - " gamma=1., # Inverse temperature, for the sharpness of the exponent\n", - " delta=0.,\n", - " eps = 1e-5\n", - " ): # Minimal accepted value of beta. For energy dynamics, it is important that beta be positive.\n", - " self.gamma = gamma\n", - " self.delta = delta\n", - " self.eps = eps\n", - "\n", - " def __call__(self, x):\n", - " return lagr_spherical_norm(x, gamma=self.gamma, delta=self.delta, eps=self.eps).sum()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Array(3.995732, dtype=float32)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#| hide\n", - "x = jnp.ones(20)\n", - "LIdentity()(x)\n", - "LRepu(n=4)(x)\n", - "LRelu()(x)\n", - "LSigmoid()(x)\n", - "LTanh()(x)\n", - "LRexp()(x)\n", - "LExp()(x)\n", - "LLayerNorm()(x)\n", - "LSphericalNorm()(x)\n", - "LSoftmax()(x)\n", - "LSoftmaxUnstable()(x)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The modules can be initialized and used as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Array(8.217218, dtype=float32)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "lag = LRepu(n=4)\n", - "x = jax.random.normal(jax.random.PRNGKey(1), (7,))\n", - "lag(x)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To apply the lagrangian to a batch of samples, we should take advantage of `jax.vmap`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Array([0.79066116, 0.634871 , 0.13261071, 3.3233747 ], dtype=float32)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "lag = jax.vmap(LRepu(n=4)); batch_size = 4\n", - "x = jax.random.normal(jax.random.PRNGKey(1), (batch_size,7))\n", - "lag(x)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "import nbdev; nbdev.nbdev_export()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:hamux]", - "language": "python", - "name": "conda-env-hamux-py" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/nbs/01_lagrangians.qmd b/nbs/01_lagrangians.qmd new file mode 100644 index 0000000..4925def --- /dev/null +++ b/nbs/01_lagrangians.qmd @@ -0,0 +1,497 @@ +# Lagrangians +> The well-behaved dynamics of associative memories is described by the Lagrangians of the neurons. + +```{python} +#| default_exp lagrangians +``` + +::: {.callout-note} +## TL;DR + +1. All dynamics of Associative Memory are constrained by a Lagrangian +2. The Lagrangian is a convex, scalar-valued function +3. A neuron's **activations** are the derivative of that neuron's Lagrangian. These activations are often non-linear functions of the dynamic state, and look like the activation functions that we see in many modern Neural Networks (e.g., `sigmoid`, `tanh`, `relu`, `softmax`, `LayerNorm`, etc.) +::: + +Lagrangian functions are fundamental to the energy of 🌀**neuron layers**. These convex functions can be seen as the integral of common activation functions (e.g., `relu`s and `softmax`es). All Lagrangians are functions of the form: + +$$\mathcal{L}(\mathbf{x};\ldots) \mapsto \mathbb{R}$$ + +where $\mathbf{x} \in \mathbb{R}^{D_1 \times \ldots \times D_n}$ can be a tensor of arbitrary shape and $\mathcal{L}$ can be optionally parameterized (e.g., the `LayerNorm`'s learnable bias and scale). **Lagrangians must be convex and differentiable.** + +We want to rely on JAX's autograd to automatically differentiate our Lagrangians into activation functions. For certain Lagrangians, the naively autodiff-ed function of the defined Lagrangian is numerically unstable (e.g., `lagr_sigmoid(x)` and `lagr_tanh(x)`). In these cases, we follow JAX's [documentation guidelines](https://jax.readthedocs.io/en/latest/notebooks/Custom_derivative_rules_for_Python_code.html) to define `custom_jvp`s to fix this behavior. + +## Elementwise Lagrangians + +Though we define Lagrangians for an entire tensor, these special "elementwise Lagrangians" take a special form: they are simply the sum of the convex, differentiable function applied elementwise to the underlying tensor. This makes it easy to plot and visualize them. + +Let's look at what some of these Lagrangians look like in practice. + +```{python} +#| export +#| hide +import equinox as eqx +from typing import Union, Callable, Tuple, Dict, List, Optional +import jax +import jax.numpy as jnp +import jax.tree_util as jtu +import jax.random as jr +from jax import lax +from jax._src.numpy.reductions import _reduction_dims +from jax._src.numpy.util import promote_args_inexact +import numpy as np +from jaxtyping import Float, Array + +Scalar = Float[Array, ""] +Tensor = Float[Array, "..."] +``` + +```{python} +#| hide +import matplotlib.pyplot as plt +import functools as ft +``` + +```{python} +#| export +def lagr_identity(x: Array, # Input tensor + ) -> Float: # Output scalar + """The Lagrangian whose activation function is simply the identity.""" + return 0.5 * jnp.power(x, 2).sum() + +``` + +$$ +\begin{align*} +\mathcal{L}_\text{identity}(\mathbf{x}) &= \frac{1}{2} \sum_i x_i^2 \\ +\partial_{x_i} \mathcal{L}_\text{identity}(\mathbf{x}) &= x_i +\end{align*} +$$ + +```{python} +#| echo: false +#| fig-align: center +#| fig-responsive: true +x = np.linspace(-2,2,100) +y = jax.grad(lagr_identity)(x) +L = jax.vmap(lagr_identity)(x) +fig, ax = plt.subplots(1) +ax.plot(x,y, 'b--', x, L, 'g-') +# ax.set_title(r"$\mathcal{L}_\text{identity}(x) = \frac{1}{2} \sum x^2$") +ax.set_title(r"lagr_identity") +ax.legend(["activation", "lagrangian"]) +plt.show(fig) +``` + +```{python} +#| export +def _repu(x: Array, # Input tensor + n: float # Degree of the polynomial in the power unit + ) -> Float: # Output scalar + return jnp.maximum(x, 0) ** n + + +def lagr_repu(x: Array, # Input tensor + n: float # Degree of the polynomial in the power unit + ) -> Float: # Output scalar + """Rectified Power Unit of degree `n`""" + return 1 / n * jnp.power(jnp.maximum(x, 0), n).sum() +``` + +$$ +\begin{align*} +\mathcal{L}_\text{RePU}(\mathbf{x}; n) &= \frac{1}{n} \sum_i \max(x_i, 0)^n \\ +\partial_{x_i} \mathcal{L}_\text{RePU}(\mathbf{x}; n) &= \max(x_i, 0)^{n-1} +\end{align*} +$$ + +```{python} +#| echo: false +#| fig-align: center +#| fig-responsive: true +x = np.linspace(-0.5,2,100) +ns = [2,4] +fig, ax = plt.subplots(1) +colors = 'bgr' + +legend = [] +for i, n in enumerate(ns): + lag = jax.vmap(lambda x_: lagr_repu(x_, n=n))(x) + act = jax.grad(lambda x_: lagr_repu(x_, n=n))(x) + # ax.plot(x,act, 'b-', x,lag,'g--') + c = colors[i] + legend += [f"activation (n={n})", f"lagrangian (n={n})"] + ax.plot(x,act,f"{c}--", x,lag,f"{c}-") + # ax.set_title(r"$\mathcal{L}_\text{RePU}(x; n) = \frac{1}{n} \sum \max(x, 0)^n$") + ax.set_title(r"lagr_repu") + +ax.legend(legend) +plt.show(fig) +``` + +```{python} +#| export +def lagr_relu(x: Array, # Input tensor + ) -> Float: # Output scalar + """Rectified Linear Unit. Same as `lagr_repu` of degree 2""" + return lagr_repu(x, 2) +``` + +$$ +\begin{align*} +\mathcal{L}_\text{relu}(\mathbf{x}) &= \frac{1}{2} \sum_i \max(x_i, 0)^2 \\ +\partial_{x_i} \mathcal{L}_\text{relu}(\mathbf{x}) &= \max(x_i, 0) +\end{align*} +$$ + +```{python} +#| export +def lagr_exp(x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar + """Exponential activation function, as in [Demicirgil et al.](https://arxiv.org/abs/1702.01929). Operates elementwise""" + return 1 / beta * jnp.exp(beta * x).sum() +``` + +$$ +\begin{align*} +\mathcal{L}_\text{exp}(\mathbf{x}; \beta) &= \frac{1}{\beta} \sum_i e^{\beta x_i} \\ +\partial_{x_i} \mathcal{L}_\text{exp}(\mathbf{x}; \beta) &= e^{\beta x_i} +\end{align*} +$$ + + +```{python} +#| echo: false +#| fig-align: center +#| fig-responsive: true +x = np.linspace(-1,2,100) +betas = [0.5,1.,1.5] +fig, ax = plt.subplots(1) +colors = 'bgr' + +legend = [] +for i, b in enumerate(betas): + lagr_fn = ft.partial(lagr_exp, beta=b) + y = jax.grad(lagr_fn)(x) + L = jax.vmap(lagr_fn)(x) + c = colors[i] + legend += [f"activation (beta={b})", f"lagrangian (beta={b})"] + ax.plot(x,y,f"{c}--", x,L,f"{c}-") + # ax.set_title(r"$\mathcal{L}_\text{exp}(x; \beta) = \frac{1}{\beta} \sum_i e^{\beta x_i}$") + ax.set_title(r"lagr_exp") + +ax.legend(legend) +plt.show(fig) +``` + +```{python} +#| export +def _rexp( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature +) -> Float: # Output scalar + """Rectified exponential activation function""" + xclipped = jnp.maximum(x, 0) + return jnp.exp(beta * xclipped) - 1 + + +def lagr_rexp(x: Array, + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar + """Lagrangian of the Rectified exponential activation function""" + xclipped = jnp.maximum(x, 0) + return (jnp.exp(beta * xclipped) / beta - xclipped).sum() + +``` + +```{python} +#| export + +@jax.custom_jvp +def _lagr_tanh(x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar + return 1 / beta * jnp.log(jnp.cosh(beta * x)) + + +@_lagr_tanh.defjvp +def _lagr_tanh_defjvp(primals, tangents): + x, beta = primals + x_dot, beta_dot = tangents + primal_out = _lagr_tanh(x, beta) + tangent_out = jnp.tanh(beta * x) * x_dot + return primal_out, tangent_out + + +def lagr_tanh(x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar + """Lagrangian of the tanh activation function""" + return _lagr_tanh(x, beta).sum() +``` + +$$ +\begin{align*} +\mathcal{L}_\text{tanh}(\mathbf{x}; \beta) &= \frac{1}{\beta} \sum_i \log(\cosh(\beta x_i)) \\ +\partial_{x_i} \mathcal{L}_\text{tanh}(\mathbf{x}; \beta) &= \tanh(\beta x_i) +\end{align*} +$$ + +```{python} +#| export +@jax.custom_jvp +def _lagr_sigmoid( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar + """The lagrangian of a sigmoid that we can define custom JVPs of""" + return 1. / beta * jnp.log(jnp.exp(beta * x) + 1) + + +def _sigmoid( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + ) -> Float: # Output scalar + """The basic sigmoid""" + return 1. / (1 + jnp.exp(-beta * x)) + + +@_lagr_sigmoid.defjvp +def _lagr_sigmoid_jvp(primals, tangents): + x, beta = primals + x_dot, beta_dot = tangents + primal_out = _lagr_sigmoid(x, beta) + tangent_out = ( + _sigmoid(x, beta=beta) * x_dot + ) # Manually defined sigmoid + return primal_out, tangent_out + + +def lagr_sigmoid( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature +) -> Float: # Output scalar + """The lagrangian of the sigmoid activation function""" + return _lagr_sigmoid(x, beta=beta).sum() + +``` + +```{python} +#| echo: false +#| fig-align: center +#| fig-responsive: true +x = np.linspace(-6,6,100) +betas = [0.5,1.,5.] +fig, ax = plt.subplots(1) +colors = 'bgr' + +legend = [] +for i, b in enumerate(betas): + lagr_fn = ft.partial(lagr_sigmoid, beta=b) + y = jax.grad(lagr_fn)(x) + L = jax.vmap(lagr_fn)(x) + c = colors[i] + legend += [f"activation (beta={b})", f"lagrangian (beta={b})"] + ax.plot(x,y,f"{c}--", x,L,f"{c}-") + # ax.set_title(r"$\mathcal{L}_\text{tanh}(x; \beta) = \frac{1}{\beta} \sum \log(\cosh(\beta x))$") + ax.set_title(r"lagr_tanh") + +ax.legend(legend) +plt.show(fig) +``` + +## Lagrangians with competing units {#lagrangians-with-competing-units} + +We can define Lagrangians where activations are normalized in some way (i.e., where the derivative of the Lagrangian introduces some normalization factor). There are many forms of activation functions in modern Deep Learning with this structure; e.g., `softmax`es, `layernorm`s, etc. normalize their input by some value. There is a nice interpretation of these kinds of activation functions as [competing hidden units](https://arxiv.org/abs/1806.10181). + +```{python} +#| export +def lagr_softmax( + x: Array, # Input tensor + beta: float = 1.0, # Inverse temperature + axis: int = -1, # Dimension over which to apply logsumexp +) -> Float: # Output scalar + """The lagrangian of the softmax -- the logsumexp""" + return 1 / beta * jax.nn.logsumexp(beta * x, axis=axis, keepdims=False) +``` + +$$ +\begin{align*} +\mathcal{L}_\text{softmax}(\mathbf{x}; \beta) &= \frac{1}{\beta} \log \sum_i e^{\beta x_i} \\ +\partial_{x_i} \mathcal{L}_\text{softmax}(\mathbf{x}; \beta) &= \frac{e^{\beta x_i}}{\sum_j e^{\beta x_j}} +\end{align*} +$$ + +We plot its activations (the softmax) for a vector of length 10 below. + +```{python} +#| echo: false +#| fig-align: center +#| fig-responsive: true +x = jr.normal(jr.PRNGKey(5), (10,))*1.5 +y = jax.grad(lagr_softmax)(x) +fig, ax = plt.subplots(1) +ax.bar(jnp.arange(len(x)), y) +ax.set_xlabel("Index") +ax.set_ylabel("Softmax Activation") +# ax.set_title(r"$\mathcal{L}_\text{softmax}(x; \beta) = \frac{1}{\beta} \log \sum_i e^{\beta x_i}$, where $\beta = 1$") +ax.set_title(r"lagr_softmax") +ax.legend(["softmax"]) +plt.show(fig) +``` + + +```{python} +#| export +def _simple_layernorm( + x: Array, # Input tensor + gamma: float = 1.0, # Scale the stdev + delta: Union[float, Array] = 0.0, # Shift the mean + axis: int = -1, # Which axis to normalize + eps: float = 1e-5, # Prevent division by 0 +) -> Array: # Layer normalized `x` + """Layer norm activation function""" + xmean = x.mean(axis, keepdims=True) + xmeaned = x - xmean + denominator = jnp.sqrt(jnp.power(xmeaned, 2).mean(axis, keepdims=True) + eps) + return gamma * xmeaned / denominator + delta + + +def lagr_layernorm( + x: Array, # Input tensor + gamma: float = 1.0, # Scale the stdev + delta: Union[float, Array] = 0.0, # Shift the mean + axis: int = -1, # Which axis to normalize + eps: float = 1e-5, # Prevent division by 0 +) -> Float: # Output scalar + """Lagrangian of the layer norm activation function. + + `gamma` must be a float, not a vector. + """ + D = x.shape[axis] if axis is not None else x.size + xmean = x.mean(axis, keepdims=True) + xmeaned = x - xmean + y = jnp.sqrt(jnp.power(xmeaned, 2).mean(axis, keepdims=True) + eps) + return (D * gamma * y + (delta * x).sum()).sum() + +``` + +$$ +\begin{align*} +\mathcal{L}_\text{layernorm}(\mathbf{x}; \gamma, \delta) &= D \gamma \sqrt{\text{Var}(\mathbf{x}) + \epsilon} + \sum_i \delta_i x_i \\ +\partial_{x_i} \mathcal{L}_\text{layernorm}(\mathbf{x}; \gamma, \delta) &= \gamma \frac{x_i - \text{Mean}(\mathbf{x})}{\sqrt{\text{Var}(\mathbf{x}) + \epsilon}} + \delta_i +\end{align*} +$$ + +```{python} +#| export +def _simple_spherical_norm( + x: Array, # Input tensor + gamma: float = 1.0, # Scale the stdev + delta: Union[float, Array] = 0.0, # Shift the mean + axis: int = -1, # Which axis to normalize + eps=1e-5, # Prevent division by 0 +): + """Spherical norm activation function""" + xnorm = jnp.sqrt(jnp.power(x, 2).sum(axis, keepdims=True) + eps) + return gamma * x / xnorm + delta + + +def lagr_spherical_norm( + x: Array, # input tensor + gamma: float = 1.0, # Scale the stdev + delta: Union[float, jnp.ndarray] = 0.0, # Shift the mean + axis: int=-1, # Which axis to normalize + eps: float=1e-5, # Prevent division by 0 +) -> Float: # Output scalar + """Lagrangian of the spherical norm (L2 norm) activation function""" + y = jnp.sqrt(jnp.power(x, 2).sum(axis, keepdims=True) + eps) + return (gamma * y + (delta * x).sum()).sum() + +``` + +$$ +\begin{align*} +\mathcal{L}_\text{L2norm}(\mathbf{x}; \gamma, \delta) &= \gamma \sqrt{\sum_i x_i^2 + \epsilon} + \sum_i \delta_i x_i \\ +\partial_{x_i} \mathcal{L}_\text{L2norm}(\mathbf{x}; \gamma, \delta) &= \gamma \frac{x_i}{\sqrt{\sum_j x_j^2 + \epsilon}} + \delta_i +\end{align*} +$$ + +```{python} +#|export +#|hide + +# Enable this function, but don't document it for now +def lagr_ghostmax( + a: Array, # Input tensor + axis: Optional[int] = None, # Axis along which the sum to be computed. If None, the sum is computed along all the axes. + b: Union[Array, None] = None, # Scaling factors for the exponentials. Must be broadcastable to the shape of a. + keepdims: bool = False, # If `True`, the axes that are reduced are left in the output as dimensions of size 1. + return_sign: bool = False, # If `True`, the output will be a (result, sign) pair, where sign is the sign of the sums and result contains the logarithms of their absolute values. If False only result is returned and it will contain NaN values if the sums are negative. + ) -> Union[Array, Tuple[Array, Array]]: # Either an array result or a pair of arrays (result, sign), depending on the value of the return_sign argument. + """ A strictly convex version of logsumexp that concatenates 0 to the array before passing to logsumexp. Code adapted from `jax.nn.logsumexp` (documentation below) + + """ + jax.nn.logsumexp.__doc__ + if b is not None: + a_arr, b_arr = promote_args_inexact("logsumexp", a, b) + a_arr = jnp.where(b_arr != 0, a_arr, -jnp.inf) + else: + a_arr, = promote_args_inexact("logsumexp", a) + b_arr = a_arr # for type checking + pos_dims, dims = _reduction_dims(a_arr, axis) + amax = jnp.max(a_arr, axis=dims, keepdims=keepdims) + amax = lax.max(amax, 0.) + amax = lax.stop_gradient(lax.select(jnp.isfinite(amax), amax, lax.full_like(amax, 0))) + amax_with_dims = amax if keepdims else lax.expand_dims(amax, pos_dims) + + # fast path if the result cannot be negative. + if b is None and not np.issubdtype(a_arr.dtype, np.complexfloating): + out = lax.add(lax.log(jnp.sum(lax.exp(lax.sub(a_arr, amax_with_dims)), + axis=dims, keepdims=keepdims) + lax.exp(-amax)), + amax) + sign = jnp.where(jnp.isnan(out), out, 1.0) + sign = jnp.where(jnp.isneginf(out), 0.0, sign).astype(out.dtype) + else: + expsub = lax.exp(lax.sub(a_arr, amax_with_dims)) + if b is not None: + expsub = lax.mul(expsub, b_arr) + + expsub = expsub + lax.exp(-amax_with_dims) + sumexp = jnp.sum(expsub, axis=dims, keepdims=keepdims) + + sign = lax.stop_gradient(jnp.sign(sumexp)) + if np.issubdtype(sumexp.dtype, np.complexfloating): + if return_sign: + sumexp = sign*sumexp + out = lax.add(lax.log(sumexp), amax) + else: + out = lax.add(lax.log(lax.abs(sumexp)), amax) + if return_sign: + return (out, sign) + if b is not None: + if not np.issubdtype(out.dtype, np.complexfloating): + with jax.debug_nans(False): + out = jnp.where(sign < 0, jnp.array(np.nan, dtype=out.dtype), out) + return out + return out + +def ghostmax(a, axis=None): + """Properly implemented ghostmax, robust to input scale. A softmax with additional `1+__` in the denominator. The derivative of `lseplus`""" + if axis is None: + og_shape = a.shape + a = jnp.pad(a.ravel(), ((1,0),), constant_values=0.) + a = jax.nn.softmax(a) + return a[1:].reshape(og_shape) + else: + pad_widths = [(0,0) for _ in range(len(a.shape))] + pad_widths[axis] = (1,0) + pad_width = tuple(pad_widths) + + a = jnp.pad(a, pad_width, constant_values=0.) + a = jax.nn.softmax(a, axis=axis) + + out_idxer = [slice(None) for _ in range(len(a.shape))] + out_idxer[axis] = slice(1, None) + return a[tuple(out_idxer)] +``` \ No newline at end of file diff --git a/nbs/01_layers.ipynb b/nbs/01_layers.ipynb deleted file mode 100644 index 334546a..0000000 --- a/nbs/01_layers.ipynb +++ /dev/null @@ -1,703 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| default_exp layers" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "from nbdev.showdoc import *\n", - "from fastcore.test import *\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import os\n", - "import warnings\n", - "from IPython.display import display, HTML" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "warnings.filterwarnings('ignore')\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Neuron Layers\n", - "\n", - "> Turning Lagrangians into building blocks for our network" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - " \"Hopfield\n", - "
The energy fundamentals of a Neuron Layer.
\n", - "
\n" - ], - "text/plain": [ - "" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#|echo: false\n", - "HTML(\"\"\"\n", - "
\n", - " \"Hopfield\n", - "
The energy fundamentals of a Neuron Layer.
\n", - "
\n", - "\"\"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Fundamentally, a neuron layer is nothing more than a lagrangian function on top of data. This Lagrangian completely defines both an **energy** and an **activation** for the layer. In practice, we additionally specify the following in addition to the Lagrangian:\n", - "\n", - "- A `shape`\n", - "- A time constant `tau`\n", - "- A `bias` (optional) that we can view as the activation threshold of a neuron layer\n", - "\n", - "Our neuron layers are extensions of the neuron layer as it is commonly incorporated in feedforward architectures. The primary difference is that our neuron layers *evolve their state $x$ over time* and have a *bounded energy function* on their states. The energy function of our neuron is completely defined by its Lagrangian $\\mathcal{L}$\n", - "\n", - "$$E_\\text{layer} = \\sum\\limits_i x_i g_i - \\mathcal{L}(x)$$\n", - "\n", - "where $g = \\nabla_x \\mathcal{L}$ are the \"activations\". The first component is a summation of the elementwise multiplication between $x$ and $g$. The second term is the Lagrangian. This energy function is the direct consequence of the Legendre transform on the Lagrangian.\n", - "\n", - "We can view a neuron layer of shape `(D,)` as a collection of $D$ neurons holding scalar data. Convolutional networks frequently have activations defined atop images or image patches of shape `(H,W,D)`. We can view layers of this shape as a collection of $D$ neurons each of shape $(H,W)$. Lagrangians that reduce over a particular dimension (e.g., the `softmax`) will typically reduce over the neuron dimension $D$." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| default_exp layers" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "from nbdev.showdoc import *\n", - "from fastcore.test import *\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import os\n", - "import warnings" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "warnings.filterwarnings('ignore')\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "import jax\n", - "import jax.numpy as jnp\n", - "from typing import *\n", - "import treex as tx\n", - "from abc import ABC, abstractmethod\n", - "from flax import linen as nn\n", - "from hamux.lagrangians import *\n", - "import functools as ft\n", - "from fastcore.meta import delegates\n", - "from fastcore.utils import *\n", - "from fastcore.basics import *" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "class Layer(tx.Module):\n", - " \"\"\"The energy building block of any activation in our network that we want to hold state over time\"\"\"\n", - " lagrangian: tx.Module \n", - " shape: Tuple\n", - " tau: float\n", - " use_bias: bool\n", - " bias: jnp.ndarray = tx.Parameter.node(default=None)\n", - "\n", - " def __init__(self, \n", - " lagrangian:tx.Module, # Factory function creating lagrangian module describing\n", - " # lagrangian:Union[Callable, tx.Module], Either a factory function or the module itself depending on `init_lagr's` value\n", - " shape:Tuple[int], # Number and shape of neuron assembly\n", - " tau:float=1.0, # Time constant\n", - " use_bias:bool=False, # Add bias?\n", - " init_lagrangian=False, # Initialize the lagrangian with kwargs?\n", - " name:str=None, # Overwrite default class name, if provided\n", - " **kwargs, # Passed to lagranigan factory\n", - " ): \n", - " self.lagrangian = lagrangian(**kwargs) if init_lagrangian else lagrangian\n", - " self.shape = shape\n", - " assert tau > 0.0, \"Tau must be positive and non-zero\"\n", - " self.tau = tau\n", - " self.use_bias = use_bias\n", - "\n", - " if name is not None:\n", - " self.name = name\n", - " \n", - " def energy(self, x):\n", - " \"\"\"The predefined energy of a layer, defined for any lagrangian\"\"\"\n", - " if self.initializing():\n", - " if self.use_bias:\n", - " self.bias = nn.initializers.normal(0.02)(tx.next_key(), self.shape)\n", - " x2 = x - self.bias if self.use_bias else x # Is this an issue?\n", - "\n", - " # When jitted, this is no slower than the optimized `@` vector multiplication\n", - " return jnp.multiply(self.g(x), x2).sum() - self.lagrangian(x2)\n", - " \n", - " def __call__(self, x):\n", - " \"\"\"Alias for `self.energy`. Helps simplify treex's `.init` method\"\"\"\n", - " return self.energy(x)\n", - " \n", - " def activation(self, x):\n", - " \"\"\"The derivative of the lagrangian is our activation or Gain function `g`. \n", - " \n", - " Defined to operate over input states `x` of shape `self.shape`\n", - " \"\"\"\n", - " if self.initializing():\n", - " if self.use_bias:\n", - " self.bias = nn.initializers.normal(0.02)(tx.next_key(), self.shape)\n", - " x2 = x - self.bias if self.use_bias else x\n", - " return jax.grad(self.lagrangian)(x2)\n", - " \n", - " def g(self, x):\n", - " \"\"\"Alias for `self.activation`\"\"\"\n", - " return self.activation(x)\n", - "\n", - " def init_state(self, \n", - " bs: int = None, # Batch size\n", - " rng=None): # If given, initialize states from a normal distribution with this key\n", - " \"\"\"Initialize the states of this layer, with correct shape.\n", - " \n", - " If `bs` is provided, return tensor of shape (bs, *self.shape), otherwise return self.shape\n", - " By default, initialize layer state to all 0.\n", - " \"\"\"\n", - " layer_shape = self.shape if bs is None else (bs, *self.shape)\n", - " if rng is not None:\n", - " return jax.random.normal(rng, layer_shape)\n", - " return jnp.zeros(layer_shape)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Initialize with a lagrangian" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Layer {\n", - " bias: None,\n", - " lagrangian: LExp {\n", - " beta: 5.0, Parameter\n", - " min_beta: 1e-06,\n", - " name: \"lexp\", str\n", - " },\n", - " name: \"layer\", str\n", - " shape: tuple [\n", - " 32,\n", - " 32,\n", - " 3,\n", - " ],\n", - " tau: 1.0,\n", - " use_bias: False,\n", - "}" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Layer(LExp(beta=5.), (32,32,3))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L48){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.energy\n", - "\n", - "> Layer.energy (x)\n", - "\n", - "The predefined energy of a layer, defined for any lagrangian" - ], - "text/plain": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L48){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.energy\n", - "\n", - "> Layer.energy (x)\n", - "\n", - "The predefined energy of a layer, defined for any lagrangian" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(Layer.energy)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L58){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.__call__\n", - "\n", - "> Layer.__call__ (x)\n", - "\n", - "Alias for `self.energy`. Helps simplify treex's `.init` method" - ], - "text/plain": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L58){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.__call__\n", - "\n", - "> Layer.__call__ (x)\n", - "\n", - "Alias for `self.energy`. Helps simplify treex's `.init` method" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(Layer.__call__)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L62){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.activation\n", - "\n", - "> Layer.activation (x)\n", - "\n", - "The derivative of the lagrangian is our activation or Gain function `g`. \n", - "\n", - "Defined to operate over input states `x` of shape `self.shape`" - ], - "text/plain": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L62){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.activation\n", - "\n", - "> Layer.activation (x)\n", - "\n", - "The derivative of the lagrangian is our activation or Gain function `g`. \n", - "\n", - "Defined to operate over input states `x` of shape `self.shape`" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(Layer.activation)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L73){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.g\n", - "\n", - "> Layer.g (x)\n", - "\n", - "Alias for `self.activation`" - ], - "text/plain": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L73){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.g\n", - "\n", - "> Layer.g (x)\n", - "\n", - "Alias for `self.activation`" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(Layer.g)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L77){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.init_state\n", - "\n", - "> Layer.init_state (bs:int=None, rng=None)\n", - "\n", - "Initialize the states of this layer, with correct shape.\n", - "\n", - "If `bs` is provided, return tensor of shape (bs, *self.shape), otherwise return self.shape\n", - "By default, initialize layer state to all 0.\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| bs | int | None | Batch size |\n", - "| rng | NoneType | None | If given, initialize states from a normal distribution with this key |" - ], - "text/plain": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/layers.py#L77){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Layer.init_state\n", - "\n", - "> Layer.init_state (bs:int=None, rng=None)\n", - "\n", - "Initialize the states of this layer, with correct shape.\n", - "\n", - "If `bs` is provided, return tensor of shape (bs, *self.shape), otherwise return self.shape\n", - "By default, initialize layer state to all 0.\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| bs | int | None | Batch size |\n", - "| rng | NoneType | None | If given, initialize states from a normal distribution with this key |" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(Layer.init_state)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Convenience Layers" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It is nice to package commonly used lagrangians into their own kind of layers, e.g., `IdentityLayer`s or `SoftmaxLayer`s. We create a helper function to do that in this section." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "def MakeLayer(lagrangian_factory:Callable, \n", - " name:Optional[str]=None): # Name of the new class\n", - " \"\"\"Hack to make it easy to create new layers from `Layer` utility class.\n", - " \n", - " `delegates` modifies the signature for all Layers. We want a different signature for each type of layer.\n", - "\n", - " So we redefine a local version of layer and delegate that for type inference.\n", - " \"\"\"\n", - " global Layer\n", - "\n", - " @delegates(lagrangian_factory, keep=True)\n", - " class Layer(Layer):\n", - " __doc__ = Layer.__doc__\n", - " \n", - " out = partialler(Layer, lagrangian_factory, init_lagrangian=True, name=name)\n", - " out.__doc__ = Layer.__doc__\n", - "\n", - " return out" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "\n", - "# Some reason, docstrings are not showing the new kwargs, and the docs for these are broken. \n", - "IdentityLayer = MakeLayer(LIdentity, \"identity_layer\")\n", - "RepuLayer = MakeLayer(LRepu, \"repu_layer\")\n", - "ReluLayer = MakeLayer(LRelu, \"relu_layer\")\n", - "SoftmaxLayer = MakeLayer(LSoftmax, \"softmax_layer\")\n", - "SigmoidLayer = MakeLayer(LSigmoid, \"sigmoid_layer\")\n", - "TanhLayer = MakeLayer(LTanh, \"tanh_layer\")\n", - "ExpLayer = MakeLayer(LExp, \"exp_layer\")\n", - "RexpLayer = MakeLayer(LRexp, \"rexp_layer\")\n", - "LayerNormLayer = MakeLayer(LLayerNorm, \"layernorm_layer\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Our utility that we use to create these \"convenience layers\" is a bit hacky, but it works by injecting the lagrangian and the expected arguments for the lagrangian into our `Layer` utility. However, the hack loses the ability to inspect docstrings of the original neuron layer." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Energy Analysis" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Most of all, every neuron layer has an **energy**. This is defined by the following equation:\n", - "\n", - "$$E_\\text{layer} = \\sum\\limits_i x_i g_i - \\mathcal{L}(x)$$\n", - "\n", - "The first component is a summation of the elementwise multiplication between $x$ and $g$. The second term is the lagrangian." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let us create a layer with state $x$ and initial state $x_0$. Let us then evolve $x$ over time by simply descending the energy of the neuron layer. Note that this neuron layer is not connected to anything, but we still expect it to reach a fixed point where the energy of the layer reaches a fixed point.\n", - "\n", - "$$\\tau\\frac{dx}{dt} = -\\frac{dE_\\text{layer}}{dx}$$" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-12-02 01:13:11.068186: E external/org_tensorflow/tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:267] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n", - "WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| code-fold: true\n", - "shape = (5,); key = jax.random.PRNGKey(0); k1, k2, key = jax.random.split(key,3)\n", - "layer = ExpLayer(shape,beta=1.).init(k1, jnp.ones(shape))\n", - "x0 = layer.init_state(rng=k2)\n", - "\n", - "@ft.partial(jax.jit, static_argnames=(\"alpha\",))\n", - "def next_x(layer:Layer, # Neuron layer\n", - " x:jnp.ndarray, # Current state\n", - " alpha:float): # Step size\n", - " dEdx = jax.value_and_grad(layer.energy)\n", - " E, dx = dEdx(x)\n", - " next_x = x -alpha * dx\n", - " return E, next_x\n", - "\n", - "x = x0\n", - "Es = []\n", - "for i in range(100):\n", - " E, x = next_x(layer, x, 0.1)\n", - " Es.append(E)\n", - " \n", - "fig, ax = plt.subplots(1)\n", - "ax.plot(np.stack(Es))\n", - "ax.set_title(\"Energy of a disconnected neuron layer over time\")\n", - "ax.set_ylabel(\"Energy\")\n", - "ax.set_xlabel(\"Timesteps\")\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The energy is bounded for any initial neuron state $x$ (though at some point the values are numerically too large for the exponential we are using as the activation function)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| code-fold: true\n", - "x = 100*x0\n", - "Es = []\n", - "for i in range(100):\n", - " E, x = next_x(layer, x, 5e-8)\n", - " Es.append(E)\n", - " \n", - "fig, ax = plt.subplots(1)\n", - "ax.plot(np.stack(Es))\n", - "ax.set_title(\"Large $x_0$, small $dt$\")\n", - "ax.set_ylabel(\"Energy\")\n", - "ax.set_xlabel(\"Timesteps\")\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "import nbdev; nbdev.nbdev_export()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:hamux]", - "language": "python", - "name": "conda-env-hamux-py" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/nbs/02_synapses.ipynb b/nbs/02_synapses.ipynb deleted file mode 100644 index 5153eeb..0000000 --- a/nbs/02_synapses.ipynb +++ /dev/null @@ -1,689 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| default_exp synapses" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "from nbdev.showdoc import *\n", - "from fastcore.test import *\n", - "\n", - "import warnings\n", - "import os\n", - "from IPython.display import display, HTML" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "warnings.filterwarnings('ignore')\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (Hyper)Synapses\n", - "\n", - "> Using Modern Deep Learning operations with Energy." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'HTML' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn [1], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m#|echo:false\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m HTML(\u001b[38;5;124m\"\"\"\u001b[39m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;124m
\u001b[39m\n\u001b[1;32m 4\u001b[0m \u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mHopfield\u001b[39m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;124m
The generalized energy of any hypersynapse as used in the Hopfield paradigm.
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\u001b[39m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;124m\"\"\"\u001b[39m)\n", - "\u001b[0;31mNameError\u001b[0m: name 'HTML' is not defined" - ] - } - ], - "source": [ - "#|echo:false\n", - "HTML(\"\"\"\n", - "
\n", - " \"Hopfield\n", - "
The generalized energy of any hypersynapse.
\n", - "
\n", - "\"\"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Hypersynapses** are the only way that neuron layers can communicate with each other. This generalization of the pairwise synapse from the Hopfield paradigm is now more general than ever before:\n", - "\n", - "\n", - "| Before | HAMUX |\n", - "|--------|------|\n", - "|Synapses connect only one neuron layer to another | Hypersynapses can connect **arbitrary numbers** of layers |\n", - "|Synapses are simple matrix multiplications | Hypersynapses can be almost **any operation**, e.g., convolutions, pooling, attention, $\\ldots$| \n", - "|Synapses are shallow | Hypersynapses can be **deep**! E.g., a sequence of convolutions, pooling, and activation functions |\n", - "\n", - "\n", - "At its core, a hypersynapse's energy is completely defined by its *alignment function* $\\mathcal{F}$ that converts any number of layer activations $(g^1, g^2, \\ldots)$ into a scalar describing its alignment:\n", - "\n", - "$$\n", - " E_{\\text{synapse}} = -\\mathcal{F},\\ \\ \\ \\ \\text{where}\\ \\ \\ \\ \\mathcal{F} (g^1, g^2, \\ldots) \\mapsto \\mathbb{R}.\n", - " $$\n", - " \n", - "The hypersynapse's energy is typically HIGH when all connected layers are \"incongruous\" and LOW when all connected layers are \"aligned\" as defined by its operation." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "import jax\n", - "import jax.numpy as jnp\n", - "from typing import *\n", - "import treex as tx\n", - "from abc import ABC, abstractmethod\n", - "from flax import linen as nn\n", - "from hamux.lagrangians import *\n", - "import functools as ft\n", - "from fastcore.meta import delegates\n", - "from fastcore.utils import *\n", - "from fastcore.basics import *\n", - "from string import ascii_letters\n", - "from flax.linen.pooling import max_pool, avg_pool\n", - "from einops import rearrange" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "All `Synapse`s conform to the following simple API. Just define a `__call__` function to describe the scalar alignment of different activations. Energy is calculated for you." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| exports\n", - "class Synapse(tx.Module, ABC):\n", - " \"\"\"The simple interface class for any synapse. Define an alignment function through `__call__` that returns a scalar.\n", - "\n", - " The energy is simply the negative of this function.\n", - " \"\"\"\n", - "\n", - " def energy(self, *gs):\n", - " return -self(*gs)\n", - "\n", - " @abstractmethod\n", - " def __call__(self, *gs):\n", - " \"\"\"The alignment function of a synapse\"\"\"\n", - " pass" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/synapses.py#L31){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Synapse.energy\n", - "\n", - "> Synapse.energy (*gs)" - ], - "text/plain": [ - "---\n", - "\n", - "[source](https://github.com/bhoov/hamux/blob/main/hamux/synapses.py#L31){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", - "\n", - "### Synapse.energy\n", - "\n", - "> Synapse.energy (*gs)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(Synapse.energy)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Dense Synapse\n", - "\n", - "The simplest of synapses is a dense alignment synapse. In feedforward networks, dense operations take an input and return an output. In HAMUX, dense operations align the activations $g^1 \\in \\mathbb{R}^{D_1}$ and $g^2 \\in \\mathbb{R}^{D_2}$ as follows:\n", - "\n", - "$$\\mathcal{F}_\\text{dense} = g^1_i W_{ij} g^2_j$$\n", - "\n", - "And would be implemented as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| exports\n", - "class SimpleDenseSynapse(Synapse):\n", - " \"\"\"The simplest of dense synapses that connects two layers (with vectorized activations) together\"\"\"\n", - " W: jnp.ndarray = tx.Parameter.node() # treex's preferred way of declaring an attribute as a parameter\n", - " def __call__(self, g1, g2):\n", - " if self.initializing():\n", - " self.W = nn.initializers.normal(0.02)(tx.next_key(), g1.shape + g2.shape)\n", - " return g1 @ self.W @ g2" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-12-02 01:13:30.993496: E external/org_tensorflow/tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:267] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n", - "WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n" - ] - }, - { - "data": { - "text/plain": [ - "DeviceArray(-0.09093504, dtype=float32)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "g1 = jnp.ones(4, dtype=jnp.float32); g2 = jnp.ones(5, dtype=jnp.float32)\n", - "syn = SimpleDenseSynapse().init(jax.random.PRNGKey(0), (g1, g2))\n", - "syn(g1, g2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "When building HAMs in practice, we typically want to follow this pattern: subclass the minimal `Synapse` class and overwrite the `Synapse.__call__` method with our desired alignment function" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We extend this simple concept into a more robust synapse that can linearly connect $>2$ layers and optionally flattens layer activations." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "class DenseSynapse(Synapse):\n", - " \"\"\"A dense synapse that aligns the representations of any number of `gs`.\n", - "\n", - " The one learnable parameter `W` is a tensor with a dimension for each connected layer.\n", - " In the case of 2 layers, this is the traditional learnable matrix synapse.\n", - " In cases `N>2` layers this is a new kind of layer where the learnable parameter is an N dimensional tensor.\n", - "\n", - " By default, this will flatten all inputs as needed to treat all activations as vectors. \n", - " \n", - " The number of layers we can align with this synapse is capped at the number of ranks that JAX stores (<255),\n", - " but you'll probably run out of memory first..\n", - " \"\"\"\n", - "\n", - " W: jnp.ndarray = tx.Parameter.node()\n", - " stdinit: float = 0.02\n", - " flatten_args: bool = True\n", - "\n", - " def __init__(self, stdinit: float = 0.02, flatten_args=True):\n", - " self.stdinit = stdinit\n", - " self.flatten_args = flatten_args\n", - "\n", - " def __call__(self, *gs):\n", - " if self.initializing():\n", - " ndims_total = jnp.sum(jnp.array([len(g.shape) for g in gs]))\n", - " assert (\n", - " ndims_total <= 52\n", - " ), f\"We are limited to english ASCII letters. We cannot connect more than 52 dimensions. Got {ndims_total} total dimensions.\"\n", - " if self.flatten_args:\n", - " gshapes = tuple([g_.size for g_ in gs])\n", - " else:\n", - " gshapes = tuple([g_.shape[-1] for g_ in gs])\n", - " self.W = nn.initializers.normal(self.stdinit)(tx.next_key(), gshapes)\n", - " if self.flatten_args:\n", - " gs = [g_.ravel() for g_ in gs]\n", - " abcs = ascii_letters[: len(gs)]\n", - " einsum_arg = \",\".join([abcs, \",\".join(abcs)]) + \"->\"\n", - " return jnp.einsum(einsum_arg, self.W, *gs)\n", - " else:\n", - " # Design the einsum to take letter positions corresponding to the\n", - " Wabcs = \"\"\n", - " gabcs = []\n", - " i = 0\n", - " for g in gs:\n", - " ndims = len(g.shape)\n", - " Wabcs += ascii_letters[(i - 1) + ndims]\n", - " gabcs.append(ascii_letters[i : i + ndims])\n", - " i = i + ndims\n", - " einsum_arg = \",\".join([Wabcs, \",\".join(gabcs)]) + \"->\"\n", - " return jnp.einsum(einsum_arg, self.W, *gs)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "g1 = jnp.ones(4, dtype=jnp.float32); g2 = jnp.ones(5, dtype=jnp.float32); g3 = jnp.ones(6, dtype=jnp.float32)\n", - "syn = DenseSynapse().init(jax.random.PRNGKey(0), (g1, g2, g3))\n", - "syn(g1, g2, g3)\n", - "assert syn.W.shape == (4,5,6)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can even implement a `DenseSynapse` with a hidden layer (Lagrangian) inside the alignment function. This is how we can implement layers that do not need to hold state through time." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "class DenseTensorSynapseWithHiddenLayer(Synapse):\n", - " \"\"\"A generalized DenseTensorSynapse that has a hidden lagrangian (non-linearity).\n", - "\n", - " We can specify a Lagrangian non-linearity for the hidden neuron layer with tau=0 and shape `(nhid,)`.\n", - "\n", - " The lagrangian can have its own learnable parameters, for example:\n", - "\n", - " ```\n", - " from hamux.core.lagrangians import *\n", - "\n", - " syn = DenseTerminusSynapse(20, hidden_lagrangian=LSoftmax(beta_init=0.2)).init(jax.random.PRNGKey(0), tuple(gs))\n", - " ```\n", - " \"\"\"\n", - "\n", - " W: jnp.ndarray = tx.Parameter.node()\n", - " hidden_lagrangian: Optional[tx.Module] # An already initialized lagrangian function\n", - "\n", - " def __init__(\n", - " self,\n", - " nhid: int,\n", - " num_heads=1,\n", - " stdinit: float = 0.02,\n", - " hidden_lagrangian: tx.Module = LRelu(),\n", - " ):\n", - " self.nhid = nhid\n", - " self.stdinit = stdinit\n", - " self.num_heads = num_heads\n", - " self.hidden_lagrangian = hidden_lagrangian\n", - "\n", - " def __call__(self, *gs):\n", - " if self.initializing():\n", - " assert (\n", - " len(gs) <= 52\n", - " ), \"We are limited to english ASCII letters. We cannot connect more than 50 layers if you include our hidden layer and number of heads\"\n", - " key = tx.next_key()\n", - " gshapes = (self.num_heads, self.nhid) + tuple([g_.size for g_ in gs])\n", - " self.W = nn.initializers.normal(self.stdinit)(key, gshapes)\n", - "\n", - " gs = [g_.ravel() for g_ in gs]\n", - " abcs = ascii_letters[: len(gs)]\n", - " einsum_arg = (\n", - " \",\".join([\"YZ\" + abcs, \",\".join(abcs)]) + \"->YZ\"\n", - " ) # We call the nhid dimension \"Z\" and number of heads \"Y\"\n", - " x = jnp.einsum(einsum_arg, self.W, *gs)\n", - " return self.hidden_lagrangian(x).sum()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "\n", - "class DenseMatrixSynapseWithHiddenLayer(Synapse):\n", - " \"\"\"A modified DenseSynapse that has a hidden lagrangian (non-linearity).\n", - "\n", - " We can specify a Lagrangian non-linearity for the hidden neuron layer with tau=0 and shape `(nhid,)`.\n", - "\n", - " Unlike the DenseTensorSynapseWithHiddenLayer, treat layers as if they are concatenated on the same\n", - " visible layer dimension instead of giving each its own dimension of the tensor space.\n", - " \"\"\"\n", - "\n", - " Ws: List[jnp.ndarray] = tx.Parameter.node()\n", - " hidden_lagrangian: Optional[tx.Module] # An already initialized lagrangian function\n", - "\n", - " def __init__(\n", - " self, nhid: int, stdinit: float = 0.02, hidden_lagrangian: tx.Module = LRelu(), do_ravel=True, do_norm=False,\n", - " ):\n", - " self.nhid = nhid\n", - " self.stdinit = stdinit\n", - " self.hidden_lagrangian = hidden_lagrangian\n", - " self.do_ravel = do_ravel\n", - " self.do_norm = do_norm\n", - "\n", - " def __call__(self, *gs):\n", - " if self.initializing():\n", - " def initw(g):\n", - " if self.do_ravel:\n", - " gsize = g.size\n", - " else:\n", - " gsize = g.shape[-1]\n", - " return nn.initializers.normal(self.stdinit)(tx.next_key(), (gsize, self.nhid))\n", - " self.Ws = [initw(g_) for g_ in gs]\n", - "\n", - " if self.do_ravel:\n", - " gs = [g_.ravel() for g_ in gs]\n", - " if self.do_norm:\n", - " Ws = [W / jnp.sqrt((W**2).sum(0,keepdims=True)) for W in self.Ws]\n", - " else:\n", - " Ws = self.Ws\n", - " hid_state = jnp.stack([g @ W for (W, g) in zip(Ws, gs)]).sum(0)\n", - " return self.hidden_lagrangian(hid_state)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "class ConvSynapse(Synapse):\n", - " \"\"\"A convolutional, binary synapse. Can automatically detect the number of output features from the 2 layers it connects\"\"\"\n", - "\n", - " conv: tx.Conv\n", - " # Delegate arguments to conv EXCEPT the features_out, which we calculate from the output layer\n", - "\n", - " @delegates(tx.Conv)\n", - " def __init__(self, kernel_size: Union[int, Iterable[int]], **kwargs):\n", - " # assert pool_type in [\"max\", \"avg\"]\n", - " self.kernel_size = kernel_size\n", - " conv_kwargs = {\"use_bias\": False}\n", - " conv_kwargs.update(kwargs)\n", - " self.conv_kwargs = conv_kwargs\n", - "\n", - " def example_output(self, g1, features_out=1):\n", - " \"\"\"Test the shape output of the convolutional layer. If unspecified, output features are 1\"\"\"\n", - " conv = tx.Conv(features_out, self.kernel_size, **self.conv_kwargs).init(\n", - " jax.random.PRNGKey(0), g1\n", - " )\n", - " return conv(g1)\n", - "\n", - " def __call__(self, g1, g2):\n", - " \"\"\"The convolutional operation. g2 is assumed to be the \"output\" of the convolution\"\"\"\n", - " if self.initializing():\n", - " features_out = g2.shape[-1]\n", - " self.conv = tx.Conv(\n", - " features_out, self.kernel_size, **self.conv_kwargs\n", - " ).init(tx.next_key(), g1)\n", - " return jnp.multiply(self.conv(g1), g2).sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Or contain pooling" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "class ConvSynapseWithPool(Synapse):\n", - " \"\"\"A convolutional, binary synapse. Can automatically detect the number of output features from the 2 layers it connects\"\"\"\n", - "\n", - " conv: tx.Conv\n", - " # Delegate arguments to conv EXCEPT the features_out, which we calculate from the output layer\n", - "\n", - " @delegates(tx.Conv)\n", - " def __init__(\n", - " self,\n", - " kernel_size: Union[int, Iterable[int]],\n", - " pool_window=(5, 5),\n", - " pool_stride=(2, 2),\n", - " pool_type=\"avg\",\n", - " **kwargs,\n", - " ):\n", - " # assert pool_type in [\"max\", \"avg\"]\n", - " self.kernel_size = kernel_size\n", - " self.conv_kwargs = kwargs\n", - " self.pool_window = pool_window\n", - " self.pool_stride = pool_stride\n", - " self.pool_type = pool_type\n", - "\n", - " self.pooler = max_pool if self.pool_type == \"max\" else avg_pool\n", - " # self.conv = None\n", - "\n", - " def example_output(self, g1, features_out=1):\n", - " \"\"\"Test the shape output of the convolutional layer. If unspecified, output features are 1\"\"\"\n", - " conv = tx.Conv(features_out, self.kernel_size, **self.conv_kwargs).init(\n", - " jax.random.PRNGKey(0), g1\n", - " )\n", - " output = self.pooler(conv(g1), self.pool_window, strides=self.pool_stride)\n", - " return output\n", - "\n", - " def __call__(self, g1, g2):\n", - " \"\"\"The convolutional operation. g2 is assumed to be the \"output\" of the convolution\"\"\"\n", - " if self.initializing():\n", - " features_out = g2.shape[-1]\n", - " self.conv = tx.Conv(\n", - " features_out, self.kernel_size, **self.conv_kwargs\n", - " ).init(tx.next_key(), g1)\n", - " output = self.pooler(self.conv(g1), self.pool_window, strides=self.pool_stride)\n", - " return jnp.multiply(output, g2).sum()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can also create synapses that model attention operations in modern networks" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "class AttentionSynapse(Synapse):\n", - " \"\"\"A generalized synapse of quadratic order, whose update rule looks very similar to the Attention operation of Transformers.\n", - "\n", - " We can specify any Lagrangian non-linearity for the hidden neuron layer (which operates with tau=0), but we default to the Softmax Lagrangian.\n", - "\n", - " To replicate similar configuration to the famous BERT-base models and \"Attention is all you need\" paper:\n", - "\n", - " ```\n", - " zspace = 64\n", - " syn = AttentionSynapse(zspace_dim=zspace, num_heads=12, hidden_lagrangian=LSoftmax(beta=1/jnp.sqrt(zspace)))\n", - " ```\n", - "\n", - " Connecting two layers of shapes: ((Nq, Dq), (Nk, Dk)) and layernorm lagrangians\n", - " \"\"\"\n", - "\n", - " Wk: jnp.ndarray = tx.Parameter.node()\n", - " Wq: jnp.ndarray = tx.Parameter.node()\n", - " hidden_lagrangian: Optional[tx.Module] # An already initialized lagrangian function\n", - " qk_norm: Optional[tx.Module]\n", - "\n", - " def __init__(\n", - " self,\n", - " num_heads: int = 1,\n", - " zspace_dim: int = 64,\n", - " stdinit: float = 0.02,\n", - " hidden_lagrangian: tx.Module = LSoftmax(),\n", - " do_qk_norm: bool = False,\n", - " ):\n", - " self.zspace_dim = zspace_dim\n", - " self.num_heads = num_heads\n", - " self.stdinit = stdinit\n", - " self.hidden_lagrangian = hidden_lagrangian\n", - " self.do_qk_norm = do_qk_norm\n", - "\n", - " def __call__(self, gq, gk):\n", - " \"\"\"Align the queries in gq with the keys in gk\"\"\"\n", - " if self.initializing():\n", - " self.Wq = nn.initializers.normal(self.stdinit)(\n", - " tx.next_key(), (gq.shape[-1], self.num_heads, self.zspace_dim)\n", - " )\n", - " self.Wk = nn.initializers.normal(self.stdinit)(\n", - " tx.next_key(), (gk.shape[-1], self.num_heads, self.zspace_dim)\n", - " )\n", - " if self.do_qk_norm:\n", - " self.qk_norm = tx.LayerNorm().init(\n", - " tx.next_key(), jnp.ones(self.zspace_dim)\n", - " )\n", - "\n", - " if len(gq.shape) == 1:\n", - " gq = gq[..., None, :]\n", - " if len(gk.shape) == 1:\n", - " gk = gk[..., None, :]\n", - " if len(gq.shape) > 2:\n", - " gq = rearrange(gq, \"... d -> (...) d\")\n", - " if len(gk.shape) > 2:\n", - " gk = rearrange(gk, \"... d -> (...) d\")\n", - " Q = jnp.einsum(\"qd,dhz->qhz\", gq, self.Wq)\n", - " K = jnp.einsum(\"kd,dhz->khz\", gk, self.Wk)\n", - " # QK = jnp.einsum(\"qhz,khz->hqk\", Q, K)\n", - " if self.do_qk_norm:\n", - " Q = self.qk_norm(Q)\n", - " K = self.qk_norm(K)\n", - " QK = jnp.einsum(\"qhz,khz->hqk\", Q, K)\n", - "\n", - " # print(\"MAX QK: \", QK.max())\n", - " # print(\"MIN QK: \", QK.min())\n", - " # , QK.min(), gk.max(), gq.max())\n", - " attn = self.hidden_lagrangian(QK) # h,q\n", - " return attn.sum()\n", - "\n", - "\n", - "class SelfAttentionSynapse(AttentionSynapse):\n", - " \"\"\"A special case of the AttentionSynapse where both inputs are of the same layer\"\"\"\n", - "\n", - " def __call__(self, g):\n", - " return super().__call__(g, g)\n", - "\n", - " \n", - "class BinaryMixerSynapse(Synapse):\n", - " \"\"\"A generalized binary synapse of quadratic order. This synapse is very similar to the Attention synapse but uses a single\n", - " weight matrix instead of a query and key matrix.\n", - "\n", - " We can specify any Lagrangian non-linearity for the hidden neuron layer (which operates with tau=0), but we default to the Softmax Lagrangian.\n", - "\n", - " \"\"\"\n", - "\n", - " W: jnp.ndarray = tx.Parameter.node()\n", - " hidden_lagrangian: Optional[tx.Module] # An already initialized lagrangian function\n", - "\n", - " def __init__(\n", - " self,\n", - " num_heads: int = 1,\n", - " zspace_dim: int = 64,\n", - " stdinit: float = 0.02,\n", - " hidden_lagrangian: tx.Module = LSoftmax(),\n", - " ):\n", - " self.num_heads = num_heads\n", - " self.zspace_dim=zspace_dim\n", - " self.stdinit = stdinit\n", - " self.hidden_lagrangian = hidden_lagrangian\n", - "\n", - " def __call__(self, ga, gb):\n", - " \"\"\"Align the activations ga with gb\"\"\"\n", - " if self.initializing():\n", - " self.W = nn.initializers.normal(self.stdinit)(\n", - " tx.next_key(), (self.num_heads, self.zspace_dim, ga.shape[-1], gb.shape[-1])\n", - " )\n", - "\n", - " if len(ga.shape) == 1:\n", - " ga = ga[...,None,:]\n", - " if len(gb.shape) == 1:\n", - " gb = gb[...,None,:]\n", - " if len(ga.shape) > 2:\n", - " ga = rearrange(ga, \"... d -> (...) d\")\n", - " if len(gb.shape) > 2:\n", - " gb = rearrange(gb, \"... d -> (...) d\")\n", - "\n", - " AB = jnp.einsum(\"hzab,...a,...b->hz\", self.W, ga, gb)\n", - " attn = self.hidden_lagrangian(AB) # h\n", - " return attn.sum()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "import nbdev; nbdev.nbdev_export()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:hamux]", - "language": "python", - "name": "conda-env-hamux-py" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/nbs/03_ham.ipynb b/nbs/03_ham.ipynb deleted file mode 100644 index 3d43a7d..0000000 --- a/nbs/03_ham.ipynb +++ /dev/null @@ -1,1059 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| default_exp ham" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "from nbdev.showdoc import *\n", - "from fastcore.test import *\n", - "import warnings\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import os\n", - "from IPython.display import display, HTML" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "warnings.simplefilter('ignore')\n", - "np.set_printoptions(precision=3)\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# HAM\n", - "\n", - "> Assembling layers and synapses into a single system governed by an energy function" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\"HAMUX\n" - ], - "text/plain": [ - "" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#|echo:false\n", - "HTML(\"\"\"\n", - "\"HAMUX\n", - "\"\"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We have now provided the two primary components: `layers` and `synapses`. This module assembles those together into a single network that is governed by an energy function" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export \n", - "import jax\n", - "import jax.numpy as jnp\n", - "from typing import *\n", - "import treex as tx\n", - "from hamux.layers import Layer\n", - "from hamux.synapses import Synapse\n", - "import jax.tree_util as jtu\n", - "from hamux.utils import pytree_save, pytree_load, to_pickleable, align_with_state_dict\n", - "import pickle\n", - "import functools as ft\n", - "from fastcore.utils import *\n", - "from abc import ABC, abstractmethod, abstractproperty\n", - "import hypernetx as hnetx" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## HAM Basics\n", - "\n", - "We connect `layers` and `synapses` in a [hypergraph](https://en.wikipedia.org/wiki/Hypergraph) to describe the energy function. A hypergraph is a generalization of the familiar graph in that edges (synapses) can connect multiple nodes (layers). This graph -- complete with the operations of the synapses and the activation behavior of the layers -- fully defines the energy function for a given collection of neuron states." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|export\n", - "class HAM(tx.Module):\n", - " layers: List[Layer]\n", - " synapses: List[Synapse]\n", - " connections: List[Tuple[Tuple, int]]\n", - "\n", - " def __init__(self, layers, synapses, connections):\n", - " self.layers = layers\n", - " self.synapses = synapses\n", - " self.connections = connections\n", - "\n", - " @property\n", - " def n_layers(self): return len(self.layers)\n", - " @property\n", - " def n_synapses(self): return len(self.synapses)\n", - " @property\n", - " def n_connections(self): return len(self.connections)\n", - " @property\n", - " def layer_taus(self): return [layer.tau for layer in self.layers]\n", - " def alphas(self, dt): return [dt / tau for tau in self.layer_taus]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|export\n", - "@patch\n", - "def activations(self:HAM, \n", - " xs:jnp.ndarray): # Collection of states for each layer\n", - " \"\"\"Turn a collection of states into a collection of activations\"\"\"\n", - " gs = [self.layers[i].g(xs[i]) for i in range(len(xs))]\n", - " return gs" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#|export\n", - "@patch\n", - "def layer_energy(self:HAM,\n", - " xs:jnp.ndarray): # Collection of states for each layer\n", - " \"\"\"The total contribution of the layers' contribution to the energy of the HAM\"\"\"\n", - " energies = jnp.stack([self.layers[i].energy(x) for i, x in enumerate(xs)])\n", - " return jnp.sum(energies)\n", - "\n", - "@patch\n", - "def synapse_energy(self:HAM,\n", - " gs:jnp.ndarray): # Collection of activations of each layer\n", - " \"\"\"The total contribution of the synapses' contribution to the energy of the HAM.\n", - " \n", - " A function of the activations `gs` rather than the states `xs`\n", - " \"\"\"\n", - " def get_energy(lset, k):\n", - " mygs = [gs[i] for i in lset]\n", - " synapse = self.synapses[k]\n", - " return synapse.energy(*mygs)\n", - " energies = jnp.stack([get_energy(lset, k) for lset, k in self.connections])\n", - " return jnp.sum(energies)\n", - "\n", - "@patch\n", - "def energy(self:HAM,\n", - " xs:jnp.ndarray): # Collection of states for each layer\n", - " \"\"\"The complete energy of the HAM\"\"\"\n", - " gs = self.activations(xs)\n", - " energy = self.layer_energy(xs) + self.synapse_energy(gs)\n", - " return energy" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As is typical for JAX frameworks, the parameters of HAMs need to be initialized. Unlike other machine learning libraries, the *states* of each *layer* -- that is, the dynamical variables of our system -- also need to be initialized. The notation $\\mathbf{x}$ indicates the collection of all states from each layer, and $x^\\alpha$ indicates that we are referring to the state of layer at index $\\alpha$ in our collection. \n", - "\n", - "We provide this functionality with the following helper functions:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "@patch\n", - "def init_states(self:HAM, \n", - " bs=None, # Batch size of the states to initialize, if needed\n", - " rng=None): # RNG seed for random initialization of the states, if non-zero initializations are desired\n", - " \"\"\"Initialize the states of every layer in the network\"\"\"\n", - " if rng is not None:\n", - " keys = jax.random.split(rng, self.n_layers)\n", - " return [layer.init_state(bs, rng=key) for layer, key in zip(self.layers, keys)]\n", - " return [layer.init_state(bs) for layer in self.layers]\n", - "\n", - "@patch\n", - "def init_states_and_params(self:HAM, \n", - " param_key, # RNG seed for random initialization of the parameters\n", - " bs=None, # Batch size of the states to initialize, if needed\n", - " state_key=None): # RNG seed for random initialization of the states, if non-zero initializations are desired\n", - " \"\"\"Initialize the states and parameters of every layer and synapse in the network\"\"\"\n", - " # params don't need a batch size to initialize\n", - " params = self.init(param_key, self.init_states(), call_method=\"energy\")\n", - " states = self.init_states(bs, rng=state_key)\n", - " return states, params" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We build and test the following small 3 layer HAM network throughout this notebook" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from hamux.layers import *\n", - "from hamux.synapses import *" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-12-02 01:13:47.509827: E external/org_tensorflow/tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:267] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n", - "WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n" - ] - } - ], - "source": [ - "layers = [\n", - " TanhLayer((2,)),\n", - " ReluLayer((3,)),\n", - " SoftmaxLayer((4,)),\n", - "]\n", - "\n", - "synapses = [\n", - " DenseSynapse(),\n", - " DenseSynapse(),\n", - "]\n", - "\n", - "connections = [\n", - " ([0,1], 0),\n", - " ([1,2],1),\n", - "]\n", - "ham = HAM(layers, synapses, connections)\n", - "\n", - "# Initialize states and parameters from specified layer shapes\n", - "xs, ham = ham.init_states_and_params(jax.random.PRNGKey(0), state_key=jax.random.PRNGKey(1));" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NLayers: 3\n", - "NSynapses: 2\n", - "NConnections: 2\n", - "Taus of each layer: [1.0, 1.0, 1.0]\n" - ] - } - ], - "source": [ - "print(\"NLayers: \", ham.n_layers)\n", - "print(\"NSynapses: \", ham.n_synapses)\n", - "print(\"NConnections: \", ham.n_connections)\n", - "print(\"Taus of each layer: \", ham.layer_taus)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The energy of a HAM is fully defined by the individual energies of its layers and synapses.\n", - "\n", - "$$E_\\text{HAM} = E_\\text{Layers} + E_\\text{Synapses}$$" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "x0: (2,)\n", - "x1: (3,)\n", - "x2: (4,)\n", - "W0: (2, 3)\n", - "W1: (3, 4)\n" - ] - } - ], - "source": [ - "#| code-fold: true\n", - "print(\"\\n\".join([f\"x{i}: {x.shape}\" for i,x in enumerate(xs)])) # The dynamic variables\n", - "print(\"\\n\".join([f\"W{i}: {S.W.shape}\" for i,S in enumerate(ham.synapses)])) # The dynamic variables" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "DeviceArray(0.071, dtype=float32)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "E_L = ham.layer_energy(xs); E_L" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "DeviceArray(-0.033, dtype=float32)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "gs = ham.activations(xs)\n", - "E_S = ham.synapse_energy(gs); E_S" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "test_eq(ham.energy(xs), E_L+E_S)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The update rule for each of the layer states is simply defined as follows:\n", - "\n", - "$$\\tau \\frac{dx^\\alpha}{dt} = -\\frac{dE_\\text{system}}{dg^\\alpha}$$\n", - "\n", - "JAX is wonderful. Autograd does this accurately and efficiently for us." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "@patch\n", - "def dEdg(self:HAM, \n", - " xs:jnp.ndarray):\n", - " \"\"\"Calculate the gradient of system energy wrt. the activations\n", - "\n", - " Notice that we use an important mathematical property of the Legendre transform to take a mathematical shortcut,\n", - " where dE_layer / dg = x\n", - " \"\"\"\n", - " gs = self.activations(xs)\n", - " return jtu.tree_map(\n", - " lambda x, s: x + s, xs, jax.grad(self.synapse_energy)(gs)\n", - " )\n", - "\n", - "@patch\n", - "def updates(self:HAM,\n", - " xs:jnp.ndarray): # Collection of states for each layer\n", - " \"\"\"The negative of our dEdg, computing the update direction each layer should descend\"\"\"\n", - " return jtu.tree_map(lambda dg: -dg, self.dEdg(xs))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's observe the energy descent in practice" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "@jax.jit\n", - "def step(ham, xs, dt):\n", - " energy = ham.energy(xs)\n", - " updates = ham.updates(xs)\n", - " alphas = [dt / tau for tau in ham.layer_taus]\n", - " next_states = jtu.tree_map(lambda x, u, alpha: x + alpha*u, xs, updates, alphas)\n", - " return energy, next_states\n", - "\n", - "energies = []\n", - "allx = []\n", - "x = ham.init_states(rng=jax.random.PRNGKey(5))\n", - "for i in range(100):\n", - " energy, x = step(ham, x, 0.1)\n", - " energies.append(energy)\n", - " allx.append(x)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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DuvbaaxUUdPzLj3Hjxrk8tyQNGjRIqampLhef/PTTT/rhhx9c+vUq87///U+BgYG6+eabXbbPmDFDxhjn6z/ttNN09tlnu4zQlJWV6e2339aFF17o7D196623FBsbqz/96U/O133o0CF169ZNUVFRFUYpWrdurcGDB1db46n485//7Px1XFycOnTooMjISI0ePdq5vUOHDoqLi3P5Kvett95Sv3791KhRI5fXMWjQIJWVlembb76pdS3/+9//JMnlK1Gp/L2WVOGr2pq+N2vXrtWBAwd0ww03uPQ6Dx8+XB07dqzwuLVx2WWXKTExscb7x8fHa/Hixfroo4/0wAMPqHHjxsrLy6vz85/Y0+z4s9SvXz8VFBS4fN0/YcIErVq1Stu3b3duW7BggZo3b67+/ftLkhYvXqysrCyNHTvW5ZwGBgaqZ8+elY6gXX/99bWqt7LPkMWLF+vMM8+ssO/hw4e1aNEijR071rntsssuc349X5Urr7xS27Zt05o1a5z/d1ebQ35+vhITE5WYmKh27drptttuU58+ffTBBx/IZrM59zvxvJSUlOjw4cNq166d4uLitH79+gqPe91117kc369fP5WVlWnXrl2SpC+++ELFxcW66aabXPb7/YWsUvmfox49eqhv377ObVFRUbruuuu0c+fOCu04EyZMcBlN7dmzp4wxuvrqq13269mzp3bv3q3S0tIq35+AgAD17t3b+ed/8+bNOnz4sGbOnCljjFasWCGpfBS4c+fOzm9aavu5eKLPPvtMTZs21UUXXeTcFhYWpmuvvbbS/aOiolw+90NCQtSjRw+Xz7eqOEZ0Fy1apIKCgpPuD/ej1QENqkePHjW6uK1FixYuPzuCqKNXa9u2bTLG6N5779W9995b6WMcOHBATZs2df78+9kkHH8h/H5GiaCgIJevY6XyD+Nx48bp+eefV0FBgSIiIrRgwQKFhYXp8ssvr/a17Nq1S6mpqYqOjnbZ3qlTJ5c6pPLAf/fdd2vPnj1q2rSpvvrqKx04cEBXXHGFc5+tW7cqOztbSUlJVb7uE1U2i4a7hIWFVQhtsbGxatasmctfro7tJ/babd26VT/88EOVoe/3r6Mmdu3apYCAgArnNCUlRXFxcS7vtVTz98ZxXGWtEB07dtS3335b61prW4NDSEiIBg0aJEkaMWKEBg4cqD59+igpKUkjRoxQWVlZhd7O+Pj4Ki/o2bRpk/76179qyZIlysnJcbnvxJ7DK664QtOmTdOCBQs0a9YsZWdn6+OPP9b06dOd53rr1q2SpPPPP7/S54qJiXH5OSgoyKXfviaq+gxx/APqRG+++aZKSkrUtWtXbdu2zbm9Z8+eWrBggW688cZKn6Nr167q2LGjFi5cqLi4OKWkpFT5mmorLCxMH330kaTyawQee+wx54WaJzp69KjmzJmjl19+WXv27HG5HqCyXtCTfWY6fg+3b9/eZb/ExMQK/9DftWuXevbsWeE5TvzMOnHquN8/tyPcNW/evMJ2u92u7OzsCu1tJ+rXr5/uv/9+HT16VMuWLVOTJk10zjnn6KyzztKyZcv0pz/9Sd9++63LP65r+7n4+9fbtm3bCp9ZVc02VNnnW6NGjfTDDz9U+RwOrVu31q233qqnnnpKCxYsUL9+/XTRRRfpqquuos2hgRB84ZFOHJk9kePD33Hx02233VbliN3vP7RO9Wr9CRMm6PHHH9f777+vsWPHauHChRoxYoRbP6yuuOIK3XXXXXrrrbc0bdo0/fe//1VsbKyGDBni3MdutyspKanKqY9+HyTrc5aCqs7Tyc6fVP46/vSnP1W4et7htNNOq3Ndv/9LqSr18d7YbDaX1+lw4sVi7qyhd+/eatKkiRYsWKARI0Zo9+7dFcL00qVLK+0BzsrKUv/+/RUTE6MHHnhAbdu2VVhYmNavX68777zT5SLDRo0aacSIEc7g+/bbb6uoqMhl5Mux/6uvvurSp+5w4jcrUvnUXgEB9ffFo+PPSJ8+fSq9/9dff1WbNm0qve/KK6/U888/r+joaF1xxRVuqzMwMND5DxdJGjx4sDp27KgpU6a4XJh700036eWXX9a0adPUq1cvxcbGymazacyYMZVe/FmTP3P15VQ+ByrTt29flZSUaMWKFVq2bJnzG79+/fpp2bJl2rJliw4ePOjcLtX+c/FUnOp7/eSTT2rSpEn64IMP9Pnnn+vmm2/WnDlztHLlylr/QxC1R/CFV3L8ZRUcHOzyl0httGzZUlL56PGJsymUlpZq586dFb467dy5s7p27aoFCxaoWbNmSk9P1zPPPFOj5/niiy+Um5vrMurr+BrZUYdUPhrQo0cP50VE7777ri655BKFhoY692nbtq2++OIL9enTx+3BraaB0R3atm2rvLy8Op+/yrRs2VJ2u11bt251jk5J5RfrZGVlubzXtX1cqfxiuN+P/KWlpbk8bqNGjSr9yvP3o83uVFhY6BwFTElJ0eLFi13uP+ussyo97quvvtLhw4f17rvvulwktGPHjkr3nzBhgi6++GKtWbNGCxYsUNeuXXXGGWc472/btq0kKSkpya3ntS527Nih7777TlOnTnW2YjjY7XaNHz9eCxcu1F//+tdKj7/yyis1a9Ys7du3T6+++mq91dmkSRNNnz5ds2fP1sqVK/WHP/xBkvT2229r4sSJevLJJ537FhYW1nn2Dsfv0a1bt7qE/YMHD1aY9aBly5ZKS0ur8BiVfWbVhx49eigkJETLli3TsmXLdPvtt0sqv/DwpZde0pdffun82eFUPhdbtmypn3/+WcYYl8/AE78lqK2TfZZ26dJFXbp00V//+ld999136tOnj1544QX97W9/q/Nzombo8YVXSkpK0oABA/TPf/5T+/btq3B/TVay6t69uxISEvTSSy+59JwtWLCgwl8EDuPHj9fnn3+uuXPnKiEhodqJ8B2GDRumsrIyPfvssy7b//73v8tms1V4jCuuuEIrV67Uf/7zHx06dMilzUGSRo8erbKyMj344IMVnqu0tLTOfzFKUmRkZINNqTN69GitWLFCixYtqnBfVlZWtX2AVRk2bJgkVZgR4qmnnpKkOl+V3717dyUlJemFF15wmY7p008/1ebNm10et23bts4RKYfvv/9ey5cvr9NzO+Tn51faE/jOO+/oyJEjzq//w8LCNGjQIJfb77/KdnCMXJ04UlVcXKz/+7//q3T/oUOHqnHjxnr00Uf19ddfV+hvHzx4sGJiYvTwww9XOstCQ64w5xj5u+OOOzRq1CiX2+jRo9W/f/9qF4xo27at5s6dqzlz5qhHjx7VPteWLVuUnp5e51pvuukmRURE6JFHHnFuCwwMrDCC+Mwzz1T5zcHJDBo0SMHBwXrmmWdcHrey2VOGDRum1atXO/tppfLffy+++KJatWql008/vU411FRYWJjOPfdcvf7660pPT3cZ8T169KiefvpptW3bVk2aNHEecyqfi4MHD9aePXtcRtwLCwv10ksv1fk1OOaJ/v3z5uTkVPhs69KliwICAk461RvcgxFfNKhPP/3U5YIZh969e1f5lWNVnnvuOfXt21ddunTRtddeqzZt2mj//v1asWKFfvvtN33//ffVHh8SEqL7779fN910k84//3yNHj1aO3fu1Lx58yrt95LKR4HuuOMOvffee7r++utrtJLZhRdeqPPOO0/33HOPdu7cqbPOOkuff/65PvjgA02bNs05SuYwevRo3XbbbbrtttsUHx9fYeSsf//+mjJliubMmaONGzfqggsuUHBwsLZu3aq33npL//jHP1zm/K2Nbt266c0339Stt96qc889V1FRUbrwwgvr9Fgnc/vtt+vDDz/UiBEjNGnSJHXr1k35+fn68ccf9fbbb2vnzp1q3LhxrR7zrLPO0sSJE/Xiiy86v8ZfvXq15s+fr0suuaTSeZJrIjg4WI8++qgmT56s/v37a+zYsc7pzFq1aqXp06c797366qv11FNPafDgwbrmmmt04MABvfDCCzrjjDMq9NDWxtatWzVo0CBdccUV6tixowICArR27Vq99tpratWqVaXzTJ9M79691ahRI02cOFE333yzbDabXn311Sq/sg0ODtaYMWP07LPPKjAw0OWiMam8h/f555/X+PHjdc4552jMmDFKTExUenq6PvnkE/Xp06fCPwDry4IFC3T22WdX6DN1uOiii3TTTTdp/fr1Oueccyrdp6bvaadOndS/f/9K53utiYSEBE2ePFn/93//p82bN6tTp04aMWKEXn31VcXGxur000/XihUr9MUXX1TbG1udxMRE3XbbbZozZ45GjBihYcOGacOGDfr0008r/DmbOXOmXn/9dQ0dOlQ333yz4uPjNX/+fO3YsUPvvPNOvbanOPTr10+PPPKIYmNj1aVLF0nlAx4dOnRQWlqaJk2a5LL/qXwuTpkyRc8++6zGjh2rW265xdk65LiQtS7fhLVt21ZxcXF64YUXFB0drcjISPXs2VPff/+9pk6dqssvv1ynnXaaSktL9eqrryowMFCXXXZZrZ8HddDwE0nAH51sKiLHlC+OKZ4ef/zxCo+h302HZYwx27dvNxMmTDApKSkmODjYNG3a1IwYMcK8/fbbFZ57zZo1ldb29NNPm5YtW5rQ0FDTo0cPs3z5ctOtWzczZMiQSvcfNmyYkWS+++67Gr/+3NxcM336dJOammqCg4NN+/btzeOPP+4yrdCJ+vTpU+m0XCd68cUXTbdu3Ux4eLiJjo42Xbp0MXfccYfZu3evc5+WLVua4cOH17jOvLw8c+WVV5q4uDgjyTn1UFXTmf1+OjFjyqf7qWxaqcpqyc3NNXfddZdp166dCQkJMY0bNza9e/c2TzzxhMv0SJWp6vlLSkrM7NmzTevWrU1wcLBp3ry5ueuuu1ym5qqqnpN58803TdeuXU1oaKiJj48348aNM7/99luF/V577TXTpk0bExISYs4++2yzaNGiKqczq+z3emUOHjxorrvuOtOxY0cTGRlpQkJCTPv27c20adPMwYMHa/QYlU1ntnz5cvOHP/zBhIeHm9TUVHPHHXc4p+87cRonh9WrVxtJ5oILLqjyeZYuXWoGDx5sYmNjTVhYmGnbtq2ZNGmSWbt2rXOfqs7fyWqv6s/xib/v1q1bZySZe++9t8rH27lzp5Fkpk+fboxxnc6sOqpkOjP9bvrDqlT3mrdv324CAwOd04odOXLETJ482TRu3NhERUWZwYMHmy1btpiWLVu6TD1W1fvimGrsxHNYVlZmZs+ebZo0aWLCw8PNgAEDzE8//VThMR31jBo1ysTFxZmwsDDTo0cP8/HHH1f6HL+fmquqmmr6HhtjzCeffGIkVZgS7c9//rORZP79739XelxNPhcrm3Lw119/NcOHDzfh4eEmMTHRzJgxw7zzzjtGklm5cqXLsZV9vv3+z7cx5dNwnn766SYoKMj5+fnrr7+aq6++2rRt29aEhYWZ+Ph4c95555kvvvjipO8J3MNmTAN0vgNexG63KzExUSNHjqz0q65LL71UP/744yn1fwHe6vvvv9fZZ5+tV155RePHj7e6HKDezJ07V9OnT9dvv/3mMkMQvBs9vvBrhYWFFb7WfeWVV5SZmVnpVfD79u3TJ598wl/48FsvvfSSoqKiNHLkSKtLAdzm6NGjLj8XFhbqn//8p9q3b0/o9TH0+MKvrVy5UtOnT9fll1+uhIQErV+/Xv/+97/VuXNnl/l5d+zYoeXLl+tf//qXgoODNWXKFAurBhreRx99pJ9//lkvvviic1lqwFeMHDlSLVq00Nlnn63s7Gy99tpr2rJlS7UXQMI7EXzh11q1aqXmzZvr6aefVmZmpuLj4zVhwgQ98sgjLhP+f/3115o8ebJatGih+fPnVzpHKeDLbrrpJu3fv1/Dhg3T7NmzrS4HcKvBgwfrX//6lxYsWKCysjKdfvrpeuONNyrMqgPvR48vAAAA/AI9vgAAAPALBF8AAAD4BXp8T8Jut2vv3r2Kjo5u0OVcAQAAUDPGGOXm5io1NbXaRVYIviexd+/eKlf+AQAAgOfYvXu3mjVrVuX9BN+TiI6OllT+RsbExFhcDQAAAH4vJydHzZs3d+a2qhB8T8LR3hATE0PwBQAA8GAna0vl4jYAAAD4BYIvAAAA/ALBFwAAAH6B4AsAAAC/QPAFAACAXyD4AgAAwC8QfAEAAOAXCL4AAADwCwRfAAAA+AWCLwAAAPwCwRcAAAB+geALAAAAv0DwBQAAgF8g+AIAAMAvEHwBAADgFwi+AAAA8AsEXwAAAPgFgi8AAAD8AsEXAAAAfoHgCwAAAL9A8AUAAIBfIPgCAADALxB8AQAA4BcIvh6kzG70zS8H9c6631RSZre6HAAAAJ8SZHUBOM4m6ep5a1RqN+rdLkFNYsOtLgkAAMBnMOLrQQICbGocFSpJOphbZHE1AAAAvoXg62ESowm+AAAA9YHg62EIvgAAAPWD4OthEml1AAAAqBcEXw/jHPHNI/gCAAC4E8HXw9DqAAAAUD8Ivh6G4AsAAFA/CL4ehlYHAACA+kHw9TBc3AYAAFA/CL4exjHiW1BcpvyiUourAQAA8B0EXw8TGRqkiJBASYz6AgAAuBPB1wPR5wsAAOB+BF8PRJ8vAACA+xF8PRBTmgEAALgfwdcDJRF8AQAA3I7g64EY8QUAAHA/gq8H4uI2AAAA9yP4eiBH8D2QW2hxJQAAAL6D4OuBEqPCJNHqAAAA4E4EXw/kGPE9lFcsu91YXA0AAIBvIPh6oISoEElSmd3oSEGxxdUAAAD4BoKvBwoODFB8ZHn45QI3AAAA9yD4eihWbwMAAHAvgq+HYi5fAAAA9yL4eiiCLwAAgHsRfD0UwRcAAMC9CL4eytnjy8VtAAAAbkHw9VCM+AIAALgXwddDEXwBAADci+DroZzBl1YHAAAAtyD4eihHj29WQYmKSsssrgYAAMD7EXw9VFxEsIIDbZKkw3ksWwwAAHCqCL4eymazsXobAACAGxF8PRgXuAEAALgPwdeDcYEbAACA+xB8PZgj+B7IIfgCAACcKoKvBzu+eluhxZUAAAB4P4KvB6PHFwAAwH0Ivh6M4AsAAOA+BF8PxsVtAAAA7uM1wTczM1Pjxo1TTEyM4uLidM011ygvL69GxxpjNHToUNlsNr3//vv1W6gbJUaFSSof8TXGWFwNAACAd/Oa4Dtu3Dht2rRJixcv1scff6xvvvlG1113XY2OnTt3rmw2Wz1X6H6No0MkSYUlduUVlVpcDQAAgHcLsrqAmti8ebM+++wzrVmzRt27d5ckPfPMMxo2bJieeOIJpaamVnnsxo0b9eSTT2rt2rVq0qRJQ5XsFhEhQYoKDVJeUakO5hYpOizY6pIAAAC8lleM+K5YsUJxcXHO0CtJgwYNUkBAgFatWlXlcQUFBbryyiv13HPPKSUlpUbPVVRUpJycHJeblbjADQAAwD28IvhmZGQoKSnJZVtQUJDi4+OVkZFR5XHTp09X7969dfHFF9f4uebMmaPY2FjnrXnz5nWu2x2Oz+VL8AUAADgVlgbfmTNnymazVXvbsmVLnR77ww8/1JIlSzR37txaHXfXXXcpOzvbedu9e3ednt9dGPEFAABwD0t7fGfMmKFJkyZVu0+bNm2UkpKiAwcOuGwvLS1VZmZmlS0MS5Ys0fbt2xUXF+ey/bLLLlO/fv301VdfVXpcaGioQkNDa/oS6h3BFwAAwD0sDb6JiYlKTEw86X69evVSVlaW1q1bp27dukkqD7Z2u109e/as9JiZM2fqz3/+s8u2Ll266O9//7suvPDCUy++gRB8AQAA3MMrZnXo1KmThgwZomuvvVYvvPCCSkpKNHXqVI0ZM8Y5o8OePXs0cOBAvfLKK+rRo4dSUlIqHQ1u0aKFWrdu3dAvoc7o8QUAAHAPr7i4TZIWLFigjh07auDAgRo2bJj69u2rF1980Xl/SUmJ0tLSVFBQYGGV7seILwAAgHt4xYivJMXHx2vhwoVV3t+qVauTrm7mjaufEXwBAADcw2tGfP1V0rHgezi/WGV27wvuAAAAnoLg6+HiI0Nks0lldqMjBcVWlwMAAOC1CL4eLigwQAmRIZKkAzm0OwAAANQVwdcLNGZmBwAAgFNG8PUCXOAGAABw6gi+XoDgCwAAcOoIvl6A4AsAAHDqCL5egNXbAAAATh3B1wscH/EttLgSAAAA70Xw9QKO4HuAVgcAAIA6I/h6geSYMEnSQebxBQAAqDOCrxdwLFucW1Sq/KJSi6sBAADwTgRfLxAVGqSIkEBJtDsAAADUFcHXC9hsNme7w4EcLnADAACoC4Kvl3Bc4LafEV8AAIA6Ifh6CUZ8AQAATg3B10skM6UZAADAKSH4egnHiO9+RnwBAADqhODrJZJijvX4EnwBAADqhODrJZKiHT2+tDoAAADUBcHXSyTH0OMLAABwKgi+XiLpWI9vXlGp8li9DQAAoNYIvl4iKjRIkY7V2+jzBQAAqDWCrxdxzuVLuwMAAECtEXy9iHP1NkZ8AQAAao3g60WOr97GiC8AAEBtEXy9SDJz+QIAANQZwdeL0OMLAABQdwRfL0KPLwAAQN0RfL0II74AAAB1R/D1IscvbmPEFwAAoLYIvl4k6VirQ35xGau3AQAA1BLB14tEhgYpKjRIEn2+AAAAtUXw9TJJx6Y0Yy5fAACA2iH4epnkaMcFboz4AgAA1AbB18sksYgFAABAnRB8vYxjZof9tDoAAADUCsHXyzhmdmAuXwAAgNoh+HqZJOeIL60OAAAAtUHw9TLJjhFfgi8AAECtEHy9zInLFhtjLK4GAADAexB8vYxjVocCVm8DAACoFYKvl4kICVK0c/U2LnADAACoKYKvFzq+eht9vgAAADVF8PVCJ/b5AgAAoGYIvl7IMZcvU5oBAADUHMHXC7F6GwAAQO0RfL1QkrPVgRFfAACAmiL4eiHnssWM+AIAANQYwdcLOVsdGPEFAACoMYKvF0qOOT7iy+ptAAAANUPw9UJJ0eUjvkdLypTL6m0AAAA1QvD1QuEhgYoOK1+9jUUsAAAAaobg66WY0gwAAKB2CL5eytnnywVuAAAANULw9VKOPl9GfAEAAGqG4OulkmJYthgAAKA2CL5eKjnasXobI74AAAA1QfD1UknOuXwZ8QUAAKgJgq+XYlYHAACA2iH4eqlk58VthazeBgAAUAMEXy/laHUoKrUrp5DV2wAAAE6G4OulwoIDFcPqbQAAADVG8PVi9PkCAADUHMHXizmCL6u3AQAAnBzB14slRZf3+WbQ6gAAAHBSBF8vlhx7bMSXVgcAAICTIvh6sZRjrQ4Z2Yz4AgAAnAzB14ulHBvx3UerAwAAwEkRfL2YY8R3PyO+AAAAJ0Xw9WJNYo/P6lBaZre4GgAAAM9G8PViCVGhCgywyW6kQ3nFVpcDAADg0Qi+XiwwwKbkY1Oa7cs+anE1AAAAno3g6+UcU5oxswMAAED1CL5eztHnyyIWAAAA1SP4erlk5vIFAACoEYKvl2PEFwAAoGYIvl7OMeK7jxFfAACAahF8vVyT2HBJ0n5GfAEAAKpF8PVyKSeM+BpjLK4GAADAcxF8vVxSTPk8vsWldmUVlFhcDQAAgOci+Hq5sOBAxUeGSKLPFwAAoDoEXx/gaHegzxcAAKBqBF8fkBLLzA4AAAAnQ/D1ASnM5QsAAHBSBF8fkOJcve2oxZUAAAB4LoKvDzg+4ltkcSUAAACei+DrAxjxBQAAODmCrw9o4hjx5eI2AACAKhF8fUDyseCbU1iqguJSi6sBAADwTARfHxAdGqTIkEBJjPoCAABUheDrA2w2m3PUl+ALAABQOYKvj2jCXL4AAADVIvj6iOQYVm8DAACojtcE38zMTI0bN04xMTGKi4vTNddco7y8vJMet2LFCp1//vmKjIxUTEyM/vjHP+roUd+b9ssx4rufEV8AAIBKeU3wHTdunDZt2qTFixfr448/1jfffKPrrruu2mNWrFihIUOG6IILLtDq1au1Zs0aTZ06VQEBXvOyaywlNlwSI74AAABVCbK6gJrYvHmzPvvsM61Zs0bdu3eXJD3zzDMaNmyYnnjiCaWmplZ63PTp03XzzTdr5syZzm0dOnRokJobmmMRC0Z8AQAAKucVQ58rVqxQXFycM/RK0qBBgxQQEKBVq1ZVesyBAwe0atUqJSUlqXfv3kpOTlb//v317bffVvtcRUVFysnJcbl5A0erAyO+AAAAlfOK4JuRkaGkpCSXbUFBQYqPj1dGRkalx/z666+SpPvvv1/XXnutPvvsM51zzjkaOHCgtm7dWuVzzZkzR7Gxsc5b8+bN3fdC6pHj4rZDeUUqKbNbXA0AAIDnsTT4zpw5Uzabrdrbli1b6vTYdnt5+JsyZYomT56srl276u9//7s6dOig//znP1Ued9dddyk7O9t52717d52ev6ElRIYoONAmY6QDuUVWlwMAAOBxLO3xnTFjhiZNmlTtPm3atFFKSooOHDjgsr20tFSZmZlKSUmp9LgmTZpIkk4//XSX7Z06dVJ6enqVzxcaGqrQ0NAaVO9ZAgJsSooO056so8rILlTTuHCrSwIAAPAolgbfxMREJSYmnnS/Xr16KSsrS+vWrVO3bt0kSUuWLJHdblfPnj0rPaZVq1ZKTU1VWlqay/ZffvlFQ4cOPfXiPVCT2OPBFwAAAK68ose3U6dOGjJkiK699lqtXr1ay5cv19SpUzVmzBjnjA579uxRx44dtXr1aknly/jefvvtevrpp/X2229r27Ztuvfee7VlyxZdc801Vr6cepPM6m0AAABV8orpzCRpwYIFmjp1qgYOHKiAgABddtllevrpp533l5SUKC0tTQUFBc5t06ZNU2FhoaZPn67MzEydddZZWrx4sdq2bWvFS6h3TY5d4JaR7XsLdAAAAJwqmzHGWF2EJ8vJyVFsbKyys7MVExNjdTnV+teyX/W3TzbrwrNS9czYrlaXAwAA0CBqmte8otUBNZMSy4gvAABAVQi+PsSxehs9vgAAABURfH2IY8R3f3aR6GABAABwRfD1IUnR5cG3uMyuzPxii6sBAADwLARfHxISFKDGUeWLb+xjLl8AAAAXBF8fkxJbHnz30+cLAADgguDrY1JiypcqZsQXAADAFcHXxzDiCwAAUDmCr49pEsuILwAAQGUIvj4m+dhcvoz4AgAAuCL4+pgmx+byZcQXAADAFcHXxzhHfAm+AAAALgi+PsaxeltuUanyikotrgYAAMBzEHx9TFRokKJDgyRJGdlHLa4GAADAcxB8fVCTOPp8AQAAfo/g64McU5rtzWLEFwAAwIHg64NS4xzBlxFfAAAAB4KvD0o9doEbI74AAADHEXx9kGPElx5fAACA4wi+Puh4qwMjvgAAAA4EXx+UemxWh73ZR2WMsbgaAAAAz0Dw9UGORSwKS+w6UlBicTUAAACegeDrg0KDAtU4KlQS7Q4AAAAOBF8f1TSOmR0AAABORPD1UVzgBgAA4Irg66Mcq7cxpRkAAEA5gq+PcszssIcRXwAAAEkEX5/FIhYAAACuCL4+ih5fAAAAVwRfH+VoddifU6jSMrvF1QAAAFiP4OujGkeGKjjQJruR9ucWWV0OAACA5Qi+PiogwOac2YF2BwAAAIKvT2sSyyIWAAAADgRfH9bUeYEbMzsAAAAQfH1YE5YtBgAAcCL4+rDjc/kSfAEAAAi+PswRfPfQ6gAAAEDw9WWpsYz4AgAAOBB8fZhjEYusghIVFJdaXA0AAIC1CL4+LDosWNGhQZKY2QEAAIDg6+NS41jEAgAAQCL4+rxUpjQDAACQRPD1eU0cI77ZtDoAAAD/RvD1cU1pdQAAAJBE8PV5TWLLWx2Y0gwAAPg7gq+PO35xG60OAADAvxF8fdyJrQ7GGIurAQAAsA7B18clx4TJZpOKSu3KzC+2uhwAAADLEHx9XEhQgBKjQiXR7gAAAPwbwdcPHJ/SjAvcAACA/yL4+oGmLGIBAABA8PUHTWLLR3z3sYgFAADwYwRfP+CY0mwPI74AAMCPEXz9AK0OAAAABF+/4Gx1YFYHAADgxwi+fsDR6rA/t1AlZXaLqwEAALAGwdcPJESGKCQwQMZI+3MY9QUAAP6J4OsHAgJsauLs8yX4AgAA/0Tw9ROpzinNuMANAAD4J4Kvn3CM+DKlGQAA8FcEXz/R1LFsMcEXAAD4KYKvn2BKMwAA4O8Ivn4ilVYHAADg5wi+fqIpyxYDAAA/R/D1E00blQff3MJSZR8tsbgaAACAhkfw9RMRIUFKiAyRJO05wqgvAADwPwRfP9Ls2Kjvb0cKLK4EAACg4RF8/UizRhGSpN8Y8QUAAH6I4OtHHCO+uxnxBQAAfojg60eaxTPiCwAA/BfB148c7/El+AIAAP9D8PUjzbm4DQAA+DGCrx9pGlfe6sBcvgAAwB8RfP1IeEigGkeVz+XLqC8AAPA3BF8/05QpzQAAgJ8i+PoZLnADAAD+iuDrZ1i9DQAA+CuCr59h9TYAAOCvCL5+hlYHAADgrwi+fqa5c8SXVgcAAOBfCL5+xjHim1tYquwC5vIFAAD+g+DrZ8KCA9U4KlSStJtRXwAA4EcIvn6IPl8AAOCPCL5+iCnNAACAPyL4+iGmNAMAAP6I4OuHaHUAAAD+iODrh2h1AAAA/ojg64ccrQ57jhyVMcbiagAAABoGwdcPOefyLSpVztFSi6sBAABoGARfP8RcvgAAwB8RfP1U83gucAMAAP6F4Ounjk9pxogvAADwDwRfP8WUZgAAwN94TfDNzMzUuHHjFBMTo7i4OF1zzTXKy8ur9piMjAyNHz9eKSkpioyM1DnnnKN33nmngSr2bExpBgAA/I3XBN9x48Zp06ZNWrx4sT7++GN98803uu6666o9ZsKECUpLS9OHH36oH3/8USNHjtTo0aO1YcOGBqrac7F6GwAA8DdeEXw3b96szz77TP/617/Us2dP9e3bV88884zeeOMN7d27t8rjvvvuO910003q0aOH2rRpo7/+9a+Ki4vTunXrGrB6z3RiqwNz+QIAAH/gFcF3xYoViouLU/fu3Z3bBg0apICAAK1atarK43r37q0333xTmZmZstvteuONN1RYWKgBAwZUeUxRUZFycnJcbr6oaVx58M0rKlX20RKLqwEAAKh/XhF8MzIylJSU5LItKChI8fHxysjIqPK4//73vyopKVFCQoJCQ0M1ZcoUvffee2rXrl2Vx8yZM0exsbHOW/Pmzd32OjxJWHCgEqPL5/Kl3QEAAPgDS4PvzJkzZbPZqr1t2bKlzo9/7733KisrS1988YXWrl2rW2+9VaNHj9aPP/5Y5TF33XWXsrOznbfdu3fX+fk9HRe4AQAAfxJk5ZPPmDFDkyZNqnafNm3aKCUlRQcOHHDZXlpaqszMTKWkpFR63Pbt2/Xss8/qp59+0hlnnCFJOuuss7Rs2TI999xzeuGFFyo9LjQ0VKGhobV/MV6oWaMIbUjPYsQXAAD4BUuDb2JiohITE0+6X69evZSVlaV169apW7dukqQlS5bIbrerZ8+elR5TUFA+ihkQ4DqoHRgYKLvdfoqV+4bmzOULAAD8iFf0+Hbq1ElDhgzRtddeq9WrV2v58uWaOnWqxowZo9TUVEnSnj171LFjR61evVqS1LFjR7Vr105TpkzR6tWrtX37dj355JNavHixLrnkEgtfjedg9TYAAOBPvCL4StKCBQvUsWNHDRw4UMOGDVPfvn314osvOu8vKSlRWlqac6Q3ODhY//vf/5SYmKgLL7xQZ555pl555RXNnz9fw4YNs+pleBRHj+/uTEZ8AQCA76tTq0N+fr4iIyPdXUu14uPjtXDhwirvb9WqVYX5aNu3b89KbdU48eI2Y4xsNpvFFQEAANSfOo34Jicn6+qrr9a3337r7nrQgFKPzeWbX1ymrALm8gUAAL6tTsH3tddeU2Zmps4//3yddtppeuSRR6pdQQ2eKSw4UEnM5QsAAPxEnYLvJZdcovfff1979uzRX/7yFy1cuFAtW7bUiBEj9O6776q0tNTddaKeMJcvAADwF6d0cVtiYqJuvfVW/fDDD3rqqaf0xRdfaNSoUUpNTdWsWbOcF5rBcx2f2YERXwAA4NtOaR7f/fv3a/78+Zo3b5527dqlUaNG6ZprrtFvv/2mRx99VCtXrtTnn3/urlpRD5wzOzDiCwAAfFydgu+7776rl19+WYsWLdLpp5+uG264QVdddZXi4uKc+/Tu3VudOnVyV52oJy3iy0d80zMJvgAAwLfVKfhOnjxZY8aM0fLly3XuuedWuk9qaqruueeeUyoO9a9FQnnw3XWY4AsAAHxbnYLvvn37FBERUe0+4eHhuu++++pUFBpOq4Ty+Zh/O1KgMrtRYABz+QIAAN9Up+BbWlqqnJycCtttNptCQ0MVEhJyyoWhYaTEhCkkKEDFpXbtzTqq5vHV/4MGAADAW9VpVoe4uDg1atSowi0uLk7h4eFq2bKl7rvvPtntdnfXCzcLCLCp+bEL3OjzBQAAvqxOI77z5s3TPffco0mTJqlHjx6SpNWrV2v+/Pn661//qoMHD+qJJ55QaGio7r77brcWDPdrmRCp7Qfztetwgfq0s7oaAACA+lGn4Dt//nw9+eSTGj16tHPbhRdeqC5duuif//ynvvzyS7Vo0UIPPfQQwdcLOGZ22HU43+JKAAAA6k+dWh2+++47de3atcL2rl27asWKFZKkvn37Kj09/dSqQ4NoxcwOAADAD9Qp+DZv3lz//ve/K2z/97//rebNm0uSDh8+rEaNGp1adWgQLY/N7LCLHl8AAODD6tTq8MQTT+jyyy/Xp59+6pzHd+3atdqyZYvefvttSdKaNWt0xRVXuK9S1BvHXL7ph/NljJHNxpRmAADA99Qp+F500UVKS0vTP//5T6WlpUmShg4dqvfff1+tWrWSJF1//fVuKxL1q1mjcNlsUn5xmQ7lFSsxOtTqkgAAANyu1sG3pKREQ4YM0QsvvKA5c+bUR01oYKFBgUqNDdeerKNKz8wn+AIAAJ9U6x7f4OBg/fDDD/VRCyzUkgvcAACAj6vTxW1XXXVVpRe3wXsRfAEAgK+r85LF//nPf/TFF1+oW7duioyMdLn/qaeecktxaDgt4svPIau3AQAAX1Wn4PvTTz/pnHPOkST98ssvLvcxI4B3coz47mQRCwAA4KPqFHyXLl3q7jpgsZbOKc0Y8QUAAL6pTj2+Dtu2bdOiRYt09OhRSZIxxi1FoeE5FrE4nF+svKJSi6sBAABwvzoF38OHD2vgwIE67bTTNGzYMO3bt0+SdM0112jGjBluLRANIyo0SAmRIZKkXbQ7AAAAH1Sn4Dt9+nQFBwcrPT1dERERzu1XXHGFPvvsM7cVh4bVgnYHAADgw+rU4/v5559r0aJFatasmcv29u3ba9euXW4pDA2vZXyENqRnaSfBFwAA+KA6jfjm5+e7jPQ6ZGZmKjSUVb+8laPPNz2TVgcAAOB76hR8+/Xrp1deecX5s81mk91u12OPPabzzjvPbcWhYbGIBQAA8GV1anV47LHHNHDgQK1du1bFxcW64447tGnTJmVmZmr58uXurhENhOALAAB8WZ1GfDt37qxffvlFffv21cUXX6z8/HyNHDlSGzZsUNu2bd1dIxqIY/W2fdlHVVRaZnE1AAAA7lWnEV9Jio2N1T333OPOWmCxxlEhiggJVEFxmX47clRtE6OsLgkAAMBt6hx8s7KytHr1ah04cEB2u93lvgkTJpxyYWh4NptNLRMitXlfjtIPFxB8AQCAT6lT8P3oo480btw45eXlKSYmRjabzXmfzWYj+HqxlvER2rwvh0UsAACAz6lTj++MGTN09dVXKy8vT1lZWTpy5IjzlpmZ6e4a0YCcF7hlcoEbAADwLXUKvnv27NHNN99c6Vy+8G6s3gYAAHxVnYLv4MGDtXbtWnfXAg/Q8tjMDjtpdQAAAD6mTj2+w4cP1+23366ff/5ZXbp0UXBwsMv9F110kVuKQ8NztDrsPnJUdrtRQIDtJEcAAAB4hzoF32uvvVaS9MADD1S4z2azqayMOWC9VWpcuIIDbSoutSsjp1CpceFWlwQAAOAWdWp1sNvtVd4Ivd4tMMCmZo1YwQ0AAPieWgXfYcOGKTs72/nzI488oqysLOfPhw8f1umnn+624mCNFvGO4EufLwAA8B21Cr6LFi1SUVGR8+eHH37YZfqy0tJSpaWlua86WIIpzQAAgC+qVfA1xlT7M3xDy4TymR2Y0gwAAPiSOvX4wre1dLQ6ZNLqAAAAfEetgq/NZnNZntixDb7F2epwuIBRfQAA4DNqNZ2ZMUaTJk1SaGioJKmwsFB/+ctfFBlZ/tX4if2/8F7Nj4345haW6khBieIjQyyuCAAA4NTVKvhOnDjR5eerrrqqwj4TJkw4tYpgubDgQDWJDdO+7ELtOpxP8AUAAD6hVsH35Zdfrq864GFaJkRoX3ahdh7OV9cWjawuBwAA4JRxcRsq1SYxSpL060EucAMAAL6B4ItKtWlc3rdN8AUAAL6C4ItKtT024rv9YJ7FlQAAALgHwReVapNYPuK741C+7HamNAMAAN6P4ItKNWsUoZDAABWV2rUn66jV5QAAAJwygi8qFRhgcy5k8esh+nwBAID3I/iiSo52h1/p8wUAAD6A4IsqtWVKMwAA4EMIvqiScy7fQ4z4AgAA70fwRZWOtzow4gsAALwfwRdVatu4fMR3X3ah8otKLa4GAADg1BB8UaXYiGAlRIZIKp/PFwAAwJsRfFEtR7sDK7gBAABvR/BFtdo0ZmYHAADgGwi+qJbzAjdaHQAAgJcj+KJazinNaHUAAABejuCLarU9NuK741C+jDEWVwMAAFB3BF9Uq3l8hIICbCooLlNGTqHV5QAAANQZwRfVCg4MUIuECElc4AYAALwbwRcn5ZjZgSnNAACANyP44qTasnQxAADwAQRfnBSLWAAAAF9A8MVJHZ/SjBFfAADgvQi+OKk2jctHfPdmH1VhSZnF1QAAANQNwRcnFR8ZotjwYBlTPp8vAACANyL44qRsNtvxpYtpdwAAAF6K4IsaacvSxQAAwMsRfFEjzOwAAAC8HcEXNeJYxOJXenwBAICXIviiRk5cxMIYY3E1AAAAtUfwRY20SIhQgE3KKyrVwdwiq8sBAACoNYIvaiQ0KFDN4yMkSduZ2QEAAHghgi9qzLGQxa+HuMANAAB4H4IvaoyliwEAgDcj+KLGji9iwYgvAADwPgRf1JhjSjN6fAEAgDci+KLG2iaVj/j+dqRAhSVlFlcDAABQOwRf1FhiVKgaRQTLbqRtB2h3AAAA3oXgixqz2Ww6LTlakvTL/lyLqwEAAKgdgi9qpUNKefBNI/gCAAAvQ/BFrThHfDMIvgAAwLsQfFErjhHfX/bT4wsAALwLwRe1clpSefDdk3VUuYUlFlcDAABQcwRf1EpsRLBSYsIkMeoLAAC8C8EXtXZaCjM7AAAA70PwRa11SC5fwS2NC9wAAIAXIfii1pjLFwAAeCOvCb4PPfSQevfurYiICMXFxdXoGGOMZs2apSZNmig8PFyDBg3S1q1b67dQP9CBVgcAAOCFvCb4FhcX6/LLL9f1119f42Mee+wxPf3003rhhRe0atUqRUZGavDgwSosLKzHSn1fu6Qo2WzSobxiHcorsrocAACAGvGa4Dt79mxNnz5dXbp0qdH+xhjNnTtXf/3rX3XxxRfrzDPP1CuvvKK9e/fq/fffr99ifVxESJBaxEdIYtQXAAB4D68JvrW1Y8cOZWRkaNCgQc5tsbGx6tmzp1asWFHlcUVFRcrJyXG5oSJWcAMAAN7GZ4NvRkaGJCk5Odlle3JysvO+ysyZM0exsbHOW/Pmzeu1Tm/V4VjwTWMuXwAA4CUsDb4zZ86UzWar9rZly5YGremuu+5Sdna287Z79+4GfX5vwVy+AADA2wRZ+eQzZszQpEmTqt2nTZs2dXrslJQUSdL+/fvVpEkT5/b9+/fr7LPPrvK40NBQhYaG1uk5/UmHE1odjDGy2WwWVwQAAFA9S4NvYmKiEhMT6+WxW7durZSUFH355ZfOoJuTk6NVq1bVamYIVK5140gFBdiUW1SqfdmFSo0Lt7okAACAanlNj296ero2btyo9PR0lZWVaePGjdq4caPy8o73mHbs2FHvvfeeJMlms2natGn629/+pg8//FA//vijJkyYoNTUVF1yySUWvQrfERIUoDaJkZKkNNodAACAF7B0xLc2Zs2apfnz5zt/7tq1qyRp6dKlGjBggCQpLS1N2dnZzn3uuOMO5efn67rrrlNWVpb69u2rzz77TGFhYQ1au686LTlav+zP0y8ZuTqvQ5LV5QAAAFTLZowxVhfhyXJychQbG6vs7GzFxMRYXY5HeebLrXpy8S8aeU5TPTX6bKvLAQAAfqqmec1rWh3geZjZAQAAeBOCL+rMMbPD1v15KrPzxQEAAPBsBF/UWfP4CIUFB6io1K70zAKrywEAAKgWwRd1FhhgU/ukYyu4sXQxAADwcARfnJLTkunzBQAA3oHgi1PSISVKEnP5AgAAz0fwxSk57YSliwEAADwZwRenpMOxKc12HMpXUWmZxdUAAABUjeCLU5ISE6bosCCV2o12HMq3uhwAAIAqEXxxSmw2m3M+X2Z2AAAAnozgi1PGCm4AAMAbEHxxyhwjvpv3EXwBAIDnIvjilJ2RGiNJ2rQ32+JKAAAAqkbwxSnr1CRGNpu0P6dIB3ILrS4HAACgUgRfnLLI0CC1aRwpSdq0N8fiagAAACpH8IVbdG4aK0natId2BwAA4JkIvnCLzqnlwfdHgi8AAPBQBF+4hWPE96c9tDoAAADPRPCFW5x+bGaHPVlHdSS/2OJqAAAAKiL4wi1iw4PVMiFCEhe4AQAAz0Twhds4+nx/Yj5fAADggQi+cJszmpa3O/zEBW4AAMADEXzhNo4RX1odAACAJyL4wm0cMzvsOJSv3MISi6sBAABwRfCF28RHhqhpXLgkRn0BAIDnIfjCrc5Ipc8XAAB4JoIv3Mq5dDEjvgAAwMMQfOFWnZnZAQAAeCiCL9zKMbPD9oN5KigutbgaAACA4wi+cKukmDAlRofKbqTN+3KtLgcAAMCJ4Au363zsArdNrOAGAAA8CMEXbtfl2AVu9PkCAABPQvCF251xLPj+uIeZHQAAgOcg+MLtHFOabd2fq8KSMourAQAAKEfwhdulxoapUUSwSu1Gv+znAjcAAOAZCL5wO5vN5hz1/Yl2BwAA4CEIvqgXZxybz/cnZnYAAAAeguCLeuFYwW0TMzsAAAAPQfBFvXBMabY5I1clZXaLqwEAACD4op60iI9QdFiQikvt2nYgz+pyAAAACL6oHzabTWccW8Hth9+yrC0GAABABF/Uo64tGkmS1u/KsrYQAAAAEXxRj845FnzXpR+xuBIAAACCL+rROS3iJEnbDuQpu6DE2mIAAIDfI/ii3iREhap140hJ0vrdjPoCAABrEXxRr85x9vkSfAEAgLUIvqhX3Voe6/Ml+AIAAIsRfFGvzmkZJ0nauDtLpSxkAQAALETwRb1qnxSt6NAgFRSXKW1/rtXlAAAAP0bwRb0KDLDp7GOzO9DnCwAArETwRb2jzxcAAHgCgi/qHQtZAAAAT0DwRb07u0WcbDZpd+ZRHcgttLocAADgpwi+qHcxYcHqkBwtSVq/K8vaYgAAgN8i+KJBnHOsz3c97Q4AAMAiBF80CGefLxe4AQAAixB80SAcMzv8+Fu2ikrLLK4GAAD4I4IvGkSrhAjFR4aouMyuTXtzrC4HAAD4IYIvGoTNZnO2O7CQBQAAsALBFw3mnJZxkujzBQAA1iD4osF0Ozbiu3bXERljLK4GAAD4G4IvGsyZzeIUFGDTwdwi/XbkqNXlAAAAP0PwRYMJDwnUGakxkpjPFwAANDyCLxqUcyEL+nwBAEADI/iiQTkXsmDEFwAANDCCLxqUYyGLzftylVdUanE1AADAnxB80aBS48LVrFG4yuxGa3ZkWl0OAADwIwRfNLi+7RpLkpZvO2RxJQAAwJ8QfNHgeh8Lvt8SfAEAQAMi+KLB9W6bIEnakpGrQ3lFFlcDAAD8BcEXDa5xVKg6pkRLklZsP2xxNQAAwF8QfGGJPsfaHb7bTrsDAABoGARfWKJPu/J2B/p8AQBAQyH4whI9WicoKMCm3ZlHtTuzwOpyAACAHyD4whJRoUE6u3mcJKY1AwAADYPgC8s4pjVbzgVuAACgARB8YRnHQhbfbTsku91YXA0AAPB1BF9Y5uzmcQoPDtTh/GKl7c+1uhwAAODjCL6wTEhQgHq0jpdEny8AAKh/BF9YytnuQJ8vAACoZwRfWKr3sfl8V/16WCVldourAQAAvozgC0t1SolRfGSI8ovL9P3uLKvLAQAAPozgC0sFBNjUq235qO/ybbQ7AACA+kPwheX6tD02ny8XuAEAgHpE8IXl+hzr892w+4gKikstrgYAAPgqgi8s1yI+Qs0ahaukzGj1jkyrywEAAD6K4AvL2Ww2Z7sD05oBAID6QvCFR+jTvjz4fp120OJKAACAryL4wiP0b5+owACb0vbnKv1wgdXlAAAAH0TwhUeIjQhWz2PLF3/+c4bF1QAAAF9E8IXH+NPpyZKkxT/vt7gSAADgiwi+8BiO4LtmZ6aO5BdbXA0AAPA1BF94jGaNItSpSYzsRvpyywGrywEAAD7Ga4LvQw89pN69eysiIkJxcXEn3b+kpER33nmnunTposjISKWmpmrChAnau3dv/ReLOjve7kCfLwAAcC+vCb7FxcW6/PLLdf3119do/4KCAq1fv1733nuv1q9fr3fffVdpaWm66KKL6rlSnIoLjgXfb345pMKSMourAQAAviTI6gJqavbs2ZKkefPm1Wj/2NhYLV682GXbs88+qx49eig9PV0tWrRwd4lwgzNSY5QaG6a92YVavu2QBnZKtrokAADgI7xmxNcdsrOzZbPZqm2VKCoqUk5OjssNDcdmszG7AwAAqBd+E3wLCwt15513auzYsYqJialyvzlz5ig2NtZ5a968eQNWCUn60+kpkqQvNh+Q3W4srgYAAPgKS4PvzJkzZbPZqr1t2bLllJ+npKREo0ePljFGzz//fLX73nXXXcrOznbedu/efcrPj9rp2SZe0WFBOpRXpA27s6wuBwAA+AhLe3xnzJihSZMmVbtPmzZtTuk5HKF3165dWrJkSbWjvZIUGhqq0NDQU3pOnJrgwACd1yFJH36/V4t/3q9uLRtZXRIAAPABlgbfxMREJSYm1tvjO0Lv1q1btXTpUiUkJNTbc8G9/nR68rHgm6GZQztaXQ4AAPABXtPjm56ero0bNyo9PV1lZWXauHGjNm7cqLy8POc+HTt21HvvvSepPPSOGjVKa9eu1YIFC1RWVqaMjAxlZGSouJhVwTzdgA6JCg60afvBfG0/mHfyAwAAAE7Ca6YzmzVrlubPn+/8uWvXrpKkpUuXasCAAZKktLQ0ZWdnS5L27NmjDz/8UJJ09tlnuzzWicfAM0WHBesPbRK0bOshLf55v9r2j7K6JAAA4OVsxhgum69GTk6OYmNjlZ2dfdL+YLjXqyt26t4PNqlby0Z65/reVpcDAAA8VE3zmte0OsD/DDo2n+/69CM6mFtkcTUAAMDbEXzhsZrEhuvMZrEyRvpiM4tZAACAU0PwhUcb2rmJJOn9DXssrgQAAHg7gi882iVdU2WzSat2ZGp3ZoHV5QAAAC9G8IVHaxIbrt5ty+dfZtQXAACcCoIvPN7Irs0kSe9u2CMmIQEAAHVF8IXHG9I5ReHBgdpxKF8bdmdZXQ4AAPBSBF94vMjQIA3pnCJJenf9bxZXAwAAvBXBF15h5DlNJUkf/7BPRaVlFlcDAAC8EcEXXqF328ZKjglVVkGJlm45aHU5AADACxF84RUCA2y6pGv5qC/tDgAAoC4IvvAajtkdlqYdUGZ+scXVAAAAb0PwhdfokBKtM1JjVFJm9PEPe60uBwAAeBmCL7zKyHPKR33fWc9iFgAAoHYIvvAqF52VqsAAm77fnaXtB/OsLgcAAHgRgi+8SmJ0qP7YvrEk6T1GfQEAQC0QfOF1HO0O723YI7udJYwBAEDNEHzhdf50erKiw4K0J+uovt7KnL4AAKBmCL7wOmHBgRrdvbkk6T/f7rC4GgAA4C0IvvBKk3q3UoBNWrb1kH7Zn2t1OQAAwAsQfOGVmsdH6E+nJ0uSXl6+09piAACAVyD4wmtd3ae1JOm9Db/pCCu5AQCAkyD4wmv1aB2vM1JjVFhi1+tr0q0uBwAAeDiCL7yWzWZzjvq+8t0ulZTZLa4IAAB4MoIvvNqIs5qocVSoMnIK9elPGVaXAwAAPBjBF14tNChQV/2hhSSmNgMAANUj+MLrjevZUiGBAdq4O0vr049YXQ4AAPBQBF94vcToUF10dqokRn0BAEDVCL7wCZP7tJIkffpThvZmHbW2GAAA4JEIvvAJZ6TG6g9t4lVmN3plxS6rywEAAB6I4Auf4ZjabMHKXSxoAQAAKiD4wmcM6pSs05vEKLeoVC98vd3qcgAAgIch+MJnBATYdPvgDpKked/t1P6cQosrAgAAnoTgC58yoEOiurdspKJSu57+cqvV5QAAAA9C8IVPsdlsumNIR0nSm2t2a9fhfIsrAgAAnoLgC5/To3W8+p+WqFK70d8X/2J1OQAAwEMQfOGTHL2+H3y/V1syciyuBgAAeAKCL3xS56axGt6liYyRnljEqC8AACD4wodN/9NpCrBJX2zer/XpR6wuBwAAWIzgC5/VLilKo7o1kyQ9sSjN4moAAIDVCL7wabcMOk0hgQH6bvthLdt60OpyAACAhQi+8GlN48I17g8tJEn3fbhJhSVlFlcEAACsQvCFz5s26DQlRofq14P5+r+vWMoYAAB/RfCFz4sND9bsi86QJD3/1Tb9sj/X4ooAAIAVCL7wC0M7p2hQp2SVlBnd9e6PstuN1SUBAIAGRvCFX7DZbHrg4jMUGRKodbuOaOHqdKtLAgAADYzgC7+RGhfuXNHt0U+3aH9OocUVAQCAhkTwhV8Z36uVzmoep9yiUt3/4SarywEAAA2I4Au/Ehhg0yMjuygowKZPf8rQ55syrC4JAAA0EIIv/E6nJjG69o9tJEmzPtik7KMlFlcEAAAaAsEXfumWge3VKiFCGTmFuv2t72UMszwAAODrCL7wS2HBgXp6bFeFBAbo85/368VvfrW6JAAAUM8IvvBbZzaL030XnS5JemxRmlb9etjiigAAQH0i+MKvXdmjhS7t2lRldqOpr2/QgVymOAMAwFcRfOHXbDabHrq0s05LjtLB3CLdtHCDSsvsVpcFAADqAcEXfi8iJEjPX9VNkSGBWrUjU098/ovVJQEAgHpA8AUktU2M0qOjzpQkvfD1di3+eb/FFQEAAHcj+ALHjDgzVZN6t5IkTXtjg77fnWVpPQAAwL0IvsAJ7h7WSb3bJii/uEwTX16trftzrS4JAAC4CcEXOEFIUIBenNBdZzWPU1ZBia769yrtziywuiwAAOAGBF/gd6JCgzRv0rk6LTlK+3OKdNW/VzHNGQAAPoDgC1SiUWSIXr2mp5rHh2vX4QJN+PdqZReUWF0WAAA4BQRfoArJMWF67ZqeSowO1ZaMXE2et1oFxaVWlwUAAOqI4AtUo2VCpF69podiw4O1Pj1L4/61Spn5xVaXBQAA6oDgC5xEx5QYzZt8rmLCgrQhPUsj/2+5dh7Kt7osAABQSwRfoAa6tmikd2/oraZx4dp5uEAjn/9OG9KPWF0WAACoBYIvUEPtkqL13o291blpjDLzizX2pZX6fFOG1WUBAIAaIvgCtZAUHaY3r+ul8zokqrDErimvrdP873ZaXRYAAKgBgi9QS5GhQXppQneN7dFcxkj3fbhJ09/cqNxCpjsDAMCTEXyBOggKDNDDl3bRnUM6KsAmvbdhj4Y9vUzr6fsFAMBjEXyBOrLZbLp+QFv9d0ovNY0L1+7Mo7r8hRV6dslWldmN1eUBAIDfIfgCp6h7q3j975Z+uvCsVJXZjZ74/BeNfWml9mYdtbo0AABwAoIv4Aax4cF6eszZevLysxQZEqjVOzJ1wd+/0YvfbFdxqd3q8gAAgAi+gNvYbDZd1q2ZPrm5n85pEae8olI9/L8tGjL3G32VdsDq8gAA8HsEX8DNWjWO1Nt/6a3HR52pxlGh+vVQvia9vEZ/nr+GFd8AALCQzRjDVTjVyMnJUWxsrLKzsxUTE2N1OfAyOYUleubLrXp5+U6V2o1CAgN0Zc8Wuu6PbZQaF251eQAA+ISa5jWC70kQfOEO2w7kafZHm7Rs6yFJUnCgTSO7NtP1A9qqVeNIi6sDAMC7EXzdhOALdzHG6Ntth/Tskm1atSNTkhRgk4afmaobBrRVpyb8/gIAoC4Ivm5C8EV9WLszU88t3aalaQed285t1UhXnNtCw7qkKCIkyMLqAADwLgRfNyH4oj5t2put/1u6XZ/+tE+ONS+iQoN00dmpuqJ7c53ZLFY2m83aIgEA8HAEXzch+KIhZGQX6p31v+nNNbuVnlng3N4+KUpDOqdo8BkpOiM1hhAMAEAlCL5uQvBFQ7LbjVbuOKw31+zWpz9luCx+0TQuXIPPSNHgM5LVrWUjBQUyGyEAABLB120IvrBKdkGJvtyyX4s2ZejrXw6qsOR4CI4ODVKP1vHq1TZBvds2VseUaAUEMBoMAPBPBF83IfjCExwtLtOyrQe1aNN+fbllv7IKSlzubxQRrD+0SVDXFnE6s1mcujSNVWQoF8gBAPwDwddNCL7wNGV2o837cvTd9kNasf2wVu/IVH5xmcs+Nlt5f7AjBJ+WHK3TkqOUEBVqUdUAANQfgq+bEHzh6UrK7Prht2yt3pGpH37L0ve7s7Q3u7DSfRtHhah9UnkIbpMYpRYJEWoZH6FmjSIUEkTPMADAOxF83YTgC290ILdQP+zO1ve/ZWnzvhz9sj/PZbaI3wuwSalx4WqZEKEmseFKjQ1TSmy4msSGqUlcmFJiwhQbHsysEgAAj0TwdROCL3xFQXGpth3I0y/78/TL/lztPJSv9MwC7TpcoKMlZSc9PjjQpoTIUDWODlHjqFA1jgpVQmSI4iJCFBcRrEYRwc5fx4QFKzosSJEhQVx0BwCodzXNa1z9AviJiJAgndms/OK3ExljdDCvSOmHy0NwRk6h9mYdVUZ2ofZmFyoj+6iOFJSopMwoI6dQGTmVt1FUxmYrX5DDGYRDgxQREqjIkPJfR4YGKjwkUOHB5beIkECFBR+/hQYFlN+O/TokKEAhgcf/H+z4f6CN0WgAwEkRfAE/Z7PZlBQdpqToMHVvFV/pPoUlZTqcX6xDuUU6lOe4FSszv1hHCoqVVVCirGP/P1JQrNzCUpXajYyRcgtLlVtYWu+vIyjApqBAm4IDygNxUIBNwYEBCgywKSjApsBjt6BAmwIDAhRok4ICApzbXW42mwIDj/0/wKYAm02BAVKAzaaAgOPbbbZj22xSwLH9AmySTcf+byvfVr5f+c+OY2wq/4eBTeXbbC7bju9rKz9JcsR6xzE6YV+X7cc2HN9u+93Prv8vv+/4DzX590Nl/8io6rCqHs9WyRHu+LdLff7zh39bAbUTFxGiP7RJsLoMFwRfACcVFhyopnHhahoXXqP9jTEqLLErt7BEOYWlyi0sUW5hqQqKy5RfVKqC4lLlH/v10eIyHS0pvxWWlOlocZkKistUXGZXUYldRaVlKiq1l99KylRSZlRcZleZ3bVLq9RuVGo3KpRdKqqPdwEAUBvntmqkt/7S2+oyXBB8AbidzWYrb2EICVRSPbXGl9mNSsrsKi6zq7jUrtKy8p9L7Ualx7aX72NUZjcqtZfvU2Z3/GxkN7/72W5UZo7/+sRtdnPs13apzBgZxzZTvuJe+WNJRuUj3XZzfJuObXNsNyr/v8r/O/ZYx39tyg9xeSyp/HhH3DeOnZy/PvE+87ufK7//907cbFT9PrXZtyZqfbGJG65OqapuNBxjaj6SzhVJ3qdDSrTVJVRA8AXglcrbEsp7gQEAqAkm7gQAAIBf8Jrg+9BDD6l3796KiIhQXFxcrY//y1/+IpvNprlz57q9NgAAAHg+rwm+xcXFuvzyy3X99dfX+tj33ntPK1euVGpqaj1UBgAAAG/gNT2+s2fPliTNmzevVsft2bNHN910kxYtWqThw4fXQ2UAAADwBl4TfOvCbrdr/Pjxuv3223XGGWfU6JiioiIVFR2fCyknJ6e+ygMAAEAD8ppWh7p49NFHFRQUpJtvvrnGx8yZM0exsbHOW/PmzeuxQgAAADQUS4PvzJkzj61OVPVty5YtdXrsdevW6R//+IfmzZtXq6VM77rrLmVnZztvu3fvrtPzAwAAwLNY2uowY8YMTZo0qdp92rRpU6fHXrZsmQ4cOKAWLVo4t5WVlWnGjBmaO3eudu7cWelxoaGhCg0NrdNzAgAAwHNZGnwTExOVmJhYL489fvx4DRo0yGXb4MGDNX78eE2ePLlenhMAAACey2subktPT1dmZqbS09NVVlamjRs3SpLatWunqKgoSVLHjh01Z84cXXrppUpISFBCQoLLYwQHByslJUUdOnRo6PIBAABgMa8JvrNmzdL8+fOdP3ft2lWStHTpUg0YMECSlJaWpuzsbCvKAwAAgIezGWOM1UV4spycHMXGxio7O1sxMTFWlwMAAIDfqWle8+npzAAAAAAHgi8AAAD8AsEXAAAAfoHgCwAAAL9A8AUAAIBfIPgCAADALxB8AQAA4BcIvgAAAPALBF8AAAD4BYIvAAAA/ALBFwAAAH6B4AsAAAC/QPAFAACAXwiyugBPZ4yRJOXk5FhcCQAAACrjyGmO3FYVgu9J5ObmSpKaN29ucSUAAACoTm5urmJjY6u832ZOFo39nN1u1969exUdHS2bzVbvz5eTk6PmzZtr9+7diomJqffnQ/3gPPoGzqNv4Dz6Bs6j96vPc2iMUW5urlJTUxUQUHUnLyO+JxEQEKBmzZo1+PPGxMTwB9sHcB59A+fRN3AefQPn0fvV1zmsbqTXgYvbAAAA4BcIvgAAAPALBF8PExoaqvvuu0+hoaFWl4JTwHn0DZxH38B59A2cR+/nCeeQi9sAAADgFxjxBQAAgF8g+AIAAMAvEHwBAADgFwi+AAAA8AsEXw/z3HPPqVWrVgoLC1PPnj21evVqq0tCFebMmaNzzz1X0dHRSkpK0iWXXKK0tDSXfQoLC3XjjTcqISFBUVFRuuyyy7R//36LKkZNPPLII7LZbJo2bZpzG+fRO+zZs0dXXXWVEhISFB4eri5dumjt2rXO+40xmjVrlpo0aaLw8HANGjRIW7dutbBi/F5ZWZnuvfdetW7dWuHh4Wrbtq0efPBBnXgdPufR83zzzTe68MILlZqaKpvNpvfff9/l/pqcs8zMTI0bN04xMTGKi4vTNddco7y8PLfXSvD1IG+++aZuvfVW3XfffVq/fr3OOussDR48WAcOHLC6NFTi66+/1o033qiVK1dq8eLFKikp0QUXXKD8/HznPtOnT9dHH32kt956S19//bX27t2rkSNHWlg1qrNmzRr985//1JlnnumynfPo+Y4cOaI+ffooODhYn376qX7++Wc9+eSTatSokXOfxx57TE8//bReeOEFrVq1SpGRkRo8eLAKCwstrBwnevTRR/X888/r2Wef1ebNm/Xoo4/qscce0zPPPOPch/PoefLz83XWWWfpueeeq/T+mpyzcePGadOmTVq8eLE+/vhjffPNN7ruuuvcX6yBx+jRo4e58cYbnT+XlZWZ1NRUM2fOHAurQk0dOHDASDJff/21McaYrKwsExwcbN566y3nPps3bzaSzIoVK6wqE1XIzc017du3N4sXLzb9+/c3t9xyizGG8+gt7rzzTtO3b98q77fb7SYlJcU8/vjjzm1ZWVkmNDTUvP766w1RImpg+PDh5uqrr3bZNnLkSDNu3DhjDOfRG0gy7733nvPnmpyzn3/+2Ugya9asce7z6aefGpvNZvbs2ePW+hjx9RDFxcVat26dBg0a5NwWEBCgQYMGacWKFRZWhprKzs6WJMXHx0uS1q1bp5KSEpdz2rFjR7Vo0YJz6oFuvPFGDR8+3OV8SZxHb/Hhhx+qe/fuuvzyy5WUlKSuXbvqpZdect6/Y8cOZWRkuJzH2NhY9ezZk/PoQXr37q0vv/xSv/zyiyTp+++/17fffquhQ4dK4jx6o5qcsxUrViguLk7du3d37jNo0CAFBARo1apVbq0nyK2Phjo7dOiQysrKlJyc7LI9OTlZW7Zssagq1JTdbte0adPUp08fde7cWZKUkZGhkJAQxcXFueybnJysjIwMC6pEVd544w2tX79ea9asqXAf59E7/Prrr3r++ed166236u6779aaNWt08803KyQkRBMnTnSeq8o+YzmPnmPmzJnKyclRx44dFRgYqLKyMj300EMaN26cJHEevVBNzllGRoaSkpJc7g8KClJ8fLzbzyvBF3CDG2+8UT/99JO+/fZbq0tBLe3evVu33HKLFi9erLCwMKvLQR3Z7XZ1795dDz/8sCSpa9eu+umnn/TCCy9o4sSJFleHmvrvf/+rBQsWaOHChTrjjDO0ceNGTZs2TampqZxHuAWtDh6icePGCgwMrHCl+P79+5WSkmJRVaiJqVOn6uOPP9bSpUvVrFkz5/aUlBQVFxcrKyvLZX/OqWdZt26dDhw4oHPOOUdBQUEKCgrS119/raefflpBQUFKTk7mPHqBJk2a6PTTT3fZ1qlTJ6Wnp0uS81zxGevZbr/9ds2cOVNjxoxRly5dNH78eE2fPl1z5syRxHn0RjU5ZykpKRUu5C8tLVVmZqbbzyvB10OEhISoW7du+vLLL53b7Ha7vvzyS/Xq1cvCylAVY4ymTp2q9957T0uWLFHr1q1d7u/WrZuCg4NdzmlaWprS09M5px5k4MCB+vHHH7Vx40bnrXv37ho3bpzz15xHz9enT58K0wn+8ssvatmypSSpdevWSklJcTmPOTk5WrVqFefRgxQUFCggwDWaBAYGym63S+I8eqOanLNevXopKytL69atc+6zZMkS2e129ezZ070FufVSOZySN954w4SGhpp58+aZn3/+2Vx33XUmLi7OZGRkWF0aKnH99deb2NhY89VXX5l9+/Y5bwUFBc59/vKXv5gWLVqYJUuWmLVr15pevXqZXr16WVg1auLEWR2M4Tx6g9WrV5ugoCDz0EMPma1bt5oFCxaYiIgI89prrzn3eeSRR0xcXJz54IMPzA8//GAuvvhi07p1a3P06FELK8eJJk6caJo2bWo+/vhjs2PHDvPuu++axo0bmzvuuMO5D+fR8+Tm5poNGzaYDRs2GEnmqaeeMhs2bDC7du0yxtTsnA0ZMsR07drVrFq1ynz77bemffv2ZuzYsW6vleDrYZ555hnTokULExISYnr06GFWrlxpdUmogqRKby+//LJzn6NHj5obbrjBNGrUyERERJhLL73U7Nu3z7qiUSO/D76cR+/w0Ucfmc6dO5vQ0FDTsWNH8+KLL7rcb7fbzb333muSk5NNaGioGThwoElLS7OoWlQmJyfH3HLLLaZFixYmLCzMtGnTxtxzzz2mqKjIuQ/n0fMsXbq00r8PJ06caIyp2Tk7fPiwGTt2rImKijIxMTFm8uTJJjc31+212ow5YTkUAAAAwEfR4wsAAAC/QPAFAACAXyD4AgAAwC8QfAEAAOAXCL4AAADwCwRfAAAA+AWCLwAAAPwCwRcAAAB+geALAB5i0qRJuuSSS6wuAwB8VpDVBQCAP7DZbNXef9999+kf//iHrF5Mc9KkScrKytL7779vaR0AUB8IvgDQAPbt2+f89ZtvvqlZs2YpLS3NuS0qKkpRUVFWlAYAfoNWBwBoACkpKc5bbGysbDaby7aoqKgKrQ4DBgzQTTfdpGnTpqlRo0ZKTk7WSy+9pPz8fE2ePFnR0dFq166dPv30U5fn+umnnzR06FBFRUUpOTlZ48eP16FDh5z3v/322+rSpYvCw8OVkJCgQYMGKT8/X/fff7/mz5+vDz74QDabTTabTV999ZUkaffu3Ro9erTi4uIUHx+viy++WDt37nQ+pqP22bNnKzExUTExMfrLX/6i4uLikz4vADQUgi8AeLD58+ercePGWr16tW666SZdf/31uvzyy9W7d2+tX79eF1xwgcaPH6+CggJJUlZWls4//3x17dpVa9eu1Weffab9+/dr9OjRkspHnseOHaurr75amzdv1ldffaWRI0fKGKPbbrtNo0eP1pAhQ7Rv3z7t27dPvXv3VklJiQYPHqzo6GgtW7ZMy5cvV1RUlIYMGeISbL/88kvnY77++ut69913NXv27JM+LwA0GAMAaFAvv/yyiY2NrbB94sSJ5uKLL3b+3L9/f9O3b1/nz6WlpSYyMtKMHz/euW3fvn1GklmxYoUxxpgHH3zQXHDBBS6Pu3v3biPJpKWlmXXr1hlJZufOnZXW9vsajDHm1VdfNR06dDB2u925raioyISHh5tFixY5j4uPjzf5+fnOfZ5//nkTFRVlysrKTvq8ANAQ6PEFAA925plnOn8dGBiohIQEdenSxbktOTlZknTgwAFJ0vfff6+lS5dW2i+8fft2XXDBBRo4cKC6dOmiwYMH64ILLtCoUaPUqFGjKmv4/vvvtW3bNkVHR7tsLyws1Pbt250/n3XWWYqIiHD+3KtXL+Xl5Wn37t0666yzav28AOBuBF8A8GDBwcEuP9tsNpdtjtki7Ha7JCkvL08XXnihHn300QqP1aRJEwUGBmrx4sX67rvv9Pnnn+uZZ57RPffco1WrVql169aV1pCXl6du3bppwYIFFe5LTEys0euoy/MCgLvR4wsAPuScc87Rpk2b1KpVK7Vr187lFhkZKak8LPfp00ezZ8/Whg0bFBISovfee0+SFBISorKysgqPuXXrViUlJVV4zNjYWOd+33//vY4ePer8eeXKlYqKilLz5s1P+rwA0BAIvgDgQ2688UZlZmZq7NixWrNmjbZv365FixZp8uTJKisr06pVq/Twww9r7dq1Sk9P17vvvquDBw+qU6dOkqRWrVrphx9+UFpamg4dOqSSkhKNGzdOjRs31sUXX6xly5Zpx44d+uqrr3TzzTfrt99+cz53cXGxrrnmGv3888/63//+p/vuu09Tp05VQEDASZ8XABoCrQ4A4ENSU1O1fPly3XnnnbrgggtUVFSkli1basiQIQoICFBMTIy++eYbzZ07Vzk5OWrZsqWefPJJDR06VJJ07bXX6quvvlL37t2Vl5enpUuXasCAAfrmm2905513auTIkcrNzVXTpk01cOBAxcTEOJ974MCBat++vf74xz+qqKhIY8eO1f333y9JJ31eAGgINmOYSwYAcGpY8Q2AN6DVAQAAAH6B4AsAAAC/QKsDAAAA/AIjvgAAAPALBF8AAAD4BYIvAAAA/ALBFwAAAH6B4AsAAAC/QPAFAACAXyD4AgAAwC8QfAEAAOAX/h+r1cOwgPwnBwAAAABJRU5ErkJggg==\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| code-fold: true\n", - "fig, ax = plt.subplots(1)\n", - "# ax = axs[0]\n", - "ax.plot(np.stack(energies))\n", - "ax.set_ylabel(\"Energy\")\n", - "ax.set_xlabel(\"Timesteps\")\n", - "ax.set_title(\"Energy over time for our 3-layer HAM. Random weights\")\n", - "plt.show(fig)\n", - "\n", - "x0diffs = jnp.abs(jnp.diff(jnp.stack([x[0] for x in allx]))).mean(-1)\n", - "x1diffs = jnp.abs(jnp.diff(jnp.stack([x[1] for x in allx]))).mean(-1)\n", - "x2diffs = jnp.abs(jnp.diff(jnp.stack([x[2] for x in allx]))).mean(-1)\n", - "# ax = axs[1]\n", - "fig2, ax = plt.subplots(1)\n", - "ax.plot(np.stack([x0diffs, x1diffs, x2diffs], axis=-1))\n", - "ax.set_title(\"Avg $|\\Delta x|$ over Time\")\n", - "ax.set_xlabel(\"Time steps\")\n", - "ax.set_ylabel(\"$\\Delta x$\")\n", - "\n", - "plt.show(fig)\n", - "plt.show(fig2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "So our 3-layer HAM system with randomly initialized weights and states converges to a fixed energy, at which point the states of each layer do not further change." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We implement the above, simple step function into the class, though more advanced optimizations from the JAX ecosystem (e.g., [optax](https://github.com/deepmind/optax)) can easily be used." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "@patch\n", - "def step(self:HAM,\n", - " xs: List[jnp.ndarray], # Collection of current states for each layer\n", - " updates: List[jnp.ndarray], # Collection of update directions for each state\n", - " dt: float = 0.1, # Stepsize to take in direction of updates\n", - " masks: Optional[List[jnp.ndarray]] = None, # Boolean mask, 0 if clamped neuron, and 1 elsewhere. A pytree identical to `xs`. Optional.\n", - "):\n", - " \"\"\"A discrete step down the energy using step size `dt` scaled by the `tau` of each layer\"\"\"\n", - " taus = self.layer_taus\n", - " alphas = [dt / tau for tau in taus] # Scaling factor of the update size of each layer\n", - " if masks is not None:\n", - " next_xs = jtu.tree_map(lambda x, u, m, alpha: x + alpha * u * m, xs, updates, masks, alphas)\n", - " else:\n", - " next_xs = jtu.tree_map(lambda x, u, alpha: x + alpha * u, xs, updates, alphas)\n", - " return next_xs" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It is particularly useful if all of these functions can be applied to a batched collection of states, something JAX makes particularly easy through its [`jax.vmap`](https://jax.readthedocs.io/en/latest/_autosummary/jax.vmap.html) functionality. We prefix vectorized versions of the above methods with a `v`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "@patch\n", - "def _statelist_batch_axes(self:HAM):\n", - " \"\"\"A helper function to tell vmap to batch along the 0'th dimension of each state in the HAM.\"\"\"\n", - " return ([0 for _ in range(self.n_layers)],)\n", - " \n", - "@patch\n", - "def vactivations(self:HAM, \n", - " xs: List[jnp.ndarray]): # Collection of states for each layer\n", - " \"\"\"A vectorized version of `activations`\"\"\"\n", - " return jax.vmap(self.activations, in_axes=self._statelist_batch_axes())(xs)\n", - "\n", - "@patch\n", - "def venergy(self:HAM, \n", - " xs: List[jnp.ndarray]): # Collection of states for each layer\n", - " \"\"\"A vectorized version of `energy`\"\"\"\n", - " return jax.vmap(self.energy, in_axes=self._statelist_batch_axes())(xs)\n", - "\n", - "@patch\n", - "def vdEdg(self:HAM, \n", - " xs: List[jnp.ndarray]): # Collection of states for each layer\n", - " \"\"\"A vectorized version of `dEdg`\"\"\"\n", - " return jax.vmap(self.dEdg, in_axes=self._statelist_batch_axes())(xs)\n", - "\n", - "@patch\n", - "def vupdates(self:HAM,\n", - " xs: List[jnp.ndarray]): # Collection of states for each layer\n", - " \"\"\"A vectorized version of `updates`\"\"\"\n", - " return jax.vmap(self.updates, in_axes=self._statelist_batch_axes())(xs)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "batch_size=5\n", - "vxs = ham.init_states(bs=batch_size, rng=jax.random.PRNGKey(2))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "x0: (2,)\n", - "x1: (3,)\n", - "x2: (4,)\n" - ] - } - ], - "source": [ - "#| code-fold: true\n", - "print(\"\\n\".join([f\"x{i}: {x.shape}\" for i,x in enumerate(xs)])) # The dynamic variables" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We repeat the above energy analysis for batched samples. For an untrained network, all samples achieve the same energy" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "@jax.jit\n", - "def step(ham, xs, dt):\n", - " energy = ham.venergy(xs)\n", - " updates = ham.vupdates(xs)\n", - " alphas = [dt / tau for tau in ham.layer_taus]\n", - " next_states = jtu.tree_map(lambda x, u, alpha: x + alpha*u, xs, updates, alphas)\n", - " return energy, next_states\n", - "\n", - "energies = []; allx = []; dt = 0.03; x = vxs\n", - "for i in range(100):\n", - " energy, x = step(ham, x, dt)\n", - " energies.append(energy)\n", - " allx.append(x)\n", - " \n", - "senergies = jnp.stack(energies)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| code-fold: true\n", - "fig,ax = plt.subplots(1)\n", - "ax.plot(senergies)\n", - "ax.set_xlabel(f\"Time step (dt={dt})\")\n", - "ax.set_ylabel(f\"Energy\")\n", - "ax.set_title(f\"System energy over time.\\nRandom initial states on 3-layer, untrained HAM\")\n", - "ax.legend([f\"Sample {i}\" for i in range(senergies.shape[-1])])\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We create several helper functions to save and load our state dict." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "@patch\n", - "def load_state_dict(self:HAM, \n", - " state_dict:Any): # The dictionary of all parameters, saved by `save_state_dict`\n", - " \"\"\"Load the state dictionary for a HAM\"\"\"\n", - " if not self.initialized:\n", - " _, self = self.init_states_and_params(jax.random.PRNGKey(0), 1)\n", - " self.connections = state_dict[\"connections\"]\n", - " self.layers = align_with_state_dict(self.layers, state_dict[\"layers\"])\n", - " self.synapses = align_with_state_dict(self.synapses, state_dict[\"synapses\"])\n", - " return self\n", - "\n", - "@patch\n", - "def to_state_dict(self:HAM):\n", - " \"\"\"Convert HAM to state dictionary of parameters and connections\"\"\"\n", - " return jtu.tree_map(to_pickleable, self.to_dict())\n", - "\n", - "@patch\n", - "def save_state_dict(self:HAM, \n", - " fname:Union[str, Path], # Filename of checkpoint to save\n", - " overwrite:bool=True): # Overwrite an existing file of the same name?\n", - " \"\"\"Save the state dictionary for a HAM\"\"\"\n", - " to_save = self.to_state_dict()\n", - " pytree_save(to_save, fname, overwrite=overwrite)\n", - "\n", - "@patch\n", - "def load_ckpt(self:HAM, \n", - " ckpt_f:Union[str, Path]): # Filename of checkpoint to load\n", - " \"\"\"Load from file name\"\"\"\n", - " with open(ckpt_f, \"rb\") as fp:\n", - " state_dict = pickle.load(fp)\n", - " return self.load_state_dict(state_dict)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Visualizing a HAM\n", - "\n", - "We employ the [`hypernetx`](https://github.com/pnnl/HyperNetX) package to create a simple visualization of the layers and nodes" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| Export\n", - "@patch\n", - "def visualize(self:HAM):\n", - " \"\"\"Return a simple hypergraph object of the connections.\"\"\"\n", - " nodenames = [l.name for l in self.layers]\n", - " edgenames = [s.name for s in self.synapses]\n", - " graph = {f\"{edgenames[syn_idx]} ({syn_idx})\": [f\"{nodenames[i]} ({i})\" for i in layer_idxs] for layer_idxs, syn_idx in self.connections}\n", - " H = hnetx.Hypergraph(graph, name=self.name)\n", - " return H" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example Model Architectures\n", - "\n", - "We can use our primitive visualization function to see the connections of our model. We showcase these only to express what is possible to build using our architectures. Hierarchical models have not yet been tested" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Simple Hopfield Network\n", - "\n", - "Consisting of one visible layer and one hidden layer" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "layers = [\n", - " IdentityLayer((768,)), # Visible Layer\n", - " SoftmaxLayer((1000,)), # Hidden Layer\n", - "]\n", - "synapses = [\n", - " DenseSynapse()\n", - "]\n", - "connections = [\n", - " ((0,1),0)\n", - "]\n", - "\n", - "ham = HAM(layers, synapses, connections)\n", - "_, ham = ham.init_states_and_params(jax.random.PRNGKey(0))\n", - "hnetx.draw(ham.visualize())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Simple Convolutional Layer" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "layers = [\n", - " LayerNormLayer((32,32,3)), # Visible Layer\n", - " TanhLayer((16,16,128,)),\n", - " SigmoidLayer((8,8,256)),\n", - " SoftmaxLayer((4,4,256)),\n", - "]\n", - "synapses = [\n", - " ConvSynapse((2,2), strides=(2,2)),\n", - " ConvSynapse((2,2), strides=(2,2)),\n", - " ConvSynapse((2,2), strides=(2,2)),\n", - "]\n", - "\n", - "connections = [\n", - " ((0,1),0),\n", - " ((1,2),1),\n", - " ((2,3),2)\n", - "]\n", - "\n", - "ham = HAM(layers, synapses, connections)\n", - "_, ham = ham.init_states_and_params(jax.random.PRNGKey(0))\n", - "hnetx.draw(ham.visualize())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Energy Transformer (explicit Hopfield Module)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "layers = [\n", - " LayerNormLayer((768,)), # Visible Layer\n", - " ReluLayer((3072,)), # Hidden layer of CHN\n", - "]\n", - "\n", - "synapses = [\n", - " DenseSynapse(),\n", - " AttentionSynapse(num_heads=3, zspace_dim=224)\n", - "]\n", - "connections = [\n", - " ((0,1), 0),\n", - " ((0,0), 1),\n", - "]\n", - "\n", - "ham = HAM(layers, synapses, connections)\n", - "_, ham = ham.init_states_and_params(jax.random.PRNGKey(0))\n", - "hnetx.draw(ham.visualize())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Energy Transformer (implicit Hopfield Module)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "layers = [\n", - " LayerNormLayer((768,)), # Visible Layer\n", - "]\n", - "\n", - "synapses = [\n", - " DenseMatrixSynapseWithHiddenLayer(nhid=3072),\n", - " SelfAttentionSynapse(num_heads=3, zspace_dim=224)\n", - "]\n", - "connections = [\n", - " ((0,), 0),\n", - " ((0,), 1),\n", - "]\n", - "\n", - "ham = HAM(layers, synapses, connections)\n", - "_, ham = ham.init_states_and_params(jax.random.PRNGKey(0))\n", - "hnetx.draw(ham.visualize())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Attention and Convolutions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "layers = [\n", - " LayerNormLayer((32,32,3)), # Visible Layer\n", - " TanhLayer((16,16,128,)),\n", - " SigmoidLayer((8,8,256)),\n", - " SoftmaxLayer((4,4,256)),\n", - "\n", - "]\n", - "synapses = [\n", - " ConvSynapse((2,2), strides=(2,2)),\n", - " ConvSynapse((2,2), strides=(2,2)),\n", - " ConvSynapse((2,2), strides=(2,2)),\n", - " AttentionSynapse(num_heads=3, zspace_dim=64),\n", - " AttentionSynapse(num_heads=3, zspace_dim=64),\n", - " AttentionSynapse(num_heads=3, zspace_dim=64),\n", - "]\n", - "\n", - "connections = [\n", - " ((0,1),0),\n", - " ((1,2),1),\n", - " ((2,3),2),\n", - " ((0,2),3),\n", - " ((1,3),4),\n", - " ((0,3),5),\n", - "]\n", - "\n", - "ham = HAM(layers, synapses, connections)\n", - "_, ham = ham.init_states_and_params(jax.random.PRNGKey(0))\n", - "hnetx.draw(ham.visualize())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### N-ary synapses" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "layers = [\n", - " LayerNormLayer((32,32,3)), # Visible Layer\n", - " TanhLayer((16,16,128,)),\n", - " SigmoidLayer((8,8,256)),\n", - " SoftmaxLayer((4,4,256)),\n", - "\n", - "]\n", - "synapses = [\n", - " ConvSynapse((2,2), strides=(2,2)),\n", - " ConvSynapse((2,2), strides=(2,2)),\n", - " ConvSynapse((2,2), strides=(2,2)),\n", - " AttentionSynapse(num_heads=3, zspace_dim=64),\n", - " DenseMatrixSynapseWithHiddenLayer(200)\n", - "]\n", - "\n", - "connections = [\n", - " ((0,1),0),\n", - " ((1,2),1),\n", - " ((2,3),2),\n", - " ((0,2),3),\n", - " ((0,2,3),4)\n", - "]\n", - "\n", - "ham = HAM(layers, synapses, connections)\n", - "_, ham = ham.init_states_and_params(jax.random.PRNGKey(0))\n", - "hnetx.draw(ham.visualize())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "import nbdev; nbdev.nbdev_export()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:hamux]", - "language": "python", - "name": "conda-env-hamux-py" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/nbs/04_registry.ipynb b/nbs/04_registry.ipynb deleted file mode 100644 index bbf0222..0000000 --- a/nbs/04_registry.ipynb +++ /dev/null @@ -1,631 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "464acfcb-4214-4646-8ae8-348d3a596e6c", - "metadata": {}, - "source": [ - "# Registry\n", - "\n", - "> Easily create preconfigured models and prediction functions on a HAM" - ] - }, - { - "cell_type": "markdown", - "id": "fe26cac9-25d4-4044-89f5-aa6d0ccbf78f", - "metadata": {}, - "source": [ - "We create very simple helper functions to instantiate HAMs with particular architectural choices. Inspired by [`timm`](https://github.com/rwightman/pytorch-image-models).\n", - "\n", - "A HAM is a fundamentally general purpose architecture. It is a general-purpose Associative Memory -- it is up to the user to extract the desired information from the system. Hence, every registered model must return the `ham` architecture and a `fwd` function that accomplishes a task from that architecture" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "db0e3694-f799-4aa4-83b7-4a323817d059", - "metadata": {}, - "outputs": [], - "source": [ - "#| default_exp registry" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "79400474-fe9a-42cc-ae5e-78feb69831f5", - "metadata": {}, - "outputs": [], - "source": [ - "#| export \n", - "import hamux as hmx\n", - "from typing import *\n", - "import functools as ft\n", - "from fastcore.utils import *\n", - "import jax\n", - "import jax.numpy as jnp\n", - "import jax.tree_util as jtu\n", - "import treex as tx\n", - "from einops import rearrange" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ec8503e8-3a96-4cd3-802e-83d288a6f629", - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "from nbdev.showdoc import *\n", - "from fastcore.test import *\n", - "import warnings\n", - "import os" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "07a2055d-603e-491f-a5b8-15857644b39b", - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "warnings.simplefilter('ignore')\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"" - ] - }, - { - "cell_type": "markdown", - "id": "23f6083e-0216-4efd-8678-18f2e8d19288", - "metadata": {}, - "source": [ - "## The Registry" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "341ae429-afbd-457c-b2be-fb15b9bdbc23", - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "__MODELS = {}\n", - "\n", - "def register_model(fgen:Callable): # Function that returns a HAM with desired config\n", - " \"\"\"Register a function that returns a model configuration factory function.\n", - " The name of the function acts as the retrieval key and must be unique across models\"\"\"\n", - " __MODELS[fgen.__name__] = fgen\n", - " return fgen\n", - "\n", - "def create_model(mname:str, # Retrieve this stored model name\n", - " *args, # Passed to retrieved factory function\n", - " **kwargs): # Passed to retrieved factory function\n", - " \"\"\"Retrieve the model name from all registered models, passing `args` and `kwargs` to the factory function\"\"\"\n", - " assert mname in __MODELS, f\"Model '{mname}' has not been registered\"\n", - " return __MODELS[mname](*args, **kwargs)\n", - "\n", - "def named_partial(f, *args, new_name=None, order=None, **kwargs):\n", - " \"\"\"Like `functools.partial` but also copies over function name and docstring. \n", - " \n", - " If new_name is not None, use that as the name\n", - " \"\"\"\n", - " fnew = ft.partial(f,*args,**kwargs)\n", - " fnew.__doc__ = f.__doc__\n", - " name = new_name if new_name is not None else f.__name__\n", - " fnew.__name__ = name\n", - " if order is not None: fnew.order=order\n", - " elif hasattr(f,'order'): fnew.order=f.order\n", - " return fnew" - ] - }, - { - "cell_type": "markdown", - "id": "ca35daca-7730-48f9-8102-8ca6248c1933", - "metadata": {}, - "source": [ - "We can now register a model as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f3636da5-2214-43ad-a812-6dae39a26c57", - "metadata": {}, - "outputs": [], - "source": [ - "@register_model\n", - "def example_classical_hn(img_shape:Tuple, # Vector input size\n", - " label_shape:Tuple[int], # Number of labels\n", - " nhid:int=1000, # Number of hidden units in the single hidden layer\n", - " depth:int=4, # Default number of iterations to run the Hopfield Network prediction function\n", - " dt:float=0.4, # Default step size of the system\n", - " ): \n", - " \"\"\"Create a 2-layer classical Hopfield Network applied on vectorized inputs and a function showing how to use it\"\"\"\n", - " layers = [\n", - " hmx.TanhLayer(img_shape),\n", - " hmx.SoftmaxLayer(label_shape),\n", - " ]\n", - "\n", - " synapses = [\n", - " hmx.DenseMatrixSynapseWithHiddenLayer(nhid, hidden_lagrangian=hmx.lagrangians.LRelu()),\n", - " ]\n", - "\n", - " connections = [\n", - " ((0, 1), 0),\n", - " ]\n", - "\n", - " ham = hmx.HAM(layers, synapses, connections)\n", - " \n", - " def fwd(model, x, depth=depth, dt=dt, rng=None):\n", - " \"\"\"A pure function to extract desired information from the configured HAM, applied on batched inputs\"\"\"\n", - " # Initialize hidden states to our image\n", - " xs = model.init_states(x.shape[0], rng=rng)\n", - " xs[0] = jnp.array(x)\n", - "\n", - " # Masks allow us to clamp our visible data over time\n", - " masks = jtu.tree_map(lambda x: jnp.ones_like(x, dtype=jnp.int8), xs)\n", - " masks[0] = jnp.zeros_like(masks[0], dtype=jnp.int8) # Don't evolve images\n", - "\n", - " for i in range(depth):\n", - " updates = model.vupdates(xs) # Calculate the updates\n", - " xs = model.step(\n", - " xs, updates, dt=dt, masks=masks\n", - " ) # Add them to our current states\n", - "\n", - " # All labels have a softmax activation function as the last layer, spitting out probabilities\n", - " return model.layers[-1].g(xs[-1])\n", - "\n", - " return ham, fwd" - ] - }, - { - "cell_type": "markdown", - "id": "56de20bc-af4b-48ca-9194-adee01cd31e7", - "metadata": {}, - "source": [ - "The model that we just created comes with a default function that predicts label probabilities after 4 steps (though feel free to write any function to extract a layer state/activation at any point in time). " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4213e631-459b-45e7-9044-14ca3d5bb41f", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-12-13 16:24:58.481170: E external/org_tensorflow/tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:267] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n", - "WARNING:jax._src.lib.xla_bridge:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n" - ] - }, - { - "data": { - "text/plain": [ - "(12, 10)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "img_shape = (32,32); bs = 12\n", - "model, fwd = create_model(\"example_classical_hn\", img_shape=img_shape, label_shape=(10,))\n", - "\n", - "_, model = model.init_states_and_params(jax.random.PRNGKey(0))\n", - "x = jnp.ones((bs, *img_shape))\n", - "probs = fwd(model, x); probs.shape" - ] - }, - { - "cell_type": "markdown", - "id": "03969322-7b45-4478-8bf2-ef41b67084c6", - "metadata": {}, - "source": [ - "For the simple pipeline of classification, our `fwd` pipelines are quite similar. We therefore create some helper functions to use throughout the rest of our model configuration." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "08e7f88e-4dfa-4595-936c-408050c547ab", - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "def simple_fwd(model:hmx.HAM, # HAM where layer[0] is the image input and layer[-1] are the labels\n", - " x: jnp.ndarray, # Starting point for clamped layer[0]\n", - " depth: int, # Number of iterations for which to run the model\n", - " dt: float, # Step size through time\n", - " rng: Optional[jnp.ndarray]=None): # If provided, initialize states to random instead of 0\n", - " \"\"\"A simple version of the forward function for showing in the paper.\n", - "\n", - " All time constants `tau` are set to be 1 in our architecture, but this is variable\n", - " \"\"\"\n", - " # Initialize hidden states to our image\n", - " xs = model.init_states(x.shape[0], rng=rng)\n", - " xs[0] = jnp.array(x)\n", - "\n", - " # Masks allow us to clamp our visible data over time\n", - " masks = jtu.tree_map(lambda x: jnp.ones_like(x, dtype=jnp.int8), xs)\n", - " masks[0] = jnp.zeros_like(masks[0], dtype=jnp.int8) # Don't evolve images\n", - "\n", - " for i in range(depth):\n", - " updates = model.vupdates(xs) # Calculate the updates\n", - " xs = model.step(\n", - " xs, updates, dt=dt, masks=masks\n", - " ) # Add them to our current states\n", - "\n", - " # All labels have a softmax activation function as the last layer, spitting out probabilities\n", - " return model.layers[-1].g(xs[-1])\n", - "\n", - "def fwd_vec(model:hmx.HAM, # HAM where layer[0] is the image input and layer[-1] are the labels\n", - " x: jnp.ndarray, # Starting point for clamped layer[0]\n", - " depth: int, # Number of iterations for which to run the model\n", - " dt: float, # Step size through time\n", - " rng: Optional[jnp.ndarray]=None): # If provided, initialize states to random instead of 0\n", - " \"\"\"Where the image input is vectorized\"\"\"\n", - " x = rearrange(x, \"... c h w -> ... (c h w)\")\n", - " return simple_fwd(model, x, depth, dt, rng)\n", - "\n", - "def fwd_conv(model:hmx.HAM, # HAM where layer[0] is the image input and layer[-1] are the labels\n", - " x: jnp.ndarray, # Starting point for clamped layer[0]\n", - " depth: int, # Number of iterations for which to run the model\n", - " dt: float, # Step size through time\n", - " rng: Optional[jnp.ndarray]=None): # If provided, initialize states to random instead of 0\n", - " \"\"\"Where the image input is kept as a 3 channel image\"\"\"\n", - " x = rearrange(x, \"... c h w -> ... h w c\")\n", - " return simple_fwd(model,x, depth,dt, rng)\n" - ] - }, - { - "cell_type": "markdown", - "id": "55236146-a0d3-432f-9c31-350b65828287", - "metadata": {}, - "source": [ - "## Model Registry" - ] - }, - { - "cell_type": "markdown", - "id": "25d72ada-5b30-4a8d-9fab-5e17644c1f9e", - "metadata": {}, - "source": [ - "### 2 Layer HN" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b0d303d4-6eb6-4d73-bb4e-becc86741618", - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "@register_model\n", - "def hn(hidden_lagrangian:tx.Module,\n", - " img_shape: Tuple, # Shape of image input to model\n", - " label_shape: Tuple, # Shape of label probabilities,typically (NLABELS,)\n", - " nhid:int=1000, # Number of units in hidden layer\n", - " do_norm:bool=False): # If provided, enforce that all weights are standardized\n", - " \"\"\"Create a Classical Hopfield Network that is intended to be applied on vectorized inputs\"\"\"\n", - " layers = [\n", - " hmx.TanhLayer(img_shape),\n", - " hmx.SoftmaxLayer(label_shape),\n", - " ]\n", - "\n", - " synapses = [\n", - " hmx.DenseMatrixSynapseWithHiddenLayer(nhid, hidden_lagrangian=hidden_lagrangian, do_norm=do_norm),\n", - " ]\n", - "\n", - " connections = [\n", - " ((0, 1), 0),\n", - " ]\n", - "\n", - " ham = hmx.HAM(layers, synapses, connections)\n", - "\n", - " forward = ft.partial(fwd_vec, depth=4, dt=0.4)\n", - "\n", - " return ham, forward\n", - "\n", - "hn_relu = named_partial(hn, hmx.lagrangians.LRelu(), new_name=\"hn_relu\")\n", - "register_model(hn_relu)\n", - "\n", - "hn_repu5 = named_partial(hn, hmx.lagrangians.LRepu(n=5), new_name=\"hn_repu5\")\n", - "register_model(hn_repu5)\n", - "\n", - "hn_softmax = named_partial(hn, hmx.lagrangians.LSoftmax(), new_name=\"hn_softmax\")\n", - "register_model(hn_softmax)\n", - "\n", - "@register_model\n", - "def hn_relu_mnist(nhid:int=1000): # Number of units in the single hidden layer\n", - " \"\"\"Vectorized HN on flattened MNIST\"\"\"\n", - " return hn_relu(img_shape=(784,), label_shape=(10,), nhid=nhid)\n", - "\n", - "@register_model\n", - "def hn_relu_cifar(nhid:int=6000): # Number of units in the single hidden layer\n", - " \"\"\"Vectorized HN on flattened CIFAR10\"\"\"\n", - " return hn_relu(img_shape=(3072,), label_shape=(10,), nhid=nhid)\n", - "\n", - "@register_model\n", - "def hn_repu5_mnist(nhid=1000):\n", - " \"\"\"Vectorized DAM on flattened MNIST\"\"\"\n", - " return hn_repu5(img_shape=(784,), label_shape=(10,), nhid=nhid)\n", - "\n", - "@register_model\n", - "def hn_repu5_cifar(nhid=6000):\n", - " \"\"\"Vectorized DAM on flattened CIFAR\"\"\"\n", - " return hn_repu5(img_shape=(3072,), label_shape=(10,), nhid=nhid)\n", - "\n", - "@register_model\n", - "def hn_softmax_mnist(nhid=1000):\n", - " return hn_softmax(img_shape=(784,), label_shape=(10,), nhid=nhid, do_norm=True)\n", - "\n", - "@register_model\n", - "def hn_softmax_cifar(nhid=6000):\n", - " return hn_softmax(img_shape=(3072,), label_shape=(10,), nhid=nhid, do_norm=True)\n" - ] - }, - { - "cell_type": "markdown", - "id": "ba1c8d86-1fe2-4f59-af06-0691eb74d1d3", - "metadata": {}, - "source": [ - "These models can now be instantiated by their strings:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5353421d-4b05-46b6-a783-4c879dc9cc1b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Array([[0.31536135, 0.08483113, 0.0897951 , 0.02981309, 0.03241062,\n", - " 0.03071734, 0.03666373, 0.00281298, 0.03433144, 0.3432633 ]], dtype=float32)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "xcifar = jnp.ones((1,3, 32,32)) # Per pytorch convention, CHW\n", - "xmnist = jnp.ones((1,1,28,28)) # Per pytorch convention, CHW\n", - "\n", - "exhn, exhn_fwd = create_model(\"hn\", hmx.lagrangians.LExp(), (32,32,3), (10,))\n", - "_, exhn = exhn.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_fwd(exhn, xcifar)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1cf646b1-3711-49e9-8f1d-f9fd8305ef8d", - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "\n", - "# Additional tests for the registry\n", - "\n", - "# Relu model tests\n", - "exhn_relu, exhn_relu_fwd = create_model(\"hn_relu\", (32,32,3), (10,))\n", - "_, exhn_relu = exhn_relu.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_relu_fwd(exhn_relu, xcifar)\n", - "\n", - "exhn_relu_mnist, exhn_relu_mnist_fwd = create_model(\"hn_relu_mnist\")\n", - "_, exhn_relu_mnist = exhn_relu_mnist.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_relu_mnist_fwd(exhn_relu_mnist, xmnist)\n", - "\n", - "exhn_relu_cifar, exhn_relu_cifar_fwd = create_model(\"hn_relu_cifar\")\n", - "_, exhn_relu_cifar = exhn_relu_cifar.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_relu_cifar_fwd(exhn_relu_cifar, xcifar)\n", - " \n", - "# Repu5 model tests\n", - "exhn_repu5, exhn_repu5_fwd = create_model(\"hn_repu5\", (32,32,3), (10,))\n", - "_, exhn_repu5 = exhn_repu5.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_repu5_fwd(exhn_repu5, xcifar)\n", - "\n", - "exhn_repu5_mnist, exhn_repu5_mnist_fwd = create_model(\"hn_repu5_mnist\")\n", - "_, exhn_repu5_mnist = exhn_repu5_mnist.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_repu5_mnist_fwd(exhn_repu5_mnist, xmnist)\n", - "\n", - "exhn_repu5_cifar, exhn_repu5_cifar_fwd = create_model(\"hn_repu5_cifar\")\n", - "_, exhn_repu5_cifar = exhn_repu5_cifar.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_repu5_cifar_fwd(exhn_repu5_cifar, xcifar)\n", - "\n", - "# Softmax model tests\n", - "exhn_repu5, exhn_repu5_fwd = create_model(\"hn_repu5\", (32,32,3), (10,))\n", - "_, exhn_repu5 = exhn_repu5.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_repu5_fwd(exhn_repu5, xcifar)\n", - "\n", - "exhn_repu5_mnist, exhn_repu5_mnist_fwd = create_model(\"hn_repu5_mnist\")\n", - "_, exhn_repu5_mnist = exhn_repu5_mnist.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_repu5_mnist_fwd(exhn_repu5_mnist, xmnist)\n", - "\n", - "exhn_repu5_cifar, exhn_repu5_cifar_fwd = create_model(\"hn_repu5_cifar\")\n", - "_, exhn_repu5_cifar = exhn_repu5_cifar.init_states_and_params(jax.random.PRNGKey(22))\n", - "exhn_repu5_cifar_fwd(exhn_repu5_cifar, xcifar)" - ] - }, - { - "cell_type": "markdown", - "id": "4725a8a1-8f44-4f52-b370-f40c831a6cc9", - "metadata": {}, - "source": [ - "## Simple Convolution" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "046d9abc-be1f-42d4-a020-0d2ab4cca73b", - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "@register_model\n", - "def conv_ham(s1, s2, s3, pool_type, nhid=1000):\n", - " layers = [\n", - " hmx.TanhLayer(s1, tau=1.0),\n", - " hmx.TanhLayer(s2, tau=1.0),\n", - " hmx.TanhLayer(s3, tau=1.0),\n", - " hmx.SoftmaxLayer((10,), tau=1.0),\n", - " ]\n", - " synapses = [\n", - " hmx.ConvSynapseWithPool(\n", - " (4, 4),\n", - " strides=(2, 2),\n", - " padding=(2, 2),\n", - " pool_window=(2, 2),\n", - " pool_stride=(2, 2),\n", - " pool_type=pool_type,\n", - " ),\n", - " hmx.ConvSynapseWithPool(\n", - " (3, 3),\n", - " strides=(1, 1),\n", - " padding=(0, 0),\n", - " pool_window=(2, 2),\n", - " pool_stride=(2, 2),\n", - " pool_type=pool_type,\n", - " ),\n", - " hmx.DenseMatrixSynapseWithHiddenLayer(nhid),\n", - " ]\n", - " connections = [\n", - " ((0, 1), 0), \n", - " ((1, 2), 1), \n", - " ((2, 3), 2)\n", - " ]\n", - "\n", - " ham = hmx.HAM(layers, synapses, connections)\n", - "\n", - " forward = ft.partial(fwd_conv, depth=7, dt=0.3)\n", - " return ham, forward\n", - "\n", - "\n", - "@register_model\n", - "def conv_ham_avgpool_mnist(nhid=1000):\n", - " return conv_ham((28, 28, 1), (7, 7, 64), (2, 2, 128), pool_type=\"avg\", nhid=nhid)\n", - "\n", - "\n", - "@register_model\n", - "def conv_ham_maxpool_mnist(nhid=1000):\n", - " return conv_ham((28, 28, 1), (7, 7, 64), (2, 2, 128), pool_type=\"max\", nhid=nhid)\n", - "\n", - "\n", - "@register_model\n", - "def conv_ham_avgpool_cifar(nhid=1000):\n", - " return conv_ham((32, 32, 3), (8, 8, 90), (3, 3, 180), pool_type=\"avg\", nhid=nhid)\n", - "\n", - "\n", - "@register_model\n", - "def conv_ham_maxpool_cifar(nhid=1000):\n", - " return conv_ham((32, 32, 3), (8, 8, 90), (3, 3, 180), pool_type=\"max\", nhid=nhid)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "aa36e38f-024c-4eef-93f3-51faec7dc388", - "metadata": {}, - "outputs": [], - "source": [ - "model, fwd = create_model(\"conv_ham_avgpool_cifar\")\n", - "_, model = model.init_states_and_params(jax.random.PRNGKey(0))\n", - "fwd(model, xcifar)" - ] - }, - { - "cell_type": "markdown", - "id": "036f93ea-f02a-4285-b0cd-c5da42cf89b1", - "metadata": {}, - "source": [ - "### Energy Version of Attention\n", - "\n", - "We now introduce a simple model for energy-based attention" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2faf57d4-9c6a-48f6-8a8b-15df11c0a7f5", - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "@register_model\n", - "def energy_attn(s1, s2, nheads_self, nheads_cross):\n", - " layers = [\n", - " hmx.TanhLayer(s1, tau=1.0),\n", - " hmx.TanhLayer(s2, tau=1.0, use_bias=True),\n", - " hmx.SoftmaxLayer((10,), tau=1.0),\n", - " ]\n", - "\n", - " synapses = [\n", - " hmx.ConvSynapse((4, 4), strides=(4, 4), padding=(0, 0)),\n", - " hmx.AttentionSynapse(num_heads=nheads_cross, zspace_dim=64, stdinit=0.002),\n", - " hmx.AttentionSynapse(num_heads=nheads_self, zspace_dim=64, stdinit=0.002),\n", - " ]\n", - "\n", - " connections = [(\n", - " (0, 1), 0), \n", - " ((2, 1), 1), \n", - " ((1, 1), 2)\n", - " ]\n", - " ham = hmx.HAM(layers, synapses, connections)\n", - " forward = ft.partial(fwd_conv, depth=5, dt=0.4)\n", - "\n", - " return ham, forward\n", - "\n", - "\n", - "@register_model\n", - "def energy_attn_mnist():\n", - " return energy_attn(\n", - " (28, 28, 1),\n", - " (7, 7, 128),\n", - " nheads_self=4,\n", - " nheads_cross=2,\n", - " )\n", - "\n", - "\n", - "@register_model\n", - "def energy_attn_cifar():\n", - " return energy_attn(\n", - " (32, 32, 3),\n", - " (8, 8, 224),\n", - " nheads_self=4,\n", - " nheads_cross=2,\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "db23841c-17cf-42a7-9a3e-27d0ac1d8233", - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "import nbdev; nbdev.nbdev_export()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:hamux]", - "language": "python", - "name": "conda-env-hamux-py" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/nbs/05_tfjs.ipynb b/nbs/05_tfjs.ipynb deleted file mode 100644 index 39bcaa3..0000000 --- a/nbs/05_tfjs.ipynb +++ /dev/null @@ -1,304 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "464acfcb-4214-4646-8ae8-348d3a596e6c", - "metadata": {}, - "source": [ - "# Converting to TFJS\n", - "\n", - "> Package and ship to the browser" - ] - }, - { - "cell_type": "markdown", - "id": "fe26cac9-25d4-4044-89f5-aa6d0ccbf78f", - "metadata": {}, - "source": [ - "One appeal of HAMs is their general compactness -- all model weights are symmetrical, so powerful models can more easily fit inside RAM. In addition, we believe HAMs to be more interpretable and fun to play around with. For these two reasons, we are building some simple helper functions to convert trained HAM models into the frontend. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "db0e3694-f799-4aa4-83b7-4a323817d059", - "metadata": {}, - "outputs": [], - "source": [ - "#| default_exp tfjs_helpers" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ec8503e8-3a96-4cd3-802e-83d288a6f629", - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "from nbdev.showdoc import *\n", - "from fastcore.test import *\n", - "import warnings\n", - "import os" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "07a2055d-603e-491f-a5b8-15857644b39b", - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "warnings.simplefilter('ignore')\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "79400474-fe9a-42cc-ae5e-78feb69831f5", - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "import tensorflowjs as tfjs\n", - "import tensorflow as tf\n", - "import tempfile\n", - "from tensorflowjs.converters import tf_saved_model_conversion_v2 as saved_model_conversion\n", - "from jax.experimental import jax2tf\n", - "from typing import *" - ] - }, - { - "cell_type": "markdown", - "id": "6d562efc-b08e-4f22-b62d-720fce957236", - "metadata": {}, - "source": [ - "The below code is primarily copied from the source code present in the examples in the [official tutorial](https://blog.tensorflow.org/2022/08/jax-on-web-with-tensorflowjs.html)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c9a944ce-3fe4-4e21-942d-055435dc9e03", - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "\n", - "DType = Any\n", - "PolyShape = jax2tf.shape_poly.PolyShape\n", - "Array = Any \n", - "_TF_SERVING_KEY = tf.saved_model.DEFAULT_SERVING_SIGNATURE_DEF_KEY" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "61996774-e0d8-4265-a2b1-4016dd951647", - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "class _ReusableSavedModelWrapper(tf.train.Checkpoint):\n", - " \"\"\"Wraps a function and its parameters for saving to a SavedModel.\n", - " Implements the interface described at\n", - " https://www.tensorflow.org/hub/reusable_saved_models.\n", - " \"\"\"\n", - "\n", - " def __init__(self, tf_graph, param_vars):\n", - " \"\"\"Args:\n", - " tf_graph: a tf.function taking one argument (the inputs), which can be\n", - " be tuples/lists/dictionaries of np.ndarray or tensors. The function\n", - " may have references to the tf.Variables in `param_vars`.\n", - " param_vars: the parameters, as tuples/lists/dictionaries of tf.Variable,\n", - " to be saved as the variables of the SavedModel.\n", - " \"\"\"\n", - " super().__init__()\n", - " # Implement the interface from https://www.tensorflow.org/hub/reusable_saved_models\n", - " self.variables = tf.nest.flatten(param_vars)\n", - " self.trainable_variables = [v for v in self.variables if v.trainable]\n", - " # If you intend to prescribe regularization terms for users of the model,\n", - " # add them as @tf.functions with no inputs to this list. Else drop this.\n", - " self.regularization_losses = []\n", - " self.__call__ = tf_graph" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9744561e-43f7-43fd-83e6-1264630bb7fb", - "metadata": {}, - "outputs": [], - "source": [ - "#| export\n", - "def convert_jax(\n", - " apply_fn: Callable[..., Any],\n", - " *,\n", - " input_signatures: Sequence[Tuple[Sequence[Union[int, None]], DType]],\n", - " model_dir: str,\n", - " polymorphic_shapes: Optional[Sequence[Union[str, PolyShape]]] = None):\n", - " \"\"\"Converts a JAX function `apply_fn` to a TensorflowJS model. \n", - " Works with `functools.partial` style models if we don't need to access the variables in the frontend.\n", - "\n", - " Example usage for an arbitrary function:\n", - "\n", - " ```\n", - " import functools as ft\n", - " ...\n", - " def predict_fn(model, input):\n", - " return model.predict(input)\n", - "\n", - " fn = ft.partial(predict_fn, trained_model)\n", - "\n", - " convert_jax(\n", - " apply_fn=fn,\n", - " input_signatures=[((D1, D2,), np.float32)],\n", - " model_dir=tfjs_model_dir)\n", - " ```\n", - "\n", - " Note that when using dynamic shapes, an additional argument\n", - " `polymorphic_shapes` should be provided specifying values for the dynamic\n", - " (\"polymorphic\") dimensions). See here for more details:\n", - " https://github.com/google/jax/tree/main/jax/experimental/jax2tf#shape-polymorphic-conversion\n", - "\n", - " This is an adaption of the original implementation in jax2tf here:\n", - " https://github.com/google/jax/blob/main/jax/experimental/jax2tf/examples/saved_model_lib.py\n", - "\n", - " Arguments:\n", - " apply_fn: A JAX function that has one or more arguments, of which the first\n", - " argument are the model parameters. This function typically is the forward\n", - " pass of the network (e.g., `Module.apply()` in Flax).\n", - " input_signatures: the input signatures for the second and remaining\n", - " arguments to `apply_fn` (the input). A signature must be a\n", - " `tensorflow.TensorSpec` instance, or a (nested) tuple/list/dictionary\n", - " thereof with a structure matching the second argument of `apply_fn`.\n", - " model_dir: Directory where the TensorflowJS model will be written to.\n", - " polymorphic_shapes: If given then it will be used as the\n", - " `polymorphic_shapes` argument for the second parameter of `apply_fn`. In\n", - " this case, a single `input_signatures` is supported, and should have\n", - " `None` in the polymorphic (dynamic) dimensions.\n", - " \"\"\"\n", - "\n", - " tf_fn = jax2tf.convert(\n", - " apply_fn,\n", - " # Gradients must be included as 'PreventGradient' is not supported.\n", - " with_gradient=True,\n", - " polymorphic_shapes=polymorphic_shapes,\n", - " # Do not use TFXLA Ops because these aren't supported by TFjs, but use\n", - " # workarounds instead. More information:\n", - " # https://github.com/google/jax/tree/main/jax/experimental/jax2tf#tensorflow-xla-ops\n", - " enable_xla=False)\n", - "\n", - " # Create tf.Variables for the parameters. If you want more useful variable\n", - " # names, you can use `tree.map_structure_with_path` from the `dm-tree`\n", - " # package.\n", - " # For HAMUX we presume that the variables are inaccessible, for now\n", - " param_vars = []\n", - " # param_vars = tf.nest.map_structure(\n", - " # lambda param: tf.Variable(param, trainable=False), params)\n", - " # Do not use TF's jit compilation on the function.\n", - " tf_graph = tf.function(\n", - " lambda *xs: tf_fn(*xs), autograph=False, jit_compile=False)\n", - "\n", - " # This signature is needed for TensorFlow Serving use.\n", - " signatures = {\n", - " _TF_SERVING_KEY: tf_graph.get_concrete_function(*input_signatures)\n", - " }\n", - "\n", - " wrapper = _ReusableSavedModelWrapper(tf_graph, param_vars)\n", - " saved_model_options = tf.saved_model.SaveOptions(\n", - " experimental_custom_gradients=True)\n", - "\n", - " with tempfile.TemporaryDirectory() as saved_model_dir:\n", - " tf.saved_model.save(\n", - " wrapper,\n", - " saved_model_dir,\n", - " signatures=signatures,\n", - " options=saved_model_options)\n", - " saved_model_conversion.convert_tf_saved_model(saved_model_dir, model_dir, skip_op_check=True)" - ] - }, - { - "cell_type": "markdown", - "id": "698b71f8-6089-45ef-a626-b8753693c7bf", - "metadata": {}, - "source": [ - "Let's presume the following example model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c36d0721-26e9-4d16-a82b-9f98999a4fd8", - "metadata": {}, - "outputs": [], - "source": [ - "import hamux as hmx\n", - "import jax\n", - "import jax.numpy as jnp\n", - "import functools as ft\n", - "\n", - "model, fwd = hmx.create_model(\"hn_softmax_mnist\")\n", - "states, model = model.init_states_and_params(jax.random.PRNGKey(0), bs=1)\n", - "\n", - "def simple_batch_fwd(\n", - " x: jnp.ndarray, # Starting point for clamped layer[0]\n", - " dt: float): # Step size through time\n", - " \"\"\"A simple version of the forward function\"\"\"\n", - " # Initialize hidden states to our image\n", - " xs = model.init_states(x.shape[0])\n", - " xs[0] = jnp.array(x)\n", - "\n", - " updates = model.vupdates(xs) # Calculate the updates\n", - " new_xs = model.step(\n", - " xs, updates, dt=dt\n", - " ) # Add them to our current states\n", - "\n", - " # All labels have a softmax activation function as the last layer, spitting out probabilities\n", - " return model.layers[-1].g(xs[-1])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "00f75682-f6cf-4aa4-a6f5-f49fe58d5327", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-12-13 17:02:40.458245: E tensorflow/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Writing weight file _archive/hamux_model/model.json...\n" - ] - } - ], - "source": [ - "# specify where to save the model\n", - "tfjs_model_dir = f'_archive/hamux_model/'\n", - "convert_jax(\n", - " simple_batch_fwd,\n", - " input_signatures=[tf.TensorSpec(states[0].shape, tf.float32), tf.TensorSpec((1,), tf.float32)], # img, dt\n", - " model_dir=tfjs_model_dir,\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:hamux]", - "language": "python", - "name": "conda-env-hamux-py" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/nbs/_quarto.yml b/nbs/_quarto.yml index 0a6dfcb..522a0ed 100644 --- a/nbs/_quarto.yml +++ b/nbs/_quarto.yml @@ -1,11 +1,15 @@ project: type: website +execute: + freeze: false format: html: theme: cosmo css: styles.css toc: true + keep-md: true + commonmark: default website: twitter-card: true diff --git a/assets/header.png b/nbs/figures/HAMUX-header.png similarity index 100% rename from assets/header.png rename to nbs/figures/HAMUX-header.png diff --git a/nbs/figures/HypersynapseOverview.png b/nbs/figures/HypersynapseOverview.png new 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index 1239dea..0000000 --- a/nbs/index.ipynb +++ /dev/null @@ -1,610 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "bibliography: references.bib\n", - "\n", - "---" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# HAMUX\n", - "\n", - "> A New Class of Deep Learning Library Built around **ENERGY**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide \n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import warnings\n", - "import os\n", - "from IPython.display import display, HTML" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "warnings.filterwarnings('ignore')\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\"HAMUX\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#|echo: false\n", - "display(HTML(\"\"\"\n", - "\"HAMUX\n", - "\"\"\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Part proof-of-concept, part functional prototype, HAMUX is designed to bridge modern AI architectures and Hopfield Networks. \n", - "\n", - "**HAMUX**: A **H**ierarchical **A**ssociative **M**emory **U**ser e**X**perience. \n", - "\n", - "[Documentation](https://bhoov.github.io/hamux)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "

\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#|echo: false\n", - "display(HTML(\"\"\"\n", - "
\n", - " 🚧 HAMUX is in rapid development. Remember to specify the version when building off of HAMUX.\n", - "
\n", - "\"\"\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## A Universal Abstraction for Hopfield Networks\n", - "\n", - "HAMUX fully captures the the energy fundamentals of Hopfield Networks and enables anyone to:\n", - "\n", - "- 🧠 Build **DEEP** Hopfield nets\n", - "\n", - "- 🧱 With modular **ENERGY** components\n", - "\n", - "- 🏆 That resemble modern DL operations\n", - "\n", - "**Every** architecture built using HAMUX is a *dynamical system* guaranteed to have a *tractable energy* function that *converges* to a fixed point. Our deep [Hierarchical Associative Memories](https://arxiv.org/abs/2107.06446) (HAMs) have several additional advantages over traditional [Hopfield Networks](http://www.scholarpedia.org/article/Hopfield_network) (HNs):\n", - "\n", - "| Hopfield Networks (HNs) | Hierarchical Associative Memories (HAMs) |\n", - "|--------|------|\n", - "|HNs are only **two layers** systems | HAMs connect **any number** of layers|\n", - "|HNs model only **simple relationships** between layers | HAMs model **any complex but differentiable operation** (e.g., convolutions, pooling, attention, $\\ldots$)| \n", - "|HNs use only **pairwise synapses** | HAMs use **many-body synapses** (which we denote **HyperSynapses**) |\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## How does HAMUX work?" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> **HAMUX** is a
hypergraph of 🌀neurons connected via 🤝hypersynapses, an abstraction sufficiently general to model the complexity of connections used in modern AI architectures." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - " We conflate the terms hypersynapse and synapse regularly. We explicitly say \"pairwise synapse\" when referring to the classical understanding of synapses.\n", - "
\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo:false\n", - "display(HTML(\"\"\"\n", - "
\n", - " We conflate the terms hypersynapse and synapse regularly. We explicitly say \"pairwise synapse\" when referring to the classical understanding of synapses.\n", - "
\n", - "\"\"\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "HAMUX defines two fundamental building blocks of energy: the **🌀neuron layer** and the **🤝hypersynapse** (an abstraction of a pairwise synapse to include many-body interactions) connected via a [**hypergraph**](https://en.wikipedia.org/wiki/Hypergraph). It is a fully dynamical system, where the \"hidden state\" $x_i^l$ of each layer $l$ (blue squares in the figure below) is an independent variable that evolves over time. The update rule of each layer is entirely local; only signals from a layer's connected synapses (red circles in the figure below) can tell the hidden state how to change. This is shown in the following equation:\n", - "\n", - "$$\\tau \\frac{d x_{i}^{l}}{dt} = -\\frac{\\partial E}{\\partial g_i^l}$$\n", - "\n", - "where $g_i^l$ are the *activations* (i.e., non-linearities) on each neuron layer, described in the section on [Neuron Layers](#🌀Neuron-Layers). Concretely, we implement the above differential equation as the following discretized equation (where the bold ${\\mathbf x}_l$ is the collection of all elements in layer $l$'s state):\n", - "\n", - "$$ \\mathbf{x}_l^{(t+1)} = \\mathbf{x}_l^{(t)} - \\frac{dt}{\\tau} \\nabla_{\\mathbf{g}_l}E(t)$$\n", - "\n", - "HAMUX handles all the complexity of scaling this fundamental update equation to many layers and hyper synapses. In addition, it provides a *framework* to:\n", - "\n", - "1. Implement your favorite Deep Learning operations as a [HyperSynapse](https://bhoov.github.io/hamux/synapses.html) \n", - "2. Port over your favorite activation functions as [Lagrangians](https://bhoov.github.io/hamux/lagrangians.html)\n", - "3. Connect your layers and hypersynapses into a [HAM](https://bhoov.github.io/hamux/ham.html) (using a hypergraph as the data structure)\n", - "4. Inject your data into the associative memory\n", - "5. Automatically calculate and descend the energy given the hidden states at any point in time\n", - "\n", - "Use these features to train any hierarchical associative memory on your own data! All of this made possible by [JAX](https://github.com/google/jax). \n", - "\n", - "The `examples/` subdirectory contains a (growing) list of examples on how to apply HAMUX on real data." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - "\"HAMUX\n", - "
Explaining the \"energy fundamentals\" of HAMUX (Layers and Synapses, left) using a 4-layer, 3-synapse example HAM (middle) that can be built using the code on the right.
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\n", - "\"HAMUX\n", - "
Explaining the \"energy fundamentals\" of HAMUX (Layers and Synapses, left) using a 4-layer, 3-synapse example HAM (middle) that can be built using the code on the right.
\n", - "
\n", - "\"\"\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 🌀Neuron Layers\n", - "\n", - "Neuron layers are the recurrent unit of a HAM; that is, 🌀neurons keep a state that changes over time according to the dynamics of the system. These states always change to minimize the global energy function of the system.\n", - "\n", - "For those of us familiar with traditional Deep Learning architectures, we are familiar with nonlinear activation functions like the `ReLU` and `SoftMax`. A neuron layer in HAMUX is exactly that: a nonlinear activation function defined on some neuron. However, we need to express the activation function as a convex **Lagrangian function** $\\mathcal{L}$ that is the integral of the desired non-linearity such that the **derivative of the Lagrangian function** $\\nabla \\mathcal{L}$ is our desired non-linearity. E.g., consider the ReLU:\n", - "\n", - "$$\n", - "\\begin{align*}\n", - "\\mathcal{L}(x) &:= \\frac{1}{2} (\\max(x, 0))^2\\\\\n", - "\\nabla \\mathcal{L} &= \\max(x, 0) = \\mathrm{relu}(x)\\\\\n", - "\\end{align*}\n", - "$$\n", - "\n", - "\n", - "We need to define our activation layer in terms of the *Lagrangian* of the ReLU instead of the ReLU itself. Extending this constraint to other nonlinearities makes it possible to define the scalar energy for any neuron in a HAM. It turns out that many activation functions used in today's Deep Learning landscape are expressible as a Lagrangian. HAMUX is \"batteries-included\" for many common activation functions including `relu`s, `softmax`es, `sigmoid`s, `LayerNorm`s, etc. See our [documentation on Lagrangians](https://bhoov.github.io/hamux/lagrangians.html) for examples on how to implement efficient activation functions from Lagrangians in JAX. We show how to turn Lagrangians into usable energy building blocks in our [documentation on neuron layers](https://bhoov.github.io/hamux/layers.html).\n", - "\n", - "\n", - "### 🤝HyperSynapses\n", - "\n", - "A 🤝hypersynapse ONLY sees activations of connected 🌀neuron layers. Its one job: report HIGH ⚡️energy if the connected activations are dissimilar and LOW ⚡️energy when they are aligned. Hypersynapses can resemble convolutions, dense multiplications, even attention… Take a look at our [documentation on (hyper)synapses](https://bhoov.github.io/hamux/synapses.html)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - " 🚨 Point of confusion: modern AI frameworks have ConvLayers and NormalizationLayers. In HAMUX, these would be more appropriately called ConvSynapses and NormalizationLagrangians.\n", - "
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\n", - " 🚨 Point of confusion: modern AI frameworks have ConvLayers and NormalizationLayers. In HAMUX, these would be more appropriately called ConvSynapses and NormalizationLagrangians.\n", - "
\n", - "\"\"\"))\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Install\n", - "\n", - "**From pip**:\n", - "\n", - "```\n", - "pip install hamux\n", - "```\n", - "\n", - "If you are using accelerators beyond the CPU you will need to additionally install the corresponding `jax` and `jaxlib` versions following [their documentation](https://github.com/google/jax#installation). E.g.,\n", - "\n", - "```\n", - "pip install --upgrade \"jax[cuda]\" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html\n", - "```\n", - "\n", - "\n", - "**From source**:\n", - "\n", - "After cloning:\n", - "```\n", - "cd hamux\n", - "conda env create -f environment.yml\n", - "conda activate hamux\n", - "pip install --upgrade \"jax[cuda]\" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html # If using GPU accelerator\n", - "pip install -e .\n", - "pip install -r requirements-dev.txt # To run the examples\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## How to Use" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import hamux as hmx\n", - "import jax.numpy as jnp\n", - "import jax\n", - "import jax.tree_util as jtu" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can build a simple 4 layer HAM architecture using the following code" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2023-01-06 15:36:55.191325: E external/org_tensorflow/tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:267] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n", - "WARNING:jax._src.lib.xla_bridge:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n" - ] - } - ], - "source": [ - "#|output:false\n", - "layers = [\n", - " hmx.TanhLayer((32,32,3)), # e.g., CIFAR Images\n", - " hmx.SigmoidLayer((11,11,1000)), # CIFAR patches\n", - " hmx.SoftmaxLayer((10,)), # CIFAR Labels\n", - " hmx.SoftmaxLayer((1000,)), # Hidden Memory Layer\n", - "]\n", - "\n", - "synapses = [\n", - " hmx.ConvSynapse((3,3), strides=3),\n", - " hmx.DenseSynapse(),\n", - " hmx.DenseSynapse(),\n", - "]\n", - "\n", - "connections = [\n", - " ([0,1], 0),\n", - " ([1,3], 1),\n", - " ([2,3], 2),\n", - "]\n", - "\n", - "rng = jax.random.PRNGKey(0)\n", - "param_key, state_key, rng = jax.random.split(rng, 3)\n", - "states, ham = hmx.HAM(layers, synapses, connections).init_states_and_params(param_key, state_key=state_key);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Notice that we did not specify any output channel shapes in the synapses. The desired output shape is computed from the layers connected to each synapse during `hmx.HAM.init_states_and_params`.\n", - "\n", - "We have two fundamental objects: `states` and `ham`. The `ham` object contains the connectivity structure of the HAM (e.g., layer+hypersynapse+hypergraph information) alongside the **parameters** of the network. The `states` object is a list of length `nlayers` where each item is a tensor representing the neuron states of the corresponding layer. \n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "assert len(states) == ham.n_layers\n", - "assert all([state.shape == layer.shape for state, layer in zip(states, ham.layers)])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We make it easy to run the dynamics of any HAM. Every `forward` function is defined external to the memory and can be modified to extract different memories from different layers, as desired. The general steps for any forward function are:\n", - "\n", - "1. Initialize the dynamic states\n", - "2. Inject an initial state into the system\n", - "3. Run dynamics, calculating energy gradient at every point in time.\n", - "4. Return the layer state/activation of interest" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def fwd(model, x, depth=15, dt=0.1):\n", - " \"\"\"Assuming a trained HAM, run association with the HAM on batched inputs `x`\"\"\"\n", - " # 1. Initialize model states at t=0. Account for batch size\n", - " xs = model.init_states(x.shape[0])\n", - " \n", - " # Inject initial state\n", - " xs[0] = x \n", - "\n", - " energies = []\n", - " for i in range(depth):\n", - " energies.append(model.venergy(xs)) # If desired, observe the energy\n", - " dEdg = model.vdEdg(xs) # Calculate the gradients\n", - " xs = jtu.tree_map(lambda x, stepsize, grad: x - stepsize * grad, xs, model.alphas(dt), dEdg)\n", - "\n", - " \n", - " # Return probabilities of our label layer\n", - " probs = model.layers[-2].activation(xs[-2])\n", - " return jnp.stack(energies), probs" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(3, 10)\n" - ] - } - ], - "source": [ - "batch_size=3\n", - "x = jax.random.normal(jax.random.PRNGKey(2), (batch_size, 32,32,3))\n", - "energies, probs = fwd(ham, x, depth=20, dt=0.3)\n", - "print(probs.shape) # batchsize, nclasses\n", - "assert jnp.allclose(probs.sum(-1), 1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "fig,ax = plt.subplots(1)\n", - "ax.plot(energies)\n", - "ax.set_title(\"Convergence of HAM Energy over time\")\n", - "ax.set_xlabel(\"Timesteps\")\n", - "ax.set_ylabel(\"Energy\");\n", - "plt.show(fig)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - " More examples coming soon!\n", - "
\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#|echo: false\n", - "display(HTML(\"\"\"\n", - "
\n", - " More examples coming soon!\n", - "
\n", - "\"\"\"))\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## The Energy Function vs the Loss Function" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We use JAX's autograd to descend the energy function of our system AND the loss function of our task. The derivative of the energy is always taken wrt to our *states*; the derivative of the loss function is always taken wrt our *parameters*. During training, we change our parameters to optimize the *Loss Function*. During inference, we assume that parameters are constant." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Autograd for Descending Energy**\n", - "\n", - "Every `HAM` defines the energy function for our system, which is everything we need to compute memories of the system. Naively, we can calculate $\\nabla_x E$: the derivative of the energy function wrt the *states* of each layer:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "stepsize = 0.01\n", - "fscore_naive = jax.grad(ham.energy)\n", - "next_states = jax.tree_util.tree_map(lambda state, score: state - stepsize, states, fscore_naive(states))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "But it turns out we improve the efficiency of our network if we instead take $\\nabla_g E$: the derivative of the energy wrt the *activations* instead of the *states*. They have the same local minima, even though the trajectory to get there is different. Some nice terms cancel, and we get:\n", - "\n", - "$$\\nabla_g E_\\text{HAM} = x + \\nabla_g E_\\text{synapse}$$" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "stepsize = 0.01\n", - "def fscore_smart(xs):\n", - " gs = ham.activations(xs)\n", - " return jax.tree_util.tree_map(lambda x, nabla_g_Esyn: x + nabla_g_Esyn, xs, jax.grad(ham.synapse_energy)(gs))\n", - "\n", - "next_states = jax.tree_util.tree_map(lambda state, score: state - stepsize, states, fscore_smart(states))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Credits\n", - "\n", - "Read our extended abstract on OpenReview: [HAMUX: A Universal Abstraction for Hierarchical Hopfield Networks](https://openreview.net/forum?id=SAv3nhzNWhw)\n", - "\n", - "Work is a collaboration between the [MIT-IBM Watson AI Lab](https://mitibmwatsonailab.mit.edu/) and the [PoloClub](https://poloclub.github.io/) @ GA Tech. \n", - "- [Ben Hoover](https://www.bhoov.com/) (IBM & GATech)\n", - "- [Polo Chau](https://faculty.cc.gatech.edu/~dchau/) (GATech)\n", - "- [Hendrik Strobelt](http://hendrik.strobelt.com/) (IBM)\n", - "- [Dmitry Krotov](https://mitibmwatsonailab.mit.edu/people/dmitry-krotov/) (IBM)\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:hamux]", - "language": "python", - "name": "conda-env-hamux-py" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/nbs/index.qmd b/nbs/index.qmd new file mode 100644 index 0000000..5a530d3 --- /dev/null +++ b/nbs/index.qmd @@ -0,0 +1,228 @@ +# HAMUX +> A universal language for describing Associative Memories as hypergraphs + +A new class of Deep Learning model built around **ENERGY**. + +```{python} +#| echo: false +import numpy as np +import matplotlib.pyplot as plt +import warnings +import os +from IPython.display import display, HTML +``` + +```{python} +#| echo: false +warnings.filterwarnings('ignore') +os.environ["CUDA_VISIBLE_DEVICES"] = "" +``` + +![HAMUX Logo](./figures/HAMUX-header.png) + +Part proof-of-concept, part functional prototype, HAMUX is designed to bridge modern AI architectures and Hopfield Networks. + +**HAMUX**: A **H**ierarchical **A**ssociative **M**emory **U**ser e**X**perience. + +[Documentation](https://bhoov.github.io/hamux). Also described in our [tutorial on Associative Memory](https://arxiv.org/abs/2507.06211) (ch. 3). + +### Quickstart + +The code in this codebase is meant to be as minimal as possible. *We do not provide a complete component library for associative memory*. It consists of 1 main logic file (`hamux/core.py`) (`<200` lines of important code), 1 file of example lagrangians (`hamux/lagrangians.py`) and 1 demo notebook: **`demo.ipynb`**. Intended for research code. + +## A Universal Abstraction for Hopfield Networks + +HAMUX fully captures the the energy fundamentals of Hopfield Networks and enables anyone to: + +- 🧠 Build **DEEP** Hopfield nets + +- 🧱 With modular **ENERGY** components + +- 🏆 That resemble modern DL operations + +**Every** architecture built using HAMUX is a formal Associative Memory (AM). That is, the architecture defines a *tractable energy*, whose minimization describes a *dynamical system* that is guaranteed to *converge* to a fixed point. [Hierarchical Associative Memories](https://arxiv.org/abs/2107.06446) (HAMs) have several additional advantages over traditional [Hopfield Networks](http://www.scholarpedia.org/article/Hopfield_network) (HNs): + +| Hopfield Networks (HNs) | Hierarchical Associative Memories (HAMs) | +|--------|------| +|HNs are only **two layers** systems | HAMs connect **any number** of layers| +|HNs have **limited storage capacity** | HAMs can be used to describe Associative Memories with much denser storage | +|HNs model only **simple relationships** between layers | HAMs model **any complex but differentiable operation** (e.g., convolutions, pooling, attention, $\ldots$)| +|HNs use only **pairwise synapses** | HAMs can also use **many-body synapses** (which we denote **HyperSynapses**) | + +## How does HAMUX work? + +![**HAMUX is a [hypergraph](https://en.wikipedia.org/wiki/Hypergraph) of 🌀neurons connected via 🤝hypersynapses**, an abstraction sufficiently general to model any conceivable Associative Memory.](./figures/hamux_overview.png) + +See our walkthrough in [this notebook](./nbs/00_core.ipynb) for a more detailed explanation of how everything works. + +In summary, this library handles all the complexity of scaling modular, learnable energy functions that interconnect many layers and hypersynapses. It is a barebones framework to explore Associative Memories that look like Deep Learning architectures. + +1. Implement your favorite Deep Learning operations as a [HyperSynapse](./00_core.ipynb#sec-hypersynapses) +2. Port over your favorite activation functions as [Lagrangians](./01_lagrangians.ipynb) +3. Connect layers and hypersynapses into a hypergraph with a [single total energy](./00_core.ipynb#sec-energy-hypergraphs). +4. Easily use autograd for descending states. + +All of this made possible by [JAX](https://github.com/google/jax) and [equinox](https://github.com/patrick-kidger/equinox). + +## Installation + +Install latest from the GitHub [repo](https://github.com/bhoov/hamux) + +```sh +$ pip install git+https://github.com/bhoov/hamux.git +``` + +or from [pypi](https://pypi.org/project/hamux/) + +```sh +pip install hamux +``` + +## How to use + + +```{python} +import hamux as hmx +import jax, jax.numpy as jnp, jax.random as jr, jax.tree_util as jtu +import equinox as eqx +from typing import * +import matplotlib.pyplot as plt +``` + +```{python} +class LinearSynapse(eqx.Module): + """The energy synapse corrolary of the linear layer in standard neural networks""" + W: jax.Array + def __call__(self, xhat1:jax.Array, xhat2:jax.Array): + return xhat1 @ self.W @ xhat2 + + @classmethod + def rand_init(cls, key: jax.Array, D1: int, D2: int): + Winit = 0.02 * jr.normal(key, (D1, D2)) + return cls(W=Winit) + +key = jr.key(0) +nhid = 9 +nlabel = 8 +ninput = 7 + +neurons = { + "input": hmx.NeuronLayer(hmx.lagr_identity, (ninput,)), + "labels": hmx.NeuronLayer(hmx.lagr_softmax, (nlabel,)), + "hidden": hmx.NeuronLayer(hmx.lagr_softmax, (nhid,)) +} + +synapses = { + "dense1": LinearSynapse.rand_init(key, ninput, nhid), + "dense2": LinearSynapse.rand_init(key, nlabel, nhid) +} + +connections = [ + (("input", "hidden"), "dense1"), + (("labels", "hidden"), "dense2") +] + +ham = hmx.HAM(neurons, synapses, connections) + +``` + +```{python} +xs = ham.init_states() # No batch size +xhats = ham.activations(xs) + +ham.energy_tree(xhats, xs) +ham.energy(xhats, xs) +ham.dEdact(xhats, xs) +``` + +```{python} +vham = ham.vectorize() +bs = 3 +xs = vham.init_states(bs) # Batch size 3 +xhats = vham.activations(xs) + +print(vham.energy_tree(xhats, xs)) +print(vham.energy(xhats, xs)) +print(vham.dEdact(xhats, xs)) + +ham = vham.unvectorize() +``` + + +We can check that the energy descent using randomize weights behaves as expected. + +```{python} +# Randomize the initial states +rkey = jr.key(42) +key_tree = dict(zip(xs.keys(), jr.split(rkey, len(xs)))) +xs = jtu.tree_map(lambda key, x: jr.normal(key, x.shape), key_tree, xs) +xhats = vham.activations(xs) + +nsteps = 40 +step_size = 0.5 +energies = jnp.empty((nsteps, bs)) +for i in range(nsteps): + energy, dEdxhats = vham.dEdact(xhats, xs, return_energy=True) + energies = energies.at[i].set(energy) + xs = jtu.tree_map(lambda x, u: x - step_size * u, xs, dEdxhats) + +plt.plot(jnp.arange(nsteps), energies) +``` + +See the [`nbs/_examples`](https://github.com/bhoov/hamux/tree/main/nbs/_examples) directory for more examples. + +## Developing locally + +`uv` (in `pyproject.toml`) handles all dependencies, `nbdev` (and its `settings.ini`) handles all packaging. We handle syncing between the `pyproject.toml` and `settings.ini` files using `scripts/sync_dependencies.py`. + +:::{.callout-warning} +Package is currently based on a fork of [nbdev](https://github.com/bhoov/nbdev/tree/qmd_support) that allows development in plain text `.qmd` files. +::: + +**Prerequisite**: Download ['uv'](https://docs.astral.sh/uv/) + +```sh +uv sync +uv run uv pip install -e . + +# OPTIONAL: Add GPU enabled JAX e.g., for CUDA 12 +uv run uv pip install -U "jax[cuda12]" + +source .venv/bin/activate +nbdev_prepare +``` + +```sh +uv sync +source .venv/bin/activate + +# Make changes to source files in `nbs/`. +uv run nbdev_prepare # Before committing changes, export and test library +uv run nbdev_preview # Preview docs +``` + +### VSCode for developmentautomatic library export +> Never let your `.qmd` source get out of sync with your `.py` library. + +VSCode has an excellent interactive mode for developing quarto files. We install the [`Run on Save`](https://marketplace.visualstudio.com/items?itemName=emeraldwalk.RunOnSave) extension to keep the `.qmd` files in sync with the `.py` library, removing the need for explicit `nbdev_export` commands. + +To accomplish this, copy and paste the following into your user/workspace settings (`Cmd+Shift+P` then either "Preferences: Open User settings (JSON)" or "Preferences: Open Workspace settings (JSON)") + +```js +{ + "files.watcherExclude": { + "**/.git/objects/**": true, + "**/.git/subtree-cache/**": true, + "**/node_modules/*/**": true, + "**/.hg/store/**": true, + }, + "emeraldwalk.runonsave": { + "commands": [ + { + "match": "nbs/.*\\.qmd$", // Replace with your own nbs/ directory + "cmd": "source ${workspaceFolder}/.venv/bin/activate && nbdev_export", // Replace with a path to your python env where `nbdev` is installed + } + ] + } +} +``` diff --git a/nbs/nbdev.yml b/nbs/nbdev.yml index 0c98219..ae7a481 100644 --- a/nbs/nbdev.yml +++ b/nbs/nbdev.yml @@ -2,8 +2,8 @@ project: output-dir: _docs website: - title: "hamux" + title: "HAMUX" site-url: "https://bhoov.github.io/hamux" - description: "A Deep Learning framework built around ENERGY" + description: "Energy formulation for deep learning" repo-branch: main repo-url: "https://github.com/bhoov/hamux" diff --git a/nbs/references.bib b/nbs/references.bib index 02670f8..5d9836a 100644 --- a/nbs/references.bib +++ b/nbs/references.bib @@ -1,8 +1,1386 @@ +% References taken from the DrDAM paper +@article{krotov2019unsupervised, + title={Unsupervised learning by competing hidden units}, + author={Krotov, Dmitry and Hopfield, John J}, + journal={Proceedings of the National Academy of Sciences}, + volume={116}, + number={16}, + pages={7723--7731}, + year={2019}, + publisher={National Acad Sciences}, + url={https://www.pnas.org/content/pnas/116/16/7723.full.pdf} +} + +@article{choromanski2020rethinking, + title={Rethinking Attention with Performers}, + author={Choromanski, Krzysztof and Likhosherstov, Valerii and Dohan, David and Song, Xingyou and Gane, Andreea and Sarlos, Tamas and Hawkins, Peter and Davis, Jared and Mohiuddin, Afroz and Kaiser, Lukasz and others}, + journal={Proceedings of ICLR}, + year={2020}, + url={https://arxiv.org/pdf/2009.14794.pdf} +} + +@inproceedings{katharopoulos2020transformers, + title={Transformers are rnns: Fast autoregressive transformers with linear attention}, + author={Katharopoulos, Angelos and Vyas, Apoorv and Pappas, Nikolaos and Fleuret, Fran{\c{c}}ois}, + booktitle={International conference on machine learning}, + pages={5156--5165}, + year={2020}, + organization={PMLR}, + url={https://proceedings.mlr.press/v119/katharopoulos20a/katharopoulos20a.pdf} +} + +@article{rahimi2007random, + title={Random features for large-scale kernel machines}, + author={Rahimi, Ali and Recht, Benjamin}, + journal={Advances in neural information processing systems}, + year={2007}, + url={https://proceedings.neurips.cc/paper/2007/file/013a006f03dbc5392effeb8f18fda755-Paper.pdf} +} + +@inproceedings{likhosherstov2023denseexponential, + title={Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel}, + author={Valerii Likhosherstov and Krzysztof Marcin Choromanski and Kumar Avinava Dubey and Frederick Liu and Tamas Sarlos and Adrian Weller}, + booktitle={Thirty-seventh Conference on Neural Information Processing Systems}, + year={2023}, + url={https://openreview.net/forum?id=S0xrBMFihS} +} + +@inproceedings{jain2023mnemosyne, + title={Mnemosyne: Learning to Train Transformers with Transformers}, + author={Deepali Jain and Krzysztof Marcin Choromanski and Kumar Avinava Dubey and Sumeet Singh and Vikas Sindhwani and Tingnan Zhang and Jie Tan}, + booktitle={Thirty-seventh Conference on Neural Information Processing Systems}, + year={2023}, + url={https://openreview.net/forum?id=Fdfyga5i0A} +} + +@inproceedings{le2013fastfood, + title={Fastfood-approximating kernel expansions in loglinear time}, + author={Le, Quoc and Sarl{\'o}s, Tam{\'a}s and Smola, Alex and others}, + booktitle={Proceedings of the international conference on machine learning}, + volume={85}, + number={8}, + year={2013}, + url={https://proceedings.mlr.press/v28/le13.pdf} +} + + +@article{hu2024nonparametric, + author = {Jerry Yao-Chieh Hu and Bo-Yu Chen and Dennis Wu and Feng Ruan and Han Liu}, + title = {Nonparametric Modern Hopfield Models}, + journal = {arXiv preprint arXiv:2404.03900}, + year = {2024}, + url = {https://arxiv.org/pdf/2404.03900.pdf}, +} + +@article{wu2024uniform, + author = {Dennis Wu and Jerry Yao-Chieh Hu and Teng-Yun Hsiao and Han Liu}, + title = {Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models}, + journal = {arXiv preprint arXiv:2404.03900}, + year = {2024}, + url = {https://arxiv.org/pdf/2404.03827.pdf}, +} + +@article{vaswani2017attention, + title={Attention is all you need}, + author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia}, + journal={Advances in neural information processing systems}, + volume={30}, + year={2017}, + url={https://proceedings.neurips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf} +} + +@article{mceliece1987capacity, + title={The capacity of the Hopfield associative memory}, + author={McEliece, ROBERTJ and Posner, Edwardc and Rodemich, EUGENER and Venkatesh, SANTOSHS}, + journal={IEEE transactions on Information Theory}, + volume={33}, + number={4}, + pages={461--482}, + year={1987}, + publisher={IEEE} +} + +@article{amit1985storing, + title={Storing infinite numbers of patterns in a spin-glass model of neural networks}, + author={Amit, Daniel J and Gutfreund, Hanoch and Sompolinsky, Haim}, + journal={Physical Review Letters}, + volume={55}, + number={14}, + pages={1530}, + year={1985}, + publisher={APS} +} + +@article{hopfield1982neural, + title={Neural networks and physical systems with emergent collective computational abilities.}, + author={Hopfield, John J}, + journal={Proceedings of the national academy of sciences}, + volume={79}, + number={8}, + pages={2554--2558}, + year={1982}, + publisher={National Acad Sciences} +} + +@inproceedings{ramsauer2021hopfield, + title={Hopfield Networks is All You Need}, + author={Hubert Ramsauer and Bernhard Sch{\"a}fl and Johannes Lehner and Philipp Seidl and Michael Widrich and Lukas Gruber and Markus Holzleitner and Thomas Adler and David Kreil and Michael K Kopp and G{\"u}nter Klambauer and Johannes Brandstetter and Sepp Hochreiter}, + booktitle={International Conference on Learning Representations}, + year={2021}, + url={https://openreview.net/forum?id=tL89RnzIiCd} +} + +@article{krotov2016dense, + title={Dense associative memory for pattern recognition}, + author={Krotov, Dmitry and Hopfield, John J}, + journal={Advances in neural information processing systems}, + volume={29}, + year={2016} +} + +@article{krotov2018dense, + title={Dense associative memory is robust to adversarial inputs}, + author={Krotov, Dmitry and Hopfield, John}, + journal={Neural computation}, + volume={30}, + number={12}, + pages={3151--3167}, + year={2018}, + publisher={MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info~…} +} + + +@inproceedings{krotov2021large, + title={Large Associative Memory Problem in Neurobiology and Machine Learning}, + author={Krotov, Dmitry and Hopfield, John J}, + booktitle={International Conference on Learning Representations}, + year={2021} +} + +@inproceedings{millidge2022universal, + title={Universal hopfield networks: A general framework for single-shot associative memory models}, + author={Millidge, Beren and Salvatori, Tommaso and Song, Yuhang and Lukasiewicz, Thomas and Bogacz, Rafal}, + booktitle={International Conference on Machine Learning}, + pages={15561--15583}, + year={2022}, + organization={PMLR} +} + +@article{demircigil2017model, + title={On a model of associative memory with huge storage capacity}, + author={Demircigil, Mete and Heusel, Judith and L{\"o}we, Matthias and Upgang, Sven and Vermet, Franck}, + journal={Journal of Statistical Physics}, + volume={168}, + number={2}, + pages={288--299}, + year={2017}, + publisher={Springer} +} + + +@inproceedings{kar2012random, + title={Random feature maps for dot product kernels}, + author={Kar, Purushottam and Karnick, Harish}, + booktitle={Artificial intelligence and statistics}, + pages={583--591}, + year={2012}, + organization={PMLR}, + url={https://proceedings.mlr.press/v22/kar12/kar12.pdf} +} + +@inproceedings{hamid2014compact, + title={Compact random feature maps}, + author={Hamid, Raffay and Xiao, Ying and Gittens, Alex and DeCoste, Dennis}, + booktitle={International conference on machine learning}, + pages={19--27}, + year={2014}, + organization={PMLR}, + url={https://proceedings.mlr.press/v32/hamid14.pdf} +} + +@inproceedings{pham2013fast, + title={Fast and scalable polynomial kernels via explicit feature maps}, + author={Pham, Ninh and Pagh, Rasmus}, + booktitle={Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining}, + pages={239--247}, + year={2013}, + url={https://dl.acm.org/doi/pdf/10.1145/2487575.2487591} +} + +@book{bottou2007large, + title={Large-scale kernel machines}, + author={Bottou, L{\'e}on}, + year={2007}, + publisher={MIT press} +} + +@article{cortes1995support, + title={Support-vector networks}, + author={Cortes, Corinna and Vapnik, Vladimir}, + journal={Machine learning}, + volume={20}, + pages={273--297}, + year={1995}, + publisher={Springer}, + url={https://link.springer.com/content/pdf/10.1007/bf00994018.pdf} +} + +@incollection{leslie2001spectrum, + title={The spectrum kernel: A string kernel for SVM protein classification}, + author={Leslie, Christina and Eskin, Eleazar and Noble, William Stafford}, + booktitle={Biocomputing 2002}, + pages={564--575}, + year={2001}, + publisher={World Scientific}, + url={https://www.worldscientific.com/doi/abs/10.1142/9789812799623_0053} +} + +@article{borgwardt2005protein, + title={Protein function prediction via graph kernels}, + author={Borgwardt, Karsten M and Ong, Cheng Soon and Sch{\"o}nauer, Stefan and Vishwanathan, SVN and Smola, Alex J and Kriegel, Hans-Peter}, + journal={Bioinformatics}, + volume={21}, + number={suppl\_1}, + pages={i47--i56}, + year={2005}, + publisher={Oxford University Press}, + url={https://dl.acm.org/doi/abs/10.1093/bioinformatics/bti1007} +} + +@inproceedings{muller1997predicting, + title={Predicting time series with support vector machines}, + author={M{\"u}ller, K-R and Smola, Alexander J and R{\"a}tsch, Gunnar and Sch{\"o}lkopf, Bernhard and Kohlmorgen, Jens and Vapnik, Vladimir}, + booktitle={International conference on artificial neural networks}, + pages={999--1004}, + year=1997, + organization={Springer}, + url={https://link.springer.com/chapter/10.1007/BFb0020283} +} + +@article{choromanski2017unreasonable, + title={The unreasonable effectiveness of structured random orthogonal embeddings}, + author={Choromanski, Krzysztof M and Rowland, Mark and Weller, Adrian}, + journal={Advances in neural information processing systems}, + volume={30}, + year={2017}, + url={https://proceedings.neurips.cc/paper/2017/file/bf8229696f7a3bb4700cfddef19fa23f-Paper.pdf} +} + +@inproceedings{Le2015TinyIV, + title={Tiny ImageNet Visual Recognition Challenge}, + author={Ya Le and Xuan S. Yang}, + year={2015}, + url={https://api.semanticscholar.org/CorpusID:16664790} +} + +@article{frey1991letter, + title={Letter recognition using Holland-style adaptive classifiers}, + author={Frey, Peter W and Slate, David J}, + journal={Machine learning}, + volume={6}, + pages={161--182}, + year={1991}, + publisher={Springer} +} + +@article{krizhevsky2009learning, + title={Learning multiple layers of features from tiny images}, + author={Krizhevsky, Alex and Hinton, Geoffrey and others}, + year={2009}, + publisher={Toronto, ON, Canada} +} + +@software{jax2018github, + author = {James Bradbury and Roy Frostig and Peter Hawkins and Matthew James Johnson and Chris Leary and Dougal Maclaurin and George Necula and Adam Paszke and Jake Vander{P}las and Skye Wanderman-{M}ilne and Qiao Zhang}, + title = {{JAX}: composable transformations of {P}ython+{N}um{P}y programs}, + url = {http://github.com/google/jax}, + version = {0.3.13}, + year = {2018}, +} + +@InProceedings{li2023transformers, + title = {Transformers as Algorithms: Generalization and Stability in In-context Learning}, + author = {Li, Yingcong and Ildiz, Muhammed Emrullah and Papailiopoulos, Dimitris and Oymak, Samet}, + booktitle = {Proceedings of the 40th International Conference on Machine Learning}, + pages = {19565--19594}, + year = {2023}, + editor = {Krause, Andreas and Brunskill, Emma and Cho, Kyunghyun and Engelhardt, Barbara and Sabato, Sivan and Scarlett, Jonathan}, + volume = {202}, + series = {Proceedings of Machine Learning Research}, + month = {23--29 Jul}, + publisher = {PMLR}, + pdf = {https://proceedings.mlr.press/v202/li23l/li23l.pdf}, + url = {https://proceedings.mlr.press/v202/li23l.html}, +} + +@article{ambrogioni2023search_old, + title={In search of dispersed memories: Generative diffusion models are associative memory networks}, + author={Ambrogioni, Luca}, + journal={arXiv preprint arXiv:2309.17290}, + year={2023} +} + + +@Article{ambrogioni2023search, +AUTHOR = {Ambrogioni, Luca}, +TITLE = {{In Search of Dispersed Memories: Generative Diffusion Models Are Associative Memory Networks}}, +JOURNAL = {Entropy}, +VOLUME = {26}, +YEAR = {2024}, +NUMBER = {5}, +ARTICLE-NUMBER = {381}, +URL = {https://www.mdpi.com/1099-4300/26/5/381}, +PubMedID = {38785630}, +ISSN = {1099-4300}, +ABSTRACT = {Uncovering the mechanisms behind long-term memory is one of the most fascinating open problems in neuroscience and artificial intelligence. Artificial associative memory networks have been used to formalize important aspects of biological memory. Generative diffusion models are a type of generative machine learning techniques that have shown great performance in many tasks. Similar to associative memory systems, these networks define a dynamical system that converges to a set of target states. In this work, we show that generative diffusion models can be interpreted as energy-based models and that, when trained on discrete patterns, their energy function is (asymptotically) identical to that of modern Hopfield networks. This equivalence allows us to interpret the supervised training of diffusion models as a synaptic learning process that encodes the associative dynamics of a modern Hopfield network in the weight structure of a deep neural network. Leveraging this connection, we formulate a generalized framework for understanding the formation of long-term memory, where creative generation and memory recall can be seen as parts of a unified continuum.}, +DOI = {10.3390/e26050381} +} + +@article{kozachkov2023neuron, + title={Neuron-Astrocyte Associative Memory}, + author={Kozachkov, Leo and Slotine, Jean-Jacques and Krotov, Dmitry}, + journal={arXiv preprint arXiv:2311.08135}, + year={2023} +} + +@article{kozachkov2023building, + title={Building transformers from neurons and astrocytes}, + author={Kozachkov, Leo and Kastanenka, Ksenia V and Krotov, Dmitry}, + journal={Proceedings of the National Academy of Sciences}, + volume={120}, + number={34}, + pages={e2219150120}, + year={2023}, + publisher={National Acad Sciences} +} + +@inproceedings{negri2023random, + title={Random Feature Hopfield Networks generalize retrieval to previously unseen examples}, + author={Negri, Matteo and Lauditi, Clarissa and Perugini, Gabriele and Lucibello, Carlo and Malatesta, Enrico Maria}, + booktitle={Associative Memory \& Hopfield Networks in 2023}, + year={2023} +} + +@article{negri2023storage, + title={Storage and learning phase transitions in the random-features hopfield model}, + author={Negri, Matteo and Lauditi, Clarissa and Perugini, Gabriele and Lucibello, Carlo and Malatesta, Enrico}, + journal={Physical Review Letters}, + volume={131}, + number={25}, + pages={257301}, + year={2023}, + publisher={APS} +} + +@inproceedings{hoover2023memory_old, + title={Memory in plain sight: A survey of the uncanny resemblances between diffusion models and associative memories}, + author={Hoover, Benjamin and Strobelt, Hendrik and Krotov, Dmitry and Hoffman, Judy and Kira, Zsolt and Chau, Duen Horng}, + booktitle={Associative Memory $\{$$\backslash$\&$\}$ Hopfield Networks in 2023}, + year={2023} +} + +@misc{hoover2023memory, + title={{Memory in Plain Sight: Surveying the Uncanny Resemblances of Associative Memories and Diffusion Models}}, + author={Benjamin Hoover and Hendrik Strobelt and Dmitry Krotov and Judy Hoffman and Zsolt Kira and Duen Horng Chau}, + year={2023}, + eprint={2309.16750}, + archivePrefix={arXiv}, + primaryClass={cs.LG}, + url={https://arxiv.org/abs/2309.16750}, +} + + + +@inproceedings{burns2022simplicial, + title={Simplicial Hopfield networks}, + author={Burns, Thomas F and Fukai, Tomoki}, + booktitle={The Eleventh International Conference on Learning Representations}, + year={2022} +} + +@article{krotov2023new, + title={A new frontier for hopfield networks}, + author={Krotov, Dmitry}, + journal={Nature Reviews Physics}, + volume={5}, + number={7}, + pages={366--367}, + year={2023}, + publisher={Nature Publishing Group UK London} +} + +@inproceedings{curtin2013fast, + title={Fast exact max-kernel search}, + author={Curtin, Ryan R and Ram, Parikshit and Gray, Alexander G}, + booktitle={Proceedings of the 2013 SIAM International Conference on Data Mining}, + pages={1--9}, + year={2013}, + organization={SIAM}, + url={https://doi.org/10.1137/1.9781611972832.1} +} + +@article{curtin2014dual, + title={Dual-tree fast exact max-kernel search}, + author={Curtin, Ryan R and Ram, Parikshit}, + journal={Statistical Analysis and Data Mining: The ASA Data Science Journal}, + volume={7}, + number={4}, + pages={229--253}, + year={2014}, + publisher={Wiley Online Library}, + url={https://doi.org/10.1002/sam.11218} +} + +@article{iatropoulos2022kernel, + title={Kernel memory networks: A unifying framework for memory modeling}, + author={Iatropoulos, Georgios and Brea, Johanni and Gerstner, Wulfram}, + journal={Advances in neural information processing systems}, + volume={35}, + pages={35326--35338}, + year={2022}, + url={https://proceedings.neurips.cc/paper_files/paper/2022/file/e55d081280e79e714debf2902e18eb69-Paper-Conference.pdf} +} + + +@article{hu2024sparse, + title={On sparse modern hopfield model}, + author={Hu, Jerry Yao-Chieh and Yang, Donglin and Wu, Dennis and Xu, Chenwei and Chen, Bo-Yu and Liu, Han}, + journal={Advances in Neural Information Processing Systems}, + volume={36}, + year={2023}, + url={https://proceedings.neurips.cc/paper_files/paper/2023/file/57bc0a850255e2041341bf74c7e2b9fa-Paper-Conference.pdf} +} + +@inproceedings{wu2024stanhop, + title={{ST}anHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction}, + author={Dennis Wu and Jerry Yao-Chieh Hu and Weijian Li and Bo-Yu Chen and Han Liu}, + booktitle={The Twelfth International Conference on Learning Representations}, + year={2024}, + url={https://openreview.net/forum?id=6iwg437CZs} +} + +@misc{schaeffer2024bridging, + title={Bridging Associative Memory and Probabilistic Modeling}, + author={Rylan Schaeffer and Nika Zahedi and Mikail Khona and Dhruv Pai and Sang Truong and Yilun Du and Mitchell Ostrow and Sarthak Chandra and Andres Carranza and Ila Rani Fiete and Andrey Gromov and Sanmi Koyejo}, + year={2024}, + eprint={2402.10202}, + archivePrefix={arXiv}, + primaryClass={cs.LG}, + url={https://arxiv.org/abs/2402.10202}, +} + + +@InProceedings{santos2024sparse, + title = {Sparse and Structured Hopfield Networks}, + author = {Santos, Saul Jos\'{e} Rodrigues Dos and Niculae, Vlad and Mcnamee, Daniel C and Martins, Andre}, + booktitle = {Proceedings of the 41st International Conference on Machine Learning}, + pages = {43368--43388}, + year = {2024}, + volume = {235}, + series = {Proceedings of Machine Learning Research}, + month = {21--27 Jul}, + publisher = {PMLR}, + pdf = {https://raw.githubusercontent.com/mlresearch/v235/main/assets/santos24a/santos24a.pdf}, + url = {https://proceedings.mlr.press/v235/santos24a.html}, +} + + + +@InProceedings{hu2024on, + title = {On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis}, + author = {Hu, Jerry Yao-Chieh and Lin, Thomas and Song, Zhao and Liu, Han}, + booktitle = {Proceedings of the 41st International Conference on Machine Learning}, + pages = {19327--19343}, + year = {2024}, + volume = {235}, + series = {Proceedings of Machine Learning Research}, + month = {21--27 Jul}, + publisher = {PMLR}, + pdf = {https://raw.githubusercontent.com/mlresearch/v235/main/assets/hu24j/hu24j.pdf}, + url = {https://proceedings.mlr.press/v235/hu24j.html}, +} + + + +@InProceedings{hu2024outlier, + title = {Outlier-Efficient Hopfield Layers for Large Transformer-Based Models}, + author = {Hu, Jerry Yao-Chieh and Chang, Pei-Hsuan and Luo, Haozheng and Chen, Hong-Yu and Li, Weijian and Wang, Wei-Po and Liu, Han}, + booktitle = {Proceedings of the 41st International Conference on Machine Learning}, + pages = {19123--19152}, + year = {2024}, + volume = {235}, + series = {Proceedings of Machine Learning Research}, + month = {21--27 Jul}, + publisher = {PMLR}, + pdf = {https://raw.githubusercontent.com/mlresearch/v235/main/assets/hu24a/hu24a.pdf}, + url = {https://proceedings.mlr.press/v235/hu24a.html}, +} + + + @article{hoover2024energy, + title={Energy transformer}, + author={Hoover, Benjamin and Liang, Yuchen and Pham, Bao and Panda, Rameswar and Strobelt, Hendrik and Chau, Duen Horng and Zaki, Mohammed and Krotov, Dmitry}, + journal={Advances in Neural Information Processing Systems}, + volume={36}, + year={2024}, + url={https://proceedings.neurips.cc/paper_files/paper/2023/file/57a9b97477b67936298489e3c1417b0a-Paper-Conference.pdf} +} + +@article{chaudhry2024long, + title={Long sequence hopfield memory}, + author={Chaudhry, Hamza and Zavatone-Veth, Jacob and Krotov, Dmitry and Pehlevan, Cengiz}, + journal={Advances in Neural Information Processing Systems}, + volume={36}, + year={2024}, + url={https://proceedings.neurips.cc/paper_files/paper/2023/file/aa32ebcdd2ce1bed4ef7f456fc8fa5c1-Paper-Conference.pdf} +} + +@misc{krotov2021hierarchical, + title={Hierarchical Associative Memory}, + author={Dmitry Krotov}, + year={2021}, + eprint={2107.06446}, + archivePrefix={arXiv}, + primaryClass={cs.NE}, + url={https://arxiv.org/abs/2107.06446}, +} + +@inproceedings{hoover2022a, + title={A Universal Abstraction for Hierarchical Hopfield Networks}, + author={Benjamin Hoover and Duen Horng Chau and Hendrik Strobelt and Dmitry Krotov}, + booktitle={The Symbiosis of Deep Learning and Differential Equations II}, + year={2022}, + url={https://openreview.net/forum?id=SAv3nhzNWhw} +} + + +@InProceedings{saha23end, + title = {End-to-end Differentiable Clustering with Associative Memories}, + author = {Saha, Bishwajit and Krotov, Dmitry and Zaki, Mohammed J and Ram, Parikshit}, + booktitle = {Proceedings of the 40th International Conference on Machine Learning}, + pages = {29649--29670}, + year = {2023}, + volume = {202}, + series = {Proceedings of Machine Learning Research}, + month = {23--29 Jul}, + publisher = {PMLR}, + pdf = {https://proceedings.mlr.press/v202/saha23a/saha23a.pdf}, + url = {https://proceedings.mlr.press/v202/saha23a.html}, +} + + + +@InProceedings{pmlr-v235-wu24i, + title = {Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models}, + author = {Wu, Dennis and Hu, Jerry Yao-Chieh and Hsiao, Teng-Yun and Liu, Han}, + booktitle = {Proceedings of the 41st International Conference on Machine Learning}, + pages = {53471--53514}, + year = {2024}, + volume = {235}, + series = {Proceedings of Machine Learning Research}, + month = {21--27 Jul}, + publisher = {PMLR}, + pdf = {https://raw.githubusercontent.com/mlresearch/v235/main/assets/wu24i/wu24i.pdf}, + url = {https://proceedings.mlr.press/v235/wu24i.html}, +} + + +@book{silverman1998density, + title={Density estimation for statistics and data analysis}, + author={Silverman, Bernard W}, + year={1998}, + publisher={Chapman \& Hall/CRC} +} + +@inproceedings{bottou2008tradeoffs, + title={The tradeoffs of large scale learning}, + author={Bottou, L{\'e}on and Bousquet, Olivier}, + booktitle={Advances in neural information processing systems}, + pages={161--168}, + year={2008} +} + +@book{devroye2013probabilistic, + title={A probabilistic theory of pattern recognition}, + author={Devroye, Luc and Gy{\"o}rfi, L{\'a}szl{\'o} and Lugosi, G{\'a}bor}, + volume={31}, + year={2013}, + publisher={Springer Science \& Business Media} +} + +@book{vapnik2006estimation, + title={Estimation of dependences based on empirical data}, + author={Vapnik, Vladimir}, + year={2006}, + publisher={Springer Science \& Business Media} +} + +@incollection{lugosi2002pattern, + title={Pattern classification and learning theory}, + author={Lugosi, G{\'a}bor}, + booktitle={Principles of nonparametric learning}, + pages={1--56}, + year={2002}, + publisher={Springer} +} + +@article{boucheron2005theory, + title={Theory of classification: A survey of some recent advances}, + author={Boucheron, St{\'e}phane and Bousquet, Olivier and Lugosi, G{\'a}bor}, + journal={ESAIM: probability and statistics}, + volume={9}, + pages={323--375}, + year={2005}, + publisher={EDP Sciences} +} + +@inproceedings{ram2023toward, + title={Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection}, + author={Ram, Parikshit and Gray, Alexander G and Samulowitz, Horst C and Bramble, Gregory}, + booktitle={Proceedings of the 2023 SIAM International Conference on Data Mining (SDM)}, + pages={802--810}, + year={2023}, + organization={SIAM}, + url={https://epubs.siam.org/doi/abs/10.1137/1.9781611977653.ch90} +} + +@article{hopfield1984Neurons, + title = {Neurons {{With Graded Response Have Collective Computational Properties Like Those}} of {{Two-State Neurons}}}, + author = {Hopfield, John}, + year = {1984}, + month = jun, + journal = {Proceedings of the National Academy of Sciences of the United States of America}, + volume = {81}, + pages = {3088--92}, + doi = {10.1073/pnas.81.10.3088}, + url = {https://www.pnas.org/doi/10.1073/pnas.81.10.3088} +} + +@article{hoover2022universal, + title={A Universal Abstraction for Hierarchical Hopfield Networks}, + author={Hoover, Benjamin and Chau, Duen Horng and Strobelt, Hendrik and Krotov, Dmitry}, + journal={The Symbiosis of Deep Learning and Differential Equations II}, + year={2022}, + url={https://openreview.net/forum?id=SAv3nhzNWhw} +} + +@inproceedings{1983Boltzmann, +author = {Hinton, Geoffrey and Sejnowski, Terrence}, +year = {1983}, +month = {01}, +pages = {448-453}, +title = {Optimal perceptual inference}, +booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition} +} + +@article{kl-divergence1951, + ISSN = {00034851}, + URL = {http://www.jstor.org/stable/2236703}, + author = {S. Kullback and R. A. Leibler}, + journal = {The Annals of Mathematical Statistics}, + number = {1}, + pages = {79--86}, + publisher = {Institute of Mathematical Statistics}, + title = {On Information and Sufficiency}, + urldate = {2025-06-16}, + volume = {22}, + year = {1951} +} + +@inbook{Hinton1985, author = {Ackley, David H. and Hinton, Geoffrey E. and Sejnowski, Terrence J.}, title = {A learning algorithm for Boltzmann machines}, year = {1988}, isbn = {0262010976}, publisher = {MIT Press}, address = {Cambridge, MA, USA}, booktitle = {Neurocomputing: Foundations of Research}, pages = {635–649}, numpages = {15} } + +@article{Hopfield1983UnlearningHA, + title={‘Unlearning’ has a stabilizing effect in collective memories}, + author={John J. Hopfield and David I. Feinstein and Richard G. Palmer}, + journal={Nature}, + year={1983}, + volume={304}, + pages={158-159}, + url={https://api.semanticscholar.org/CorpusID:4269710} +} + +@article{song2021trainebm, + title={How to train your energy-based models}, + author={Song, Yang and Kingma, Diederik P}, + journal={arXiv preprint arXiv:2101.03288}, + year={2021} +} + +@article{Hastings1970, + author = {Hastings, W. K.}, + title = {Monte Carlo sampling methods using Markov chains and their applications}, + journal = {Biometrika}, + volume = {57}, + number = {1}, + pages = {97-109}, + year = {1970}, + month = {04}, + abstract = {A generalization of the sampling method introduced by Metropolis et al. (1953) is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates. Examples of the methods, including the generation of random orthogonal matrices and potential applications of the methods to numerical problems arising in statistics, are discussed.}, + issn = {0006-3444}, + doi = {10.1093/biomet/57.1.97}, + url = {https://doi.org/10.1093/biomet/57.1.97}, + eprint = {https://academic.oup.com/biomet/article-pdf/57/1/97/23940249/57-1-97.pdf}, +} + +@ARTICLE{GemanS1984, + author={Geman, Stuart and Geman, Donald}, + journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, + title={Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images}, + year={1984}, + volume={PAMI-6}, + number={6}, + pages={721-741}, + keywords={Stochastic processes;Bayesian methods;Image restoration;Degradation;Markov random fields;Additive noise;Deformable models;Temperature distribution;Energy states;Annealing;Annealing;Gibbs distribution;image restoration;line process;MAP estimate;Markov random field;relaxation;scene modeling;spatial degradation}, + doi={10.1109/TPAMI.1984.4767596}} + + +@article{GelfandA1990, +author = {Alan E. Gelfand and Adrian F. M. Smith}, +title = {Sampling-Based Approaches to Calculating Marginal Densities}, +journal = {Journal of the American Statistical Association}, +volume = {85}, +number = {410}, +pages = {398--409}, +year = {1990}, +publisher = {ASA Website}, +doi = {10.1080/01621459.1990.10476213}, +URL = {https://www.tandfonline.com/doi abs/10.1080/01621459.1990.10476213 +}, +eprint = {https://www.tandfonline.com/doi/pdf/10.1080/01621459.1990.10476213} +} + + @inproceedings{ -krotov2021large, -title={Large Associative Memory Problem in Neurobiology and Machine Learning}, -author={Dmitry Krotov and John J. Hopfield}, -booktitle={International Conference on Learning Representations}, -year={2021}, -url={https://openreview.net/forum?id=X4y_10OX-hX} + song2021scorebased, + title={Score-Based Generative Modeling through Stochastic Differential Equations}, + author={Yang Song and Jascha Sohl-Dickstein and Diederik P Kingma and Abhishek Kumar and Stefano Ermon and Ben Poole}, + booktitle={International Conference on Learning Representations}, + year={2021}, + url={https://openreview.net/forum?id=PxTIG12RRHS} +} + +@article{ho2020denoising, + title={Denoising diffusion probabilistic models}, + author={Ho, Jonathan and Jain, Ajay and Abbeel, Pieter}, + journal={Advances in neural information processing systems}, + volume={33}, + pages={6840--6851}, + year={2020} +} + + +@InProceedings{sohl-dickstein15, + title = {Deep Unsupervised Learning using Nonequilibrium Thermodynamics}, + author = {Sohl-Dickstein, Jascha and Weiss, Eric and Maheswaranathan, Niru and Ganguli, Surya}, + booktitle = {Proceedings of the 32nd International Conference on Machine Learning}, + pages = {2256--2265}, + year = {2015}, + editor = {Bach, Francis and Blei, David}, + volume = {37}, + series = {Proceedings of Machine Learning Research}, + address = {Lille, France}, + month = {7}, + publisher = {PMLR}, + pdf = {http://proceedings.mlr.press/v37/sohl-dickstein15.pdf}, + url = {https://proceedings.mlr.press/v37/sohl-dickstein15.html}, +} + +@article{hyvarinen05a, + author = {Aapo Hyv{{\"a}}rinen}, + title = {Estimation of Non-Normalized Statistical Models by Score Matching}, + journal = {Journal of Machine Learning Research}, + year = {2005}, + volume = {6}, + number = {24}, + pages = {695--709}, + url = {http://jmlr.org/papers/v6/hyvarinen05a.html} +} + +@ARTICLE{VincentP2011, + author={Vincent, Pascal}, + journal={Neural Computation}, + title={A Connection Between Score Matching and Denoising Autoencoders}, + year={2011}, + volume={23}, + number={7}, + pages={1661-1674}, + keywords={}, + doi={10.1162/NECO_a_00142}} + +@article{du2019implicit, + title={Implicit generation and modeling with energy based models}, + author={Du, Yilun and Mordatch, Igor}, + journal={Advances in neural information processing systems}, + volume={32}, + year={2019} +} + +@article{du2020improved, + title={Improved contrastive divergence training of energy based models}, + author={Du, Yilun and Li, Shuang and Tenenbaum, Joshua and Mordatch, Igor}, + journal={arXiv preprint arXiv:2012.01316}, + year={2020} +} + +@article{parisiLangevin, +title = {Correlation functions and computer simulations}, +journal = {Nuclear Physics B}, +volume = {180}, +number = {3}, +pages = {378-384}, +year = {1981}, +issn = {0550-3213}, +doi = {https://doi.org/10.1016/0550-3213(81)90056-0}, +url = {https://www.sciencedirect.com/science/article/pii/0550321381900560}, +author = {G. Parisi}, +abstract = {If the equilibrium properties of a statistical system are obtained by solving numerically the associated Langevin equation describing the approach to equilibrium, the connected correlation functions can be computed directly with small effort and high precision.} +} + +@article{song2020denoising, + title={Denoising diffusion implicit models}, + author={Song, Jiaming and Meng, Chenlin and Ermon, Stefano}, + journal={arXiv preprint arXiv:2010.02502}, + year={2020} +} + +@article{chen2020wavegrad, + title={WaveGrad: Estimating gradients for waveform generation}, + author={Chen, Nanxin and Zhang, Yu and Zen, Heiga and Weiss, Ron J and Norouzi, Mohammad and Chan, William}, + journal={arXiv preprint arXiv:2009.00713}, + year={2020} +} + +@article{kong2020diffwave, + title={Diffwave: A versatile diffusion model for audio synthesis}, + author={Kong, Zhifeng and Ping, Wei and Huang, Jiaji and Zhao, Kexin and Catanzaro, Bryan}, + journal={arXiv preprint arXiv:2009.09761}, + year={2020} +} + +@InProceedings{liu2023audioldm, + title = {{A}udio{LDM}: Text-to-Audio Generation with Latent Diffusion Models}, + author = {Liu, Haohe and Chen, Zehua and Yuan, Yi and Mei, Xinhao and Liu, Xubo and Mandic, Danilo and Wang, Wenwu and Plumbley, Mark D}, + booktitle = {Proceedings of the 40th International Conference on Machine Learning}, + pages = {21450--21474}, + year = {2023}, + volume = {202}, +} + +@article{ho2022video, + title={Video diffusion models}, + author={Ho, Jonathan and Salimans, Tim and Gritsenko, Alexey and Chan, William and Norouzi, Mohammad and Fleet, David J}, + journal={arXiv preprint arXiv:2204.03458}, + year={2022} +} + +@article{singer2022make, + title={Make-a-video: Text-to-video generation without text-video data}, + author={Singer, Uriel and Polyak, Adam and Hayes, Thomas and Yin, Xi and An, Jie and Zhang, Songyang and Hu, Qiyuan and Yang, Harry and Ashual, Oron and Gafni, Oran and others}, + journal={arXiv preprint arXiv:2209.14792}, + year={2022} +} + +@article{videoworldsimulators2024, + title={Video generation models as world simulators}, + author={Tim Brooks and Bill Peebles and Connor Holmes and Will DePue and Yufei Guo and Li Jing and David Schnurr and Joe Taylor and Troy Luhman and Eric Luhman and Clarence Ng and Ricky Wang and Aditya Ramesh}, + journal={openai.com}, + year={2024}, + url={https://openai.com/index/video-generation-models-as-world-simulators/} +} + +@inproceedings{blattmann2023videoldm, + title={Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models}, + author={Blattmann, Andreas and Rombach, Robin and Ling, Huan and Dockhorn, Tim and Kim, Seung Wook and Fidler, Sanja and Kreis, Karsten}, + booktitle={IEEE Conference on Computer Vision and Pattern Recognition ({CVPR})}, + year={2023} +} + +@article{pham2025memorization, + title={Memorization to generalization: Emergence of diffusion models from associative memory}, + author={Pham, Bao and Raya, Gabriel and Negri, Matteo and Zaki, Mohammed J and Ambrogioni, Luca and Krotov, Dmitry}, + journal={arXiv preprint arXiv:2505.21777}, + year={2025} +} + +@article{lipman2022flow, + title={Flow matching for generative modeling}, + author={Lipman, Yaron and Chen, Ricky TQ and Ben-Hamu, Heli and Nickel, Maximilian and Le, Matt}, + journal={arXiv preprint arXiv:2210.02747}, + year={2022} +} + +@article{cortes1987hierarchical, + title={Hierarchical associative networks}, + author={Cortes, C and Krogh, A and Hertz, JA}, + journal={Journal of Physics A: Mathematical and General}, + volume={20}, + number={13}, + pages={4449}, + year={1987}, + publisher={IOP Publishing} +} + +@article{gutfreund1988neural, + title={Neural networks with hierarchically correlated patterns}, + author={Gutfreund, Hanoch}, + journal={Physical Review A}, + volume={37}, + number={2}, + pages={570}, + year={1988}, + publisher={APS} +} + +@article{krogh1988mean, + title={Mean-field analysis of hierarchical associative networks with'magnetisation'}, + author={Krogh, A and Hertz, JA}, + journal={Journal of Physics A: Mathematical and General}, + volume={21}, + number={9}, + pages={2211}, + year={1988}, + publisher={IOP Publishing} +} + +@article{kanter1987associative, + title={Associative recall of memory without errors}, + author={Kanter, I and Sompolinsky, Haim}, + journal={Physical Review A}, + volume={35}, + number={1}, + pages={380}, + year={1987}, + publisher={APS} +} + +@article{van1997hebbian, + title={Hebbian learning, its correlation catastrophe, and unlearning}, + author={Van Hemmen, JL}, + journal={Network: Computation in Neural Systems}, + volume={8}, + number={3}, + pages={V1}, + year={1997}, + publisher={IOP Publishing} +} + +@inproceedings{hu2024provably, + title={Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes}, + author={Jerry Yao-Chieh Hu and Dennis Wu and Han Liu}, + booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems}, + year={2024}, + url={https://openreview.net/forum?id=4UReW4Ez6s} +} + +@article{dasgupta2008hardness, + title={The hardness of k-means clustering}, + author={Dasgupta, Sanjoy}, + year={2008}, + journal={UCSD Technical Report}, + url={https://cseweb.ucsd.edu/~dasgupta/papers/kmeans.pdf} +} + +@article{lloyd1982least, + title={Least squares quantization in {PCM}}, + author={Lloyd, Stuart}, + journal={IEEE transactions on information theory}, + volume={28}, + number={2}, + pages={129--137}, + year={1982}, + publisher={IEEE} +} + +@article{dunn1974fuzzy, + title={A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters}, + author={Dunn, J. C. }, + journal={Journal of Cybernetics}, + volume={3}, + pages={32--57}, + year={1974} +} + +@book{bezdek2013pattern, + title={Pattern recognition with fuzzy objective function algorithms}, + author={Bezdek, James C}, + year={2013}, + publisher={Springer Science \& Business Media} +} + +@inproceedings{saha2024deep, + title={Deep Clustering with Associative Memories}, + author={Bishwajit Saha and Dmitry Krotov and Mohammed J Zaki and Parikshit Ram}, + booktitle={NeurIPS Workshop on Machine Learning and Compression}, + year={2024}, + url={https://openreview.net/forum?id=AqglcDyLem} +} + + +@article{mcculloch1943logical, + title={A logical calculus of the ideas immanent in nervous activity}, + author={McCulloch, Warren S and Pitts, Walter}, + journal={The bulletin of mathematical biophysics}, + volume={5}, + pages={115--133}, + year={1943}, + publisher={Springer} +} + +@article{rosenblatt1962principles, + title={Principles of neurodynamics}, + author={Rosenblatt, Frank}, + journal={Perceptrons and the theory of brain mechanisms}, + year={1962}, + publisher={Spartan Press} +} + + +@article{NYTPerceptrons, + author = {The New York Times}, + title = {NEW NAVY DEVICE LEARNS BY DOING; Psychologist Shows Embryo of Computer Designed to Read and Grow Wiser}, + journal = {The New York Times}, + year = {1958}, + url={https://www.nytimes.com/1958/07/08/archives/new-navy-device-learns-by-doing-psychologist-shows-embryo-of.html#} +} + +@article{marvin1969perceptrons, + title={Perceptrons}, + author={Marvin, Minsky and Seymour, A Papert}, + journal={Cambridge, MA: MIT Press}, + volume={6}, + number={318-362}, + pages={7}, + year={1969} +} + +@article{anderson1968memory, + title={A memory storage model utilizing spatial correlation functions}, + author={Anderson, James A}, + journal={Kybernetik}, + volume={5}, + number={3}, + pages={113--119}, + year={1968}, + publisher={Springer} +} + +@article{willshaw1969non, + title={Non-holographic associative memory}, + author={Willshaw, David J and Buneman, O Peter and Longuet-Higgins, Hugh Christopher}, + journal={Nature}, + volume={222}, + number={5197}, + pages={960--962}, + year={1969}, + publisher={Nature Publishing Group UK London} +} + +@article{little1975statistical, + title={A statistical theory of short and long term memory}, + author={Little, WA and Shaw, Gordon L}, + journal={Behavioral biology}, + volume={14}, + number={2}, + pages={115--133}, + year={1975}, + publisher={Elsevier} +} + +@article{amari1972learning, + title={Learning patterns and pattern sequences by self-organizing nets of threshold elements}, + author={Amari, S-I}, + journal={IEEE Transactions on computers}, + volume={100}, + number={11}, + pages={1197--1206}, + year={1972}, + publisher={IEEE} +} + +@article{amari1977neural, + title={Neural theory of association and concept-formation}, + author={Amari, S-I}, + journal={Biological cybernetics}, + volume={26}, + number={3}, + pages={175--185}, + year={1977}, + publisher={Springer} +} + +@article{cohen1983absolute, + title={Absolute stability of global pattern formation and parallel memory storage by competitive neural networks}, + author={Cohen, Michael A and Grossberg, Stephen}, + journal={IEEE transactions on systems, man, and cybernetics}, + number={5}, + pages={815--826}, + year={1983}, + publisher={IEEE} +} + + + + + + + +@article{min2018survey, + title={A survey of clustering with deep learning: From the perspective of network architecture}, + author={Min, Erxue and Guo, Xifeng and Liu, Qiang and Zhang, Gen and Cui, Jianjing and Long, Jun}, + journal={IEEE Access}, + volume={6}, + pages={39501--39514}, + year={2018}, + publisher={IEEE} +} + +@article{zhou2025comprehensive, + author = {Zhou, Sheng and Xu, Hongjia and Zheng, Zhuonan and Chen, Jiawei and Li, Zhao and Bu, Jiajun and Wu, Jia and Wang, Xin and Zhu, Wenwu and Ester, Martin}, + title = {A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions}, + year = {2024}, + issue_date = {March 2025}, + publisher = {Association for Computing Machinery}, + address = {New York, NY, USA}, + volume = {57}, + number = {3}, + issn = {0360-0300}, + url = {https://doi.org/10.1145/3689036}, + doi = {10.1145/3689036}, + journal = {ACM Computing Surveys}, + month = nov, + articleno = {69}, + numpages = {38}, + keywords = {Deep learning, clustering, representation learning} +} + + + +@article{ren2022deep, + title={Deep clustering: A comprehensive survey}, + author={Ren, Yazhou and Pu, Jingyu and Yang, Zhimeng and Xu, Jie and Li, Guofeng and Pu, Xiaorong and Philip, S Yu and He, Lifang}, + journal={IEEE Transactions on Neural Networks and Learning Systems}, + year={2024}, + publisher={IEEE}, + url={https://ieeexplore.ieee.org/abstract/document/10585323} +} + +@inproceedings{curtin2013tree, + title={Tree-independent dual-tree algorithms}, + author={Curtin, Ryan and March, William and Ram, Parikshit and Anderson, David and Gray, Alexander and Isbell, Charles}, + booktitle={International Conference on Machine Learning}, + pages={1435--1443}, + year={2013}, + organization={PMLR}, + url={https://proceedings.mlr.press/v28/curtin13.pdf} +} + +@article{curtin2015plug, + title={Plug-and-play dual-tree algorithm runtime analysis.}, + author={Curtin, Ryan R and Lee, Dongryeol and March, William B and Ram, Parikshit}, + journal={J. Mach. Learn. Res.}, + volume={16}, + pages={3269--3297}, + year={2015}, + url={https://www.jmlr.org/papers/volume16/curtin15a/curtin15a.pdf} +} + +@article{ram2009linear, + title={Linear-time algorithms for pairwise statistical problems}, + author={Ram, Parikshit and Lee, Dongryeol and March, William and Gray, Alexander}, + journal={Advances in Neural Information Processing Systems}, + volume={22}, + year={2009}, + url={https://proceedings.neurips.cc/paper_files/paper/2009/file/2421fcb1263b9530df88f7f002e78ea5-Paper.pdf} +} + +@article{rahimi2008weighted, + title={Weighted sums of random kitchen sinks: Replacing minimization with randomization in learning}, + author={Rahimi, Ali and Recht, Benjamin}, + journal={Advances in neural information processing systems}, + volume={21}, + year={2008} +} + +@article{yu2016orthogonal, + title={Orthogonal random features}, + author={Yu, Felix Xinnan X and Suresh, Ananda Theertha and Choromanski, Krzysztof M and Holtmann-Rice, Daniel N and Kumar, Sanjiv}, + journal={Advances in neural information processing systems}, + volume={29}, + year={2016} +} + +@article{liu2021random, + title={Random features for kernel approximation: A survey on algorithms, theory, and beyond}, + author={Liu, Fanghui and Huang, Xiaolin and Chen, Yudong and Suykens, Johan AK}, + journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, + volume={44}, + number={10}, + pages={7128--7148}, + year={2021}, + publisher={IEEE} +} + +@inproceedings{hoover2024dense, + title={Dense associative memory through the lens of random features}, + author={Hoover, Benjamin and Chau, Duen Horng and Strobelt, Hendrik and Ram, Parikshit and Krotov, Dmitry}, + booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems}, + year={2024}, + url={https://proceedings.neurips.cc/paper_files/paper/2024/file/29ff36c8fbed10819b2e50267862a52a-Paper-Conference.pdf} +} + +@inproceedings{hoover2025dense, + title={Dense Associative Memory with Epanechnikov energy}, + author={Benjamin Hoover and Krishna Balasubramanian and Dmitry Krotov and Parikshit Ram}, + booktitle={New Frontiers in Associative Memories}, + year={2025}, + url={https://openreview.net/forum?id=LOAkHpRSlZ} +} + +@book{wand1994kernel, + title={Kernel smoothing}, + author={Wand, Matt P and Jones, M Chris}, + year={1994}, + publisher={CRC press} +} + +@article{muller1984smooth, + title={Smooth optimum kernel estimators of densities, regression curves and modes}, + author={M{\"u}ller, Hans-Georg}, + journal={The Annals of Statistics}, + pages={766--774}, + year={1984}, + publisher={JSTOR} +} + +@article{epanechnikov1969non, + title={Non-parametric estimation of a multivariate probability density}, + author={Epanechnikov, Vassiliy A}, + journal={Theory of Probability \& Its Applications}, + volume={14}, + number={1}, + pages={153--158}, + year={1969}, + publisher={SIAM} +} + + +@book{gradshteyn2014table, + title={Table of integrals, series, and products}, + author={Gradshteyn, Izrail Solomonovich and Ryzhik, Iosif Moiseevich}, + year={2014}, + publisher={Academic press} +} + + +@inproceedings{burg2021on, + title={On Memorization in Probabilistic Deep Generative Models}, + author={Gerrit J.J. Van den Burg and Chris Williams}, + booktitle={Advances in Neural Information Processing Systems}, + editor={A. Beygelzimer and Y. Dauphin and P. Liang and J. Wortman Vaughan}, + year={2021}, + url={https://openreview.net/forum?id=PlGSgjFK2oJ} +} + +@article{gu2023memorization, + title={On memorization in diffusion models}, + author={Gu, Xiangming and Du, Chao and Pang, Tianyu and Li, Chongxuan and Lin, Min and Wang, Ye}, + journal={arXiv preprint arXiv:2310.02664}, + year={2023} +} + +@inproceedings{yoon2023diffusion, +title={Diffusion probabilistic models generalize when they fail to memorize}, + author={Yoon, TaeHo and Choi, Joo Young and Kwon, Sehyun and Ryu, Ernest K}, + booktitle={ICML 2023 Workshop on Structured Probabilistic Inference Generative Modeling}, + year={2023} +} + + +@article{somepalli2023understanding, + title={Understanding and mitigating copying in diffusion models}, + author={Somepalli, Gowthami and Singla, Vasu and Goldblum, Micah and Geiping, Jonas and Goldstein, Tom}, + journal={Advances in Neural Information Processing Systems}, + volume={36}, + pages={47783--47803}, + year={2023} +} + +@inproceedings{somepalli2023diffusion, + title={Diffusion art or digital forgery? investigating data replication in diffusion models}, + author={Somepalli, Gowthami and Singla, Vasu and Goldblum, Micah and Geiping, Jonas and Goldstein, Tom}, + booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, + pages={6048--6058}, + year={2023} +} + +@inproceedings{meehan2020non, + title={A non-parametric test to detect data-copying in generative models}, + author={Meehan, Casey and Chaudhuri, Kamalika and Dasgupta, Sanjoy}, + booktitle={International Conference on Artificial Intelligence and Statistics}, + year={2020} +} + +@inproceedings{Carlini2023, author = {Carlini, Nicholas and Hayes, Jamie and Nasr, Milad and Jagielski, Matthew and Sehwag, Vikash and Tram\`{e}r, Florian and Balle, Borja and Ippolito, Daphne and Wallace, Eric}, +title = {Extracting training data from diffusion models}, +year = {2023}, isbn = {978-1-939133-37-3}, publisher = {USENIX Association}, address = {USA}, +booktitle = {Proceedings of the 32nd USENIX Conference on Security Symposium}, articleno = {294}, numpages = {18}, location = {Anaheim, CA, USA}, series = {SEC '23} } + +@article{biroli2024dynamical, + title={Dynamical regimes of diffusion models}, + volume={15}, + ISSN={2041-1723}, + url={http://dx.doi.org/10.1038/s41467-024-54281-3}, + DOI={10.1038/s41467-024-54281-3}, + number={1}, + journal={Nature Communications}, + publisher={Springer Science and Business Media LLC}, + author={Biroli, Giulio and Bonnaire, Tony and de Bortoli, Valentin and Mézard, Marc}, + year={2024}, + month=nov +} + +@article{achilli2024losing, + title={Losing dimensions: Geometric memorization in generative diffusion}, + author={Achilli, Beatrice and Ventura, Enrico and Silvestri, Gianluigi and Pham, Bao and Raya, Gabriel and Krotov, Dmitry and Lucibello, Carlo and Ambrogioni, Luca}, + journal={arXiv preprint arXiv:2410.08727}, + year={2024} } + +@article{demicirgil2017model, + title={On a Model of Associative Memory with Huge Storage Capacity}, + volume={168}, + ISSN={1572-9613}, + url={http://dx.doi.org/10.1007/s10955-017-1806-y}, + DOI={10.1007/s10955-017-1806-y}, + number={2}, + journal={Journal of Statistical Physics}, + publisher={Springer Science and Business Media LLC}, + author={Demircigil, Mete and Heusel, Judith and Löwe, Matthias and Upgang, Sven and Vermet, Franck}, + year={2017}, + month=may, pages={288–299} } + +@article{dosovitskiy2020vit, + author = {Alexey Dosovitskiy and + Lucas Beyer and + Alexander Kolesnikov and + Dirk Weissenborn and + Xiaohua Zhai and + Thomas Unterthiner and + Mostafa Dehghani and + Matthias Minderer and + Georg Heigold and + Sylvain Gelly and + Jakob Uszkoreit and + Neil Houlsby}, + title = {An Image is Worth 16x16 Words: Transformers for Image Recognition + at Scale}, + journal = {CoRR}, + volume = {abs/2010.11929}, + year = {2020}, + url = {https://arxiv.org/abs/2010.11929}, + eprinttype = {arXiv}, + eprint = {2010.11929}, + timestamp = {Fri, 20 Nov 2020 14:04:05 +0100}, + biburl = {https://dblp.org/rec/journals/corr/abs-2010-11929.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org} +} \ No newline at end of file diff --git a/nbs/sidebar.yml b/nbs/sidebar.yml index cf640ef..8b437dc 100644 --- a/nbs/sidebar.yml +++ b/nbs/sidebar.yml @@ -2,8 +2,5 @@ website: sidebar: contents: - index.ipynb - - 00_lagrangians.ipynb - - 01_layers.ipynb - - 02_synapses.ipynb - - 03_ham.ipynb - - 04_registry.ipynb \ No newline at end of file + - 00_core.ipynb + - 01_lagrangians.ipynb diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..bc76484 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,38 @@ +[project] +name="hamux" +version = "0.2.1" +description = "Add your description here" +readme = "README.md" +authors = [ + { name = "Ben Hoover", email = "24350185+bhoov@users.noreply.github.com" } +] +requires-python=">=3.10" +dependencies = [ + "equinox>=0.12.2", + "jax>=0.6.1", +] + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[dependency-groups] +dev = [ + "datasets>=4.0.0", + "einops>=0.8.1", + "hamux", + "ipykernel>=6.29.5", + "jupytext>=1.17.1", + "matplotlib>=3.10.3", + "nbclient>=0.10.2", + "nbdev", + "nbformat>=5.10.4", + "optax>=0.2.5", + "seaborn>=0.13.2", + "setuptools<81", + "tomli>=2.2.1", +] + +[tool.uv.sources] +hamux = { workspace = true } +nbdev = { git = "https://github.com/bhoov/nbdev.git", rev = "qmd_support" } diff --git a/requirements-dev.txt b/requirements-dev.txt deleted file mode 100644 index 2937ce3..0000000 --- a/requirements-dev.txt +++ /dev/null @@ -1,5 +0,0 @@ -tfds-nightly -tensorflow -timm -twine -tensorflowjs \ No newline at end of file diff --git a/scripts/build.sh b/scripts/build.sh new file mode 100644 index 0000000..42797d1 --- /dev/null +++ b/scripts/build.sh @@ -0,0 +1,21 @@ +#!/bin/bash + +# Modified build script for nbdev project +set -e # Exit on any error + +echo "🔄 Syncing dependencies..." +uv run python scripts/sync_dependencies.py + +echo "🤔 nbdev_prepare..." +uv run nbdev_prepare + +echo "📄 Copying README from _proc to root directory..." +if [ -f "_proc/README.md" ]; then + cp _proc/README.md README.md + echo "✅ README.md successfully updated!" +else + echo "❌ Warning: _proc/README.md not found. README may not have been generated." + exit 1 +fi + +echo "�� Build complete!" \ No newline at end of file diff --git a/scripts/prep_pypi.py b/scripts/prep_pypi.py new file mode 100644 index 0000000..f4efd0a --- /dev/null +++ b/scripts/prep_pypi.py @@ -0,0 +1,35 @@ +#!/usr/bin/env python3 +"""Bump version and sync from settings.ini to pyproject.toml for PyPI release""" + +import subprocess +import sys +import re +import configparser +from pathlib import Path +from fastcore.script import * + +ROOT = Path(__file__).parent.parent +version_part = sys.argv[1] if len(sys.argv) > 1 else '2' + +@call_parse +def main( + version_part:int=2, # 0: major, 1: minor, 2: patch +): + print("Syncing dependencies from pyproject.toml to settings.ini...") + subprocess.run([sys.executable, ROOT / 'scripts' / 'sync_dependencies.py'], check=True) + + # Bump version + print("Bumping version...") + subprocess.run(['uv', 'run', 'nbdev_bump_version', '--part', str(version_part)], check=True) + + # Read version from settings.ini + config = configparser.ConfigParser() + config.read(ROOT / 'settings.ini') + version = config['DEFAULT']['version'] + + # Update pyproject.toml + content = open(ROOT / 'pyproject.toml', 'r').read() + content = re.sub(r'^version\s*=\s*["\'].*["\']', f'version = "{version}"', content, flags=re.MULTILINE) + open(ROOT / 'pyproject.toml', 'w').write(content) + + print(f"Complete. Now run `nbdev_pypi` to push package") diff --git a/scripts/sync_dependencies.py b/scripts/sync_dependencies.py new file mode 100644 index 0000000..df5d45f --- /dev/null +++ b/scripts/sync_dependencies.py @@ -0,0 +1,39 @@ +#%% +"""Sync dependencies from pyproject.toml to settings.ini""" + +import tomli as tomllib +import re +from pathlib import Path +import shutil + +ROOT = Path(__file__).parent.parent +pyproject_f = ROOT / 'pyproject.toml' +settings_f = ROOT / 'settings.ini' + +data = tomllib.load(open(pyproject_f, 'rb')) + +# Extract shared fields +main_deps = ' '.join(data.get('project', {}).get('dependencies', [])) +dev_deps = ' '.join(data.get('dependency-groups', {}).get('dev', [])) +python_version = data.get('project', {}).get('requires-python', '').lstrip('>=').strip('"') + +# Create backup of settings.ini +backup_path = settings_f.with_suffix('.ini.backup') +shutil.copy2(settings_f, backup_path) + +ini_content = open(settings_f, 'r').read() +lines = ini_content.split('\n') + +# Replace existing lines or add if missing +for pattern, replacement in [ + (r'^\s*#?\s*requirements\s*=.*$', f'requirements = {main_deps}'), + (r'^\s*#?\s*dev_requirements\s*=.*$', f'dev_requirements = {dev_deps}'), + (r'^\s*min_python\s*=.*$', f'min_python = {python_version}') + +]: + if re.search(pattern, ini_content, re.MULTILINE): + ini_content = re.sub(pattern, replacement, ini_content, flags=re.MULTILINE) + else: + ini_content += f'\n{replacement}' + +open(settings_f, 'w').write(ini_content) diff --git a/settings.ini b/settings.ini index 9c9890b..3630d29 100644 --- a/settings.ini +++ b/settings.ini @@ -1,36 +1,40 @@ [DEFAULT] repo = hamux lib_name = hamux -version = 0.1.1 -min_python = 3.7 +version = 0.2.1 +min_python = 3.10 license = apache2 +black_formatting = False doc_path = _docs lib_path = hamux nbs_path = nbs recursive = True tst_flags = notest put_version_in_init = True +update_pyproject = True branch = main custom_sidebar = False doc_host = https://bhoov.github.io doc_baseurl = /hamux git_url = https://github.com/bhoov/hamux -title = hamux +title = HAMUX +readme_nb = index.qmd audience = Developers author = Benjamin Hoover -author_email = benjamin.hoover@ibm.com -copyright = 2022 onwards, Benjamin Hoover -description = A Deep Learning framework built around ENERGY -keywords = nbdev jupyter notebook python hopfield ai hypergraph neurons synapses associative memory hierarchical framework jax treex energy autograd lagrangian +author_email = benhoover34@gmail.com +copyright = 2025 onwards, Benjamin Hoover +description = Energy formulation for deep learning +keywords = nbdev jupyter notebook python language = English status = 3 user = bhoov -requirements = fastcore flax treex loguru jax jaxlib hypernetx tensorflowjs -black_formatting = False -readme_nb = index.ipynb +requirements = equinox>=0.12.2 jax>=0.6.1 +dev_requirements = datasets>=4.0.0 einops>=0.8.1 hamux ipykernel>=6.29.5 jupytext>=1.17.1 matplotlib>=3.10.3 nbclient>=0.10.2 nbdev nbformat>=5.10.4 optax>=0.2.5 seaborn>=0.13.2 setuptools<81 tomli>=2.2.1 allowed_metadata_keys = allowed_cell_metadata_keys = -jupyter_hooks = True +jupyter_hooks = False clean_ids = True clear_all = False +cell_number = True +skip_procs = diff --git a/setup.py b/setup.py index 5cf5922..21b001e 100644 --- a/setup.py +++ b/setup.py @@ -1,11 +1,11 @@ from pkg_resources import parse_version from configparser import ConfigParser -import setuptools +import setuptools, shlex assert parse_version(setuptools.__version__)>=parse_version('36.2') # note: all settings are in settings.ini; edit there, not here config = ConfigParser(delimiters=['=']) -config.read('settings.ini') +config.read('settings.ini', encoding='utf-8') cfg = config['DEFAULT'] cfg_keys = 'version description keywords author author_email'.split() @@ -22,14 +22,21 @@ } statuses = [ '1 - Planning', '2 - Pre-Alpha', '3 - Alpha', '4 - Beta', '5 - Production/Stable', '6 - Mature', '7 - Inactive' ] -py_versions = '3.6 3.7 3.8 3.9 3.10'.split() +py_versions = '3.6 3.7 3.8 3.9 3.10 3.11 3.12'.split() -requirements = cfg.get('requirements','').split() -if cfg.get('pip_requirements'): requirements += cfg.get('pip_requirements','').split() +requirements = shlex.split(cfg.get('requirements', '')) +if cfg.get('pip_requirements'): requirements += shlex.split(cfg.get('pip_requirements', '')) min_python = cfg['min_python'] lic = licenses.get(cfg['license'].lower(), (cfg['license'], None)) dev_requirements = (cfg.get('dev_requirements') or '').split() +package_data = dict() +pkg_data = cfg.get('package_data', None) +if pkg_data: + package_data[cfg['lib_name']] = pkg_data.split() # split as multiple files might be listed +# Add package data to setup_cfg for setuptools.setup(..., **setup_cfg) +setup_cfg['package_data'] = package_data + setuptools.setup( name = cfg['lib_name'], license = lic[0], @@ -45,7 +52,7 @@ extras_require={ 'dev': dev_requirements }, dependency_links = cfg.get('dep_links','').split(), python_requires = 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gitignore --- .gitignore | 10 +- nbs/_examples/README.md | 1 + nbs/_examples/_demo.qmd | 221 ++++++++++++++++++++++++++++++++++++++++ 3 files changed, 226 insertions(+), 6 deletions(-) create mode 100644 nbs/_examples/README.md create mode 100644 nbs/_examples/_demo.qmd diff --git a/.gitignore b/.gitignore index f35ba49..23d1e59 100644 --- a/.gitignore +++ b/.gitignore @@ -1,10 +1,9 @@ _modidx.py _logs _dummylogs -examples/data +nbs/_examples/data _docs/ _proc/ -_*/ *.bak .gitattributes .last_checked @@ -21,6 +20,8 @@ code_example_snippets.py model.json *.bin flaxrepo +OLD/ +*.ini.backup # Byte-compiled / optimized / DLL files __pycache__/ @@ -156,7 +157,4 @@ checklink/cookies.txt .pkg # Quarto -.quarto -OLD/ - -*.ini.backup \ No newline at end of file +.quarto \ No newline at end of file diff --git a/nbs/_examples/README.md b/nbs/_examples/README.md new file mode 100644 index 0000000..f26dceb --- /dev/null +++ b/nbs/_examples/README.md @@ -0,0 +1 @@ +**HAMUX's API has changed since v0.1.0. We are working to recreate examples** \ No newline at end of file diff --git a/nbs/_examples/_demo.qmd b/nbs/_examples/_demo.qmd new file mode 100644 index 0000000..c6153e5 --- /dev/null +++ b/nbs/_examples/_demo.qmd @@ -0,0 +1,221 @@ +# MNIST demo + +Uncomment the following cell to install necessary dependencies for the demo + +```{python} +## If you setup the env using `uv sync`, uncommenting the following is not necessary: +#!pip install seaborn optax datasets einops +``` + +```{python} +#| code-fold: true +#| code-summary: Import dependencies +from typing import * +import jax +import jax.numpy as jnp +import jax.tree_util as jtu +import jax.random as jr +import equinox as eqx +import hamux as hmx + +import datasets +from einops import rearrange +import matplotlib as mpl +import matplotlib.pyplot as plt +import numpy as np +from pathlib import Path +from tqdm.auto import tqdm +import optax +``` + +```{python} +#| hide +import os +import jax +import os + +# Auto-configure CUDA if available +gpu_available = any(d.device_kind == 'gpu' for d in jax.devices()) +if gpu_available: + os.environ["CUDA_VISIBLE_DEVICES"] = "0" + os.environ["XLA_PYTHON_CLIENT_MEM_FRACTION"] = "0.5" + print("✅ Using CUDA") +else: + print("⚠️ CUDA recommended for better performance") +``` + + +```{python} +def get_mnist_train_test(): + # Save to `data/` + data_path = Path("data/") + data_path.mkdir(parents=True, exist_ok=True) + Xtrain_path, Xtest_path = data_path / "Xtrain_mnist.npy", data_path / "Xtest_mnist.npy" + if not Xtrain_path.exists() or not Xtest_path.exists(): + print("Downloading MNIST data...") + mnist = datasets.load_dataset("mnist").with_format("numpy") + train_set = mnist['train'] + test_set = mnist['test'] + + print("Saving Xtrain...") + Xtrain = next(train_set.iter(len(train_set)))['image'] + np.save(Xtrain_path, Xtrain) + print("Saving Xtest...") + Xtest = next(test_set.iter(len(test_set)))['image'] + np.save(Xtest_path, Xtest) + print("Done") + + Xtrain, Xtest = np.load(Xtrain_path), np.load(Xtest_path) + return Xtrain, Xtest +``` + +```{python} +def transform(x): + x = x / 255. + x = rearrange(x, "... h w -> ... (h w)") + x = x / jnp.sqrt((x ** 2).sum(-1, keepdims=True)) + return x + +Xtrain, Xtest = get_mnist_train_test() +Xtest = transform(Xtest) +Xtrain = transform(Xtrain) +``` + + +```{python} +#| hide +# set the colormap and centre the colorbar +class MidpointNormalize(mpl.colors.Normalize): + """Normalise the colorbar.""" + def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False): + self.midpoint = midpoint + mpl.colors.Normalize.__init__(self, vmin, vmax, clip) + + def __call__(self, value, clip=None): + x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1] + return np.ma.masked_array(np.interp(value, x, y), np.isnan(value)) + +cnorm=MidpointNormalize(midpoint=0.) + +def show_img(img): + vmin, vmax = img.min(), img.max() + vscale = max(np.abs(vmin), np.abs(vmax)) + cnorm = MidpointNormalize(midpoint=0., vmin=-vscale, vmax=vscale) + + fig, ax = plt.subplots(1,1) + pcm = ax.imshow(img, cmap="seismic", norm=cnorm) + ax.axis("off") + + fig.subplots_adjust(right=0.8) + cbar_ax = fig.add_axes([0.83, 0.15, 0.03, 0.7]) + fig.colorbar(pcm, cax=cbar_ax); + return fig +``` + + +```{python} +class DenseSynapseHid(eqx.Module): + """This synapse captures the 'Dense Associative Memory' energy""" + W: jax.Array + beta: float = 1. + + @property + def nW(self): + "Normalize the weights" + nc = jnp.sqrt(jnp.sum(self.W ** 2, axis=0, keepdims=True)) + return self.W / nc + + def __call__(self, xhat1): + """Compute the energy of the synapse""" + x2 = xhat1 @ self.nW + return - 1/self.beta * jax.nn.logsumexp(self.beta * x2, axis=-1) + + @classmethod + def rand_init(cls, key, d1:int, d2:int): + Winit = 0.02 * jr.normal(key, (d1, d2)) + return cls(W=Winit) + +key = jax.random.PRNGKey(0) +neurons = { + "input": hmx.NeuronLayer(hmx.lagr_spherical_norm, (784,)), +} +synapses = { + "s1": DenseSynapseHid.rand_init(key, 784, 900), +} +connections = [ + (["input"], "s1") +] + +ham = hmx.HAM(neurons, synapses, connections) +xs = ham.init_states() +xhats = ham.activations(xs) +opt = optax.adam(4e-2) +``` + + +```{python} +n_epochs = 10 +pbar = tqdm(range(n_epochs), total=n_epochs) +img = Xtrain[:] +batch_size = 100 + +ham = ham.vectorize() +opt_state = opt.init(eqx.filter(ham, eqx.is_array)) + +def lossf(ham, xs,key, nsteps=1, alpha=1.): + """Given a noisy initial image, descend the energy and try to reconstruct the original image at the end of the dynamics. + + Works best with fewer steps due to vanishing gradient problems""" + img = xs['input'] + xs['input'] = img + jr.normal(key, img.shape) * 0.3 + + for i in range(nsteps): + # Construct noisy image to final prediction + xhats = ham.activations(xs) + evalue, egrad = ham.dEdact(xhats, xs, return_energy=True) + xs = jtu.tree_map(lambda x, dEdact: x - alpha * dEdact, xs, egrad) + + xhats = ham.activations(xs) + img_final = xhats['input'] + loss = ((img_final - img)**2).mean() + + logs = { + "loss": loss, + } + + return loss, logs + +@eqx.filter_jit +def step(img, ham, opt_state, key): + xs = ham.init_states(bs=img.shape[0]) + xs["input"] = img + + (loss, logs), grads = eqx.filter_value_and_grad(lossf, has_aux=True)(ham, xs, key) + updates, opt_state = opt.update(grads, opt_state, ham) + newparams = optax.apply_updates(eqx.filter(ham, eqx.is_array), updates) + ham = eqx.combine(newparams, ham) + return ham, opt_state, logs + +noise_rng = jr.PRNGKey(100) +batch_rng = jr.PRNGKey(10) +for e in pbar: + batch_key, batch_rng = jr.split(batch_rng) + idxs = jr.permutation(batch_key, jnp.arange(img.shape[0])) + i = 0 + + while i < img.shape[0]: + noise_key, noise_rng = jr.split(noise_rng) + batch = img[idxs[i: i+batch_size]] + ham, opt_state, logs = step(batch, ham, opt_state, noise_key) + i = i+batch_size + + pbar.set_description(f'[{i}]: epoch = {e+1:03d}/{n_epochs:03d}, loss = {logs["loss"].item():2.6f}') +``` + +The above architecture trains ok. We can inspect the weights to see the attractors the model has learned. + +```{python} +myW = ham.hypersynapses["s1"].nW +kh = kw = int(np.sqrt(myW.shape[-1])) +show_img(rearrange(myW, "(h w) (kh kw) -> (kh h) (kw w)", h=28, w=28, kh=kh, kw=kw)); +``` \ No newline at end of file

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