From e10b8dcec3794fa558c03aa671198bf959bd4b73 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 16 Feb 2025 17:00:23 -0700 Subject: [PATCH 001/146] Add ratchet-web-train --- Cargo.toml | 2 +- crates/ratchet-web-train/Cargo.toml | 66 +++ crates/ratchet-web-train/README.md | 2 + crates/ratchet-web-train/src/lib.rs | 2 + crates/ratchet-web-train/src/model.rs | 686 ++++++++++++++++++++++++++ 5 files changed, 757 insertions(+), 1 deletion(-) create mode 100644 crates/ratchet-web-train/Cargo.toml create mode 100644 crates/ratchet-web-train/README.md create mode 100644 crates/ratchet-web-train/src/lib.rs create mode 100644 crates/ratchet-web-train/src/model.rs diff --git a/Cargo.toml b/Cargo.toml index eae21a07..78d672bc 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -2,7 +2,7 @@ members = [ "crates/ratchet-hub", "crates/ratchet-core", - "crates/ratchet-web", + "crates/ratchet-web-train", "crates/ratchet-loader", "crates/ratchet-models", "crates/ratchet-nn", diff --git a/crates/ratchet-web-train/Cargo.toml b/crates/ratchet-web-train/Cargo.toml new file mode 100644 index 00000000..98443f89 --- /dev/null +++ b/crates/ratchet-web-train/Cargo.toml @@ -0,0 +1,66 @@ +[package] +name = "ratchet-web-train" +version = "0.0.0" +edition = "2021" +license = "MIT" +repository = "https://github.com/vinhowe/ratchet-backward" + +[features] +debug = ["ratchet-nn/debug"] + +[lib] +crate-type = ["cdylib", "rlib"] + +[package.metadata.docs.rs] +default-target = "wasm32-unknown-unknown" + +[package.metadata.wasm-pack.profile.dev.wasm-bindgen] +debug-js-glue = true +demangle-name-section = true +dwarf-debug-info = true + +[package.metadata.wasm-pack.profile.release] +wasm-opt = [ + '-O4', + '--enable-simd', + '--flexible-inline-max-function-size', + '4294967295', +] + +# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html +[dependencies] +ratchet-models = { path = "../ratchet-models" } +ratchet-nn = { path = "../ratchet-nn" } +ratchet-datasets = { path = "../ratchet-datasets" } +ratchet = { path = "../ratchet-core" } +wasm-bindgen = { workspace = true } +wasm-bindgen-futures = { workspace = true } +js-sys = { workspace = true } +thiserror.workspace = true +anyhow.workspace = true +serde = { workspace = true } +serde_json = { workspace = true } +serde-wasm-bindgen = { workspace = true } +console_error_panic_hook = { workspace = true } +console_log = { workspace = true, features = ["color"] } +log.workspace = true +chrono = { workspace = true } +fern = { workspace = true } +tokenizers = { version = "0.19.1", default-features = false, features = [ + "unstable_wasm", +] } +futures = "0.3.30" +async-trait = { workspace = true } +[dependencies.web-sys] +features = [ + 'console', + 'Window', + 'Navigator', +] +workspace = true + + +[dev-dependencies] +wasm-bindgen-test.workspace = true +serde_json = { workspace = true } +ndarray = { workspace = true } diff --git a/crates/ratchet-web-train/README.md b/crates/ratchet-web-train/README.md new file mode 100644 index 00000000..8792012a --- /dev/null +++ b/crates/ratchet-web-train/README.md @@ -0,0 +1,2 @@ +# ratchet-web-train + diff --git a/crates/ratchet-web-train/src/lib.rs b/crates/ratchet-web-train/src/lib.rs new file mode 100644 index 00000000..8c866e04 --- /dev/null +++ b/crates/ratchet-web-train/src/lib.rs @@ -0,0 +1,2 @@ +#![cfg(target_arch = "wasm32")] +mod model; diff --git a/crates/ratchet-web-train/src/model.rs b/crates/ratchet-web-train/src/model.rs new file mode 100644 index 00000000..8b6a43be --- /dev/null +++ b/crates/ratchet-web-train/src/model.rs @@ -0,0 +1,686 @@ +use anyhow::Result; +use async_trait::async_trait; +use ratchet::{DType, Device, DeviceRequest, GradStore, Tensor, Var}; +use ratchet_datasets::batcher::IterResult2; +use ratchet_datasets::{ + nlp::{ + tinystories::{ + Dataset as TinyStoriesDataset, DatasetRandomIter as TinyStoriesDatasetRandomIter, + }, + toy::{ + AddTask, CountTask, ModAddTask, SlapjackTask, SortTask, ToyTaskIter, TwoSumTask, + ZerosTask, + }, + }, + Batcher, +}; +use ratchet_models::gpt2::{Config, GPT2Input, PositionalEncoding}; +use ratchet_models::gpt2::{LayerNormPosition, GPT2}; +use ratchet_nn::{ + clip_grad_norm, cross_entropy, Activation, AdamW, ConstantLR, CosineAnnealingLR, LRScheduler, + LRSchedulerCore, LinearLR, Module, Optimizer, ParamsAdamW, VarBuilder, VarMap, SGD, +}; +use serde::{Deserialize, Serialize}; +use std::iter::Iterator; +use wasm_bindgen::prelude::*; + +#[wasm_bindgen(start)] +pub fn start() { + console_error_panic_hook::set_once(); + let logger = fern::Dispatch::new() + .format(|out, message, record| { + out.finish(format_args!( + "{}[{}][{}] {}", + chrono::Local::now().format("[%Y-%m-%d][%H:%M:%S]"), + record.target(), + record.level(), + message + )) + }) + .level_for("tokenizers", log::LevelFilter::Off) + .level(log::LevelFilter::Info) + .chain(fern::Output::call(console_log::log)) + .apply(); + match logger { + Ok(_) => log::info!("Logging initialized."), + Err(error) => eprintln!("Error initializing logging: {:?}", error), + } +} + +#[derive(Serialize, Deserialize)] +pub struct OptimizerConfig { + pub optimizer_type: String, // "adamw" or "sgd" + pub lr: f64, + #[serde(default = "default_beta1")] + pub beta1: f64, + #[serde(default = "default_beta2")] + pub beta2: f64, + #[serde(default = "default_eps")] + pub eps: f64, + #[serde(default = "default_weight_decay")] + pub weight_decay: f64, + #[serde(default = "default_momentum")] + pub momentum: f64, // For SGD + #[serde(default = "default_scheduler_type")] + pub scheduler_type: String, // "none", "constant", "linear", "cosine" + #[serde(default = "default_scheduler_factor")] + pub scheduler_factor: f64, // For constant/linear scheduler + #[serde(default = "default_scheduler_steps")] + pub scheduler_steps: usize, // For all schedulers + #[serde(default = "default_scheduler_eta_min")] + pub scheduler_eta_min: f64, // For cosine scheduler +} + +fn default_beta1() -> f64 { + 0.9 +} +fn default_beta2() -> f64 { + 0.999 +} +fn default_eps() -> f64 { + 1e-8 +} +fn default_weight_decay() -> f64 { + 0.0 +} +fn default_momentum() -> f64 { + 0.0 +} +fn default_scheduler_type() -> String { + "none".to_string() +} +fn default_scheduler_factor() -> f64 { + 1.0 +} +fn default_scheduler_steps() -> usize { + 1000 +} +fn default_scheduler_eta_min() -> f64 { + 0.0 +} + +// ------------------------------------------------------------------- +// Trainer configuration that is deserializable from JavaScript. +// Note the additional fields for batch size and dataset selection. +// ------------------------------------------------------------------- +#[derive(Serialize, Deserialize)] +pub struct TrainerConfig { + pub vocab_size: usize, + pub n_embd: usize, + pub n_layer: usize, + pub n_head: usize, + pub block_size: usize, + pub batch_size: usize, + /// A string specifying which dataset to use: "two_sum" (default), "zeros", or "tinystories". + pub dataset: String, + #[serde(default = "default_optimizer_config")] + pub optimizer: OptimizerConfig, + #[serde(default = "default_activation")] + pub activation: String, + #[serde(default = "default_attention_only")] + pub attention_only: bool, + #[serde(default = "default_positional_encoding")] + pub positional_encoding: String, + #[serde(default = "default_layernorm_position")] + pub layernorm_position: String, + #[serde(default = "default_seed")] + pub seed: Option, +} + +fn default_optimizer_config() -> OptimizerConfig { + OptimizerConfig { + optimizer_type: "adamw".to_string(), + lr: 1e-3, + beta1: default_beta1(), + beta2: default_beta2(), + eps: default_eps(), + weight_decay: default_weight_decay(), + momentum: default_momentum(), + scheduler_type: default_scheduler_type(), + scheduler_factor: default_scheduler_factor(), + scheduler_steps: default_scheduler_steps(), + scheduler_eta_min: default_scheduler_eta_min(), + } +} + +fn default_activation() -> String { + "gelu".to_string() +} + +fn default_attention_only() -> bool { + false +} + +fn default_positional_encoding() -> String { + "learned".to_string() +} + +fn default_layernorm_position() -> String { + "pre".to_string() +} + +fn default_seed() -> Option { + None +} + +fn string_to_activation(s: &str) -> Activation { + match s.to_lowercase().as_str() { + "gelu" => Activation::Gelu, + "relu" => Activation::Relu, + "relu2" => Activation::Relu2, + "silu" => Activation::Silu, + "sigmoid" => Activation::Sigmoid, + "swiglu" => Activation::Swiglu, + _ => Activation::Relu2, // Default to Relu2 for unrecognized values + } +} + +// ------------------------------------------------------------------- +// Batch and BatchHandle definitions. +// The inner Batch holds the (input, target) tensors on the current device. +// ------------------------------------------------------------------- +pub struct Batch { + pub input: Tensor, + pub target: Tensor, +} + +#[wasm_bindgen(js_name = "Batch")] +pub struct BatchHandle { + inner: Batch, +} + +#[wasm_bindgen] +impl BatchHandle { + /// Asynchronously converts the underlying batch data into a JS object. + /// This operation transfers the tensors to the CPU and then converts them into Vec. + #[wasm_bindgen] + pub async fn to_js(&self) -> Result { + // Transfer the input and target tensors to CPU. + let input_cpu = self + .inner + .input + .to(&Device::CPU) + .await + .map_err(|e| e.to_string())?; + let target_cpu = self + .inner + .target + .to(&Device::CPU) + .await + .map_err(|e| e.to_string())?; + // Convert the tensors to Vec. + let input_vec = input_cpu.to_vec::().map_err(|e| e.to_string())?; + let target_vec = target_cpu.to_vec::().map_err(|e| e.to_string())?; + // Create a JS-friendly object. + let batch_obj = serde_json::json!({ + "input": input_vec, + "target": target_vec, + }); + serde_wasm_bindgen::to_value(&batch_obj).map_err(|e| e.to_string().into()) + } +} + +// Updated to: + +enum BatcherType<'a> { + ToyTwoSum( + Batcher< + IterResult2< + ratchet_datasets::nlp::toy::ToyTaskIter, + >, + >, + ), + ToyZeros( + Batcher< + IterResult2< + ratchet_datasets::nlp::toy::ToyTaskIter, + >, + >, + ), + ToySort( + Batcher< + IterResult2< + ratchet_datasets::nlp::toy::ToyTaskIter, + >, + >, + ), + ToyAdd( + Batcher< + IterResult2< + ratchet_datasets::nlp::toy::ToyTaskIter, + >, + >, + ), + ToyCount( + Batcher< + IterResult2< + ratchet_datasets::nlp::toy::ToyTaskIter, + >, + >, + ), + ToySlapjack( + Batcher< + IterResult2< + ratchet_datasets::nlp::toy::ToyTaskIter, + >, + >, + ), + ToyModAdd( + Batcher< + IterResult2< + ratchet_datasets::nlp::toy::ToyTaskIter, + >, + >, + ), + TinyStories(Batcher>>), +} + +/// An enum for optimizer configurations +#[derive(Debug, Clone)] +pub enum OptimizerConfigEnum { + AdamW(ParamsAdamW), + SGD(f64), +} + +/// An enum that wraps the concrete optimizer types +pub enum OptimizerEnum { + AdamW(AdamW), + SGD(SGD), +} + +#[async_trait] +impl Optimizer for OptimizerEnum { + type Config = OptimizerConfigEnum; + + fn new(vars: Vec<(Option, Var)>, config: Self::Config) -> anyhow::Result { + match config { + OptimizerConfigEnum::AdamW(params) => Ok(Self::AdamW(AdamW::new(vars, params)?)), + OptimizerConfigEnum::SGD(params) => Ok(Self::SGD(SGD::new(vars, params)?)), + } + } + + async fn step(&mut self, grads: &GradStore, device: &Device) -> anyhow::Result<()> { + match self { + OptimizerEnum::AdamW(opt) => opt.step(grads, device).await, + OptimizerEnum::SGD(opt) => opt.step(grads, device).await, + } + } + + fn learning_rate(&self) -> f64 { + match self { + OptimizerEnum::AdamW(opt) => opt.learning_rate(), + OptimizerEnum::SGD(opt) => opt.learning_rate(), + } + } + + fn set_learning_rate(&mut self, lr: f64) { + match self { + OptimizerEnum::AdamW(opt) => opt.set_learning_rate(lr), + OptimizerEnum::SGD(opt) => opt.set_learning_rate(lr), + } + } +} + +// ------------------------------------------------------------------- +// The Trainer manages the model, optimizer, device, and dataset batcher. +// ------------------------------------------------------------------- +#[wasm_bindgen] +pub struct Trainer { + model: GPT2, + optimizer: Box + Send + Sync>, + device: Device, + config: TrainerConfig, + batcher: BatcherType<'static>, +} + +#[wasm_bindgen] +impl Trainer { + /// Create a new Trainer from a JavaScript configuration object. + /// This async constructor initializes the device, model, optimizer, + /// and dataset iterator (wrapped in a Batcher) based on the config. + #[wasm_bindgen(constructor)] + pub async fn new(config: JsValue) -> Result { + // Deserialize the configuration from JS. + let cfg: TrainerConfig = + serde_wasm_bindgen::from_value(config).map_err(|e| JsValue::from(e.to_string()))?; + + // Request a GPU device. + let device = Device::request_device(DeviceRequest::GPU) + .await + .map_err(|e| e.to_string())?; + + // Set the seed if provided + if let Some(seed) = cfg.seed { + device.set_seed(seed); + } + + // Set up the variable map and variable builder for model initialization. + let varmap = VarMap::new(); + let vb = VarBuilder::from_varmap(&varmap, DType::F32, &device); + + // Create the GPT2 model configuration. + let gpt2_config = Config { + vocab_size: cfg.vocab_size, + hidden_act: string_to_activation(&cfg.activation), + n_embd: cfg.n_embd, + n_layer: cfg.n_layer, + n_head: cfg.n_head, + block_size: cfg.block_size, + attention_only: cfg.attention_only, + positional_encoding: match cfg.positional_encoding.to_lowercase().as_str() { + "rope" => PositionalEncoding::RoPE, + "alibi" => PositionalEncoding::ALiBi, + "sinusoidal" => PositionalEncoding::Sinusoidal, + _ => PositionalEncoding::Learned, + }, + layernorm_position: match cfg.layernorm_position.to_lowercase().as_str() { + "pre" => LayerNormPosition::Pre, + "post" => LayerNormPosition::Post, + _ => LayerNormPosition::Pre, + }, + }; + // Initialize the GPT2 model. + let model = GPT2::new(&gpt2_config, vb) + .await + .map_err(|e| e.to_string())?; + + // Set up the optimizer based on the configuration + let vars = varmap + .all_labeled_vars() + .iter() + .map(|(label, var)| (Some(label.to_owned()), var.to_owned())) + .collect::>(); + + let optimizer_config = match cfg.optimizer.optimizer_type.to_lowercase().as_str() { + "sgd" => OptimizerConfigEnum::SGD(cfg.optimizer.lr), + _ => OptimizerConfigEnum::AdamW(ParamsAdamW { + lr: cfg.optimizer.lr, + beta1: cfg.optimizer.beta1, + beta2: cfg.optimizer.beta2, + eps: cfg.optimizer.eps, + weight_decay: cfg.optimizer.weight_decay, + }), + }; + + let base_optimizer = + OptimizerEnum::new(vars, optimizer_config).map_err(|e| e.to_string())?; + + // Wrap the optimizer in the selected scheduler + let optimizer: Box + Send + Sync> = + match cfg.optimizer.scheduler_type.to_lowercase().as_str() { + "constant" => Box::new(ConstantLR::new( + base_optimizer, + cfg.optimizer.scheduler_factor, + cfg.optimizer.scheduler_steps, + )), + "linear" => Box::new(LinearLR::new( + base_optimizer, + 1.0, // start_factor + cfg.optimizer.scheduler_factor, // end_factor + cfg.optimizer.scheduler_steps, + )), + "cosine" => Box::new(CosineAnnealingLR::new( + base_optimizer, + cfg.optimizer.scheduler_steps, + cfg.optimizer.scheduler_eta_min, + )), + _ => Box::new(NoopScheduler::new(base_optimizer)), // Default to no scheduler + }; + + // Based on the config.dataset value, choose the dataset iterator and wrap it in a Batcher. + // Supported options (case-insensitive): "two_sum" (default), "zeros", "tinystories", "sort", "add", "count", "slapjack", "mod_add" + let batcher = match cfg.dataset.to_lowercase().as_str() { + "zeros" => { + let task = ZerosTask::new(cfg.block_size); + let dataset_iter = ToyTaskIter::new(task, device.clone()); + BatcherType::ToyZeros(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) + } + "sort" => { + let task = SortTask::new(20, cfg.seed); + let dataset_iter = ToyTaskIter::new(task, device.clone()); + BatcherType::ToySort(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) + } + "add" => { + let task = AddTask::new(1000, cfg.seed); + let dataset_iter = ToyTaskIter::new(task, device.clone()); + BatcherType::ToyAdd(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) + } + "count" => { + let task = CountTask::new(10, 'd', cfg.seed); + let dataset_iter = ToyTaskIter::new(task, device.clone()); + BatcherType::ToyCount(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) + } + "slapjack" => { + let task = SlapjackTask::new(48, cfg.seed); + let dataset_iter = ToyTaskIter::new(task, device.clone()); + BatcherType::ToySlapjack(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) + } + "mod_add" => { + let task = ModAddTask::new(113, cfg.seed); + let dataset_iter = ToyTaskIter::new(task, device.clone()); + BatcherType::ToyModAdd(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) + } + // "tinystories" => { + // let dataset = TinyStoriesDataset::new(); + // let dataset_iter = TinyStoriesDatasetRandomIter::new(dataset, device.clone()); + // BatcherEnum::TinyStories(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) + // } + // Default (including "two_sum" and unrecognized values): use the TwoSum task. + _ => { + let task = TwoSumTask::new(5, 5, cfg.seed); + let dataset_iter = ToyTaskIter::new(task, device.clone()); + BatcherType::ToyTwoSum(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) + } + }; + + Ok(Trainer { + model, + optimizer, + device, + config: cfg, + batcher, + }) + } + + /// Asynchronously retrieve the next batch as a BatchHandle. + /// The returned BatchHandle wraps a Batch consisting of (input, target) tensors, + /// which reside on the device. + #[wasm_bindgen] + pub async fn next_batch(&mut self) -> Result { + // Pull the next (input, target) tuple from the dataset iterator. + let (input, target) = match &mut self.batcher { + BatcherType::ToyTwoSum(batcher) => batcher + .next() + .ok_or_else(|| { + JsValue::from_str("No more data available in the ToyTwoSum dataset") + })? + .map_err(|e| e.to_string())?, + BatcherType::ToyZeros(batcher) => batcher + .next() + .ok_or_else(|| JsValue::from_str("No more data available in the ToyZeros dataset"))? + .map_err(|e| e.to_string())?, + BatcherType::ToySort(batcher) => batcher + .next() + .ok_or_else(|| JsValue::from_str("No more data available in the ToySort dataset"))? + .map_err(|e| e.to_string())?, + BatcherType::ToyAdd(batcher) => batcher + .next() + .ok_or_else(|| JsValue::from_str("No more data available in the ToyAdd dataset"))? + .map_err(|e| e.to_string())?, + BatcherType::ToyCount(batcher) => batcher + .next() + .ok_or_else(|| JsValue::from_str("No more data available in the ToyCount dataset"))? + .map_err(|e| e.to_string())?, + BatcherType::ToySlapjack(batcher) => batcher + .next() + .ok_or_else(|| { + JsValue::from_str("No more data available in the ToySlapjack dataset") + })? + .map_err(|e| e.to_string())?, + BatcherType::ToyModAdd(batcher) => batcher + .next() + .ok_or_else(|| { + JsValue::from_str("No more data available in the ToyModAdd dataset") + })? + .map_err(|e| e.to_string())?, + BatcherType::TinyStories(batcher) => batcher + .next() + .ok_or_else(|| { + JsValue::from_str("No more data available in the TinyStories dataset") + })? + .map_err(|e| e.to_string())?, + }; + Ok(BatchHandle { + inner: Batch { input, target }, + }) + } + + /// Asynchronously train on the provided batch. + /// Here we assume that `batch.input` and `batch.target` are already on the correct device. + /// They are passed directly into the model; loss, backpropagation, and the optimizer step + /// are performed, and the scalar loss value is returned. + #[wasm_bindgen] + pub async fn train_step(&mut self, batch_handle: BatchHandle) -> Result { + // Extract the batch from the handle. + let batch = batch_handle.inner; + + // Forward pass: compute logits from the model. + let (logits, attn_masks) = self + .model + .schedule(GPT2Input { + x: batch.input, + index_pos: 0, + }) + .map_err(|e| e.to_string())?; + + // Flatten the logits and targets. + let logits_flat = logits.flatten_to(1).map_err(|e| e.to_string())?; + let target_flat = batch.target.flatten_to(1).map_err(|e| e.to_string())?; + + // Compute the cross-entropy loss. + let loss = cross_entropy(logits_flat, target_flat).map_err(|e| e.to_string())?; + + // Backpropagate to compute gradients. + let grads = loss.backward().map_err(|e| e.to_string())?; + + // Run an optimizer step (updating model parameters). + self.optimizer + .step(&grads, &self.device) + .await + .map_err(|e| e.to_string())?; + + log::debug!("Done training step"); + + // Transfer the loss to CPU and extract its scalar value. + let loss_cpu = loss.to(&Device::CPU).await.map_err(|e| e.to_string())?; + let loss_vec = loss_cpu.to_vec::().map_err(|e| e.to_string())?; + + // Transfer attention masks to CPU and get their shape and flattened data + let attn_masks_cpu = attn_masks + .to(&Device::CPU) + .await + .map_err(|e| e.to_string())?; + let attn_masks_shape = attn_masks_cpu.shape().to_vec(); + let attn_masks_data = attn_masks_cpu.to_vec::().map_err(|e| e.to_string())?; + + // Create a JS-friendly object with both loss and attention masks + let result = serde_json::json!({ + "loss": loss_vec[0], + "learning_rate": self.optimizer.get_lr(), + "attn_masks": { + "data": attn_masks_data, + "shape": attn_masks_shape, + } + }); + + serde_wasm_bindgen::to_value(&result).map_err(|e| e.to_string().into()) + } + + #[wasm_bindgen] + pub fn usage_bytes(&self) -> u64 { + self.device.try_gpu().unwrap().usage_bytes() + } +} + +/// A scheduler that does nothing, just passes through to the underlying optimizer. +/// This is used when no scheduler is selected. +pub struct NoopScheduler { + core: LRSchedulerCore, +} + +impl NoopScheduler { + pub fn new(optimizer: O) -> Self { + Self { + core: LRSchedulerCore::new(optimizer), + } + } +} + +impl LRScheduler for NoopScheduler { + fn optimizer_mut(&mut self) -> &mut O { + &mut self.core.optimizer + } + + fn base_lr(&self) -> f64 { + self.core.base_lr + } + + fn step_count(&self) -> usize { + self.core.step_count + } + + fn set_step_count(&mut self, count: usize) { + self.core.step_count = count; + } + + fn compute_lr(&self) -> f64 { + self.core.base_lr + } +} + +#[cfg(all(test, target_arch = "wasm32"))] +mod tests { + use crate::test_utils::log_init; + + use super::*; + use ratchet::{ + shape, + test_utils::{to_vec0_round, to_vec1_round}, + }; + use ratchet_nn::Linear; + use wasm_bindgen_test::*; + + wasm_bindgen_test::wasm_bindgen_test_configure!(run_in_browser); + + #[wasm_bindgen_test] + async fn train_browser() -> Result<(), JsValue> { + log_init(); + let json_config = r#"{ + "vocab_size": 1024, + "n_embd": 768, + "n_layer": 6, + "n_head": 6, + "block_size": 24, + "batch_size": 1, + "dataset": "two_sum", + "optimizer": { + "lr": 1e-3 + } + }"#; + // Parse the JSON string into a TrainerConfig first to validate it + let config: TrainerConfig = + serde_json::from_str(json_config).map_err(|e| JsValue::from(e.to_string()))?; + // Convert to JsValue + let config_js = + serde_wasm_bindgen::to_value(&config).map_err(|e| JsValue::from(e.to_string()))?; + + let mut trainer = Trainer::new(config_js).await.unwrap(); + for i in 0..10 { + let batch = trainer.next_batch().await.unwrap(); + let loss = trainer.train_step(batch).await.unwrap(); + log::error!("step {}: loss: {:?}", i, loss); + } + // log::error!("config_js: {:?}", config_js); + Ok(()) + } +} From 87eb40c14e03c73883aaab82c56fdd42a5101deb Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 16 Feb 2025 17:03:50 -0700 Subject: [PATCH 002/146] Add ratchet-train-toy demo --- examples/ratchet-train-toy/.gitignore | 23 + examples/ratchet-train-toy/.npmrc | 1 + examples/ratchet-train-toy/.prettierignore | 4 + examples/ratchet-train-toy/.prettierrc | 17 + examples/ratchet-train-toy/README.md | 1 + examples/ratchet-train-toy/eslint.config.js | 34 + examples/ratchet-train-toy/package.json | 43 + examples/ratchet-train-toy/src/app.css | 1 + examples/ratchet-train-toy/src/app.d.ts | 13 + examples/ratchet-train-toy/src/app.html | 12 + .../lib/components/ActivationPicker.svelte | 79 ++ .../src/lib/components/BaseSlider.svelte | 96 ++ .../src/lib/components/LogSlider.svelte | 127 ++ .../src/lib/components/Slider.svelte | 25 + .../src/lib/components/TickSlider.svelte | 69 ++ examples/ratchet-train-toy/src/lib/index.ts | 1 + .../src/routes/+layout.svelte | 6 + .../ratchet-train-toy/src/routes/+layout.ts | 1 + .../ratchet-train-toy/src/routes/+page.svelte | 1033 +++++++++++++++++ examples/ratchet-train-toy/src/trainWorker.ts | 109 ++ examples/ratchet-train-toy/svelte.config.js | 15 + examples/ratchet-train-toy/tsconfig.json | 19 + examples/ratchet-train-toy/vite.config.ts | 18 + 23 files changed, 1747 insertions(+) create mode 100644 examples/ratchet-train-toy/.gitignore create mode 100644 examples/ratchet-train-toy/.npmrc create mode 100644 examples/ratchet-train-toy/.prettierignore create mode 100644 examples/ratchet-train-toy/.prettierrc create mode 100644 examples/ratchet-train-toy/README.md create mode 100644 examples/ratchet-train-toy/eslint.config.js create mode 100644 examples/ratchet-train-toy/package.json create mode 100644 examples/ratchet-train-toy/src/app.css create mode 100644 examples/ratchet-train-toy/src/app.d.ts create mode 100644 examples/ratchet-train-toy/src/app.html create mode 100644 examples/ratchet-train-toy/src/lib/components/ActivationPicker.svelte create mode 100644 examples/ratchet-train-toy/src/lib/components/BaseSlider.svelte create mode 100644 examples/ratchet-train-toy/src/lib/components/LogSlider.svelte create mode 100644 examples/ratchet-train-toy/src/lib/components/Slider.svelte create mode 100644 examples/ratchet-train-toy/src/lib/components/TickSlider.svelte create mode 100644 examples/ratchet-train-toy/src/lib/index.ts create mode 100644 examples/ratchet-train-toy/src/routes/+layout.svelte create mode 100644 examples/ratchet-train-toy/src/routes/+layout.ts create mode 100644 examples/ratchet-train-toy/src/routes/+page.svelte create mode 100644 examples/ratchet-train-toy/src/trainWorker.ts create mode 100644 examples/ratchet-train-toy/svelte.config.js create mode 100644 examples/ratchet-train-toy/tsconfig.json create mode 100644 examples/ratchet-train-toy/vite.config.ts diff --git a/examples/ratchet-train-toy/.gitignore b/examples/ratchet-train-toy/.gitignore new file mode 100644 index 00000000..3b462cb0 --- /dev/null +++ b/examples/ratchet-train-toy/.gitignore @@ -0,0 +1,23 @@ +node_modules + +# Output +.output +.vercel +.netlify +.wrangler +/.svelte-kit +/build + +# OS +.DS_Store +Thumbs.db + +# Env +.env +.env.* +!.env.example +!.env.test + +# Vite +vite.config.js.timestamp-* +vite.config.ts.timestamp-* diff --git a/examples/ratchet-train-toy/.npmrc b/examples/ratchet-train-toy/.npmrc new file mode 100644 index 00000000..b6f27f13 --- /dev/null +++ b/examples/ratchet-train-toy/.npmrc @@ -0,0 +1 @@ +engine-strict=true diff --git a/examples/ratchet-train-toy/.prettierignore b/examples/ratchet-train-toy/.prettierignore new file mode 100644 index 00000000..ab78a95d --- /dev/null +++ b/examples/ratchet-train-toy/.prettierignore @@ -0,0 +1,4 @@ +# Package Managers +package-lock.json +pnpm-lock.yaml +yarn.lock diff --git a/examples/ratchet-train-toy/.prettierrc b/examples/ratchet-train-toy/.prettierrc new file mode 100644 index 00000000..b5132629 --- /dev/null +++ b/examples/ratchet-train-toy/.prettierrc @@ -0,0 +1,17 @@ +{ + "useTabs": true, + "singleQuote": true, + "trailingComma": "none", + "printWidth": 100, + "plugins": [ + "prettier-plugin-svelte" + ], + "overrides": [ + { + "files": "*.svelte", + "options": { + "parser": "svelte" + } + } + ] +} diff --git a/examples/ratchet-train-toy/README.md b/examples/ratchet-train-toy/README.md new file mode 100644 index 00000000..22309833 --- /dev/null +++ b/examples/ratchet-train-toy/README.md @@ -0,0 +1 @@ +# ratchet-train-toy demo \ No newline at end of file diff --git a/examples/ratchet-train-toy/eslint.config.js b/examples/ratchet-train-toy/eslint.config.js new file mode 100644 index 00000000..e18311fa --- /dev/null +++ b/examples/ratchet-train-toy/eslint.config.js @@ -0,0 +1,34 @@ +import prettier from "eslint-config-prettier"; +import js from '@eslint/js'; +import { includeIgnoreFile } from '@eslint/compat'; +import svelte from 'eslint-plugin-svelte'; +import globals from 'globals'; +import { fileURLToPath } from 'node:url'; +import ts from 'typescript-eslint'; +const gitignorePath = fileURLToPath(new URL("./.gitignore", import.meta.url)); + +export default ts.config( + includeIgnoreFile(gitignorePath), + js.configs.recommended, + ...ts.configs.recommended, + ...svelte.configs["flat/recommended"], + prettier, + ...svelte.configs['flat/prettier'], + { + languageOptions: { + globals: { + ...globals.browser, + ...globals.node + } + } + }, + { + files: ["**/*.svelte"], + + languageOptions: { + parserOptions: { + parser: ts.parser + } + } + } +); diff --git a/examples/ratchet-train-toy/package.json b/examples/ratchet-train-toy/package.json new file mode 100644 index 00000000..375b32e4 --- /dev/null +++ b/examples/ratchet-train-toy/package.json @@ -0,0 +1,43 @@ +{ + "name": "ratchet-train-toy", + "private": true, + "version": "0.0.1", + "type": "module", + "scripts": { + "dev": "vite dev", + "build": "vite build", + "preview": "vite preview", + "prepare": "svelte-kit sync || echo ''", + "check": "svelte-kit sync && svelte-check --tsconfig ./tsconfig.json", + "check:watch": "svelte-kit sync && svelte-check --tsconfig ./tsconfig.json --watch", + "lint": "eslint . && prettier --check .", + "format": "prettier --write ." + }, + "dependencies": { + "@ratchet-ml/ratchet-web-train": "link:../../target/pkg/ratchet-web-train", + "chart.js": "^4.4.7", + "mathjs": "^14.2.1" + }, + "devDependencies": { + "@eslint/compat": "^1.2.5", + "@eslint/js": "^9.18.0", + "@sveltejs/adapter-static": "^3.0.8", + "@sveltejs/kit": "^2.16.0", + "@sveltejs/vite-plugin-svelte": "^5.0.0", + "@tailwindcss/vite": "^4.0.0", + "eslint": "^9.18.0", + "eslint-config-prettier": "^10.0.1", + "eslint-plugin-svelte": "^2.46.1", + "globals": "^15.14.0", + "prettier": "^3.4.2", + "prettier-plugin-svelte": "^3.3.3", + "svelte": "^5.0.0", + "svelte-check": "^4.0.0", + "tailwindcss": "^4.0.0", + "typescript": "^5.0.0", + "typescript-eslint": "^8.20.0", + "vite": "^6.1.0", + "vite-plugin-top-level-await": "^1.4.4", + "vite-plugin-wasm": "^3.4.1" + } +} \ No newline at end of file diff --git a/examples/ratchet-train-toy/src/app.css b/examples/ratchet-train-toy/src/app.css new file mode 100644 index 00000000..f86f709d --- /dev/null +++ b/examples/ratchet-train-toy/src/app.css @@ -0,0 +1 @@ +@import 'tailwindcss' diff --git a/examples/ratchet-train-toy/src/app.d.ts b/examples/ratchet-train-toy/src/app.d.ts new file mode 100644 index 00000000..da08e6da --- /dev/null +++ b/examples/ratchet-train-toy/src/app.d.ts @@ -0,0 +1,13 @@ +// See https://svelte.dev/docs/kit/types#app.d.ts +// for information about these interfaces +declare global { + namespace App { + // interface Error {} + // interface Locals {} + // interface PageData {} + // interface PageState {} + // interface Platform {} + } +} + +export {}; diff --git a/examples/ratchet-train-toy/src/app.html b/examples/ratchet-train-toy/src/app.html new file mode 100644 index 00000000..5889edbd --- /dev/null +++ b/examples/ratchet-train-toy/src/app.html @@ -0,0 +1,12 @@ + + + + + + + %sveltekit.head% + + +
%sveltekit.body%
+ + diff --git a/examples/ratchet-train-toy/src/lib/components/ActivationPicker.svelte b/examples/ratchet-train-toy/src/lib/components/ActivationPicker.svelte new file mode 100644 index 00000000..5ba7fe76 --- /dev/null +++ b/examples/ratchet-train-toy/src/lib/components/ActivationPicker.svelte @@ -0,0 +1,79 @@ + + +
+
+ +
+ +
+
+
+ + + + + + + + +
+
\ No newline at end of file diff --git a/examples/ratchet-train-toy/src/lib/components/BaseSlider.svelte b/examples/ratchet-train-toy/src/lib/components/BaseSlider.svelte new file mode 100644 index 00000000..eacc08b5 --- /dev/null +++ b/examples/ratchet-train-toy/src/lib/components/BaseSlider.svelte @@ -0,0 +1,96 @@ + + +
+ +
+ +
+
+ + +
+
+
+ + \ No newline at end of file diff --git a/examples/ratchet-train-toy/src/lib/components/LogSlider.svelte b/examples/ratchet-train-toy/src/lib/components/LogSlider.svelte new file mode 100644 index 00000000..63372085 --- /dev/null +++ b/examples/ratchet-train-toy/src/lib/components/LogSlider.svelte @@ -0,0 +1,127 @@ + + + +
+ {formatNumber(logValue)} +
+ +
+ {#each ticks as tick} + {@const position = `${((tick.value - minExp) / (maxExp - minExp)) * 100}%`} + {@const isSnapPoint = snapPoints.includes(tick.value)} +
+
+ {#if tick.type === 'major'} +
+ {@html tick.label} +
+ {/if} +
+ {/each} +
+ + + \ No newline at end of file diff --git a/examples/ratchet-train-toy/src/lib/components/Slider.svelte b/examples/ratchet-train-toy/src/lib/components/Slider.svelte new file mode 100644 index 00000000..1ba7c119 --- /dev/null +++ b/examples/ratchet-train-toy/src/lib/components/Slider.svelte @@ -0,0 +1,25 @@ + + + +
+ {formatter(value)} +
+ + \ No newline at end of file diff --git a/examples/ratchet-train-toy/src/lib/components/TickSlider.svelte b/examples/ratchet-train-toy/src/lib/components/TickSlider.svelte new file mode 100644 index 00000000..02fc9868 --- /dev/null +++ b/examples/ratchet-train-toy/src/lib/components/TickSlider.svelte @@ -0,0 +1,69 @@ + + + +
+ {formatter(value)} +
+ +
+ {#each ticks as tick} + {@const position = `${((tick.value - min) / (max - min)) * 100}%`} +
+
+
+ {/each} +
+ + + \ No newline at end of file diff --git a/examples/ratchet-train-toy/src/lib/index.ts b/examples/ratchet-train-toy/src/lib/index.ts new file mode 100644 index 00000000..856f2b6c --- /dev/null +++ b/examples/ratchet-train-toy/src/lib/index.ts @@ -0,0 +1 @@ +// place files you want to import through the `$lib` alias in this folder. diff --git a/examples/ratchet-train-toy/src/routes/+layout.svelte b/examples/ratchet-train-toy/src/routes/+layout.svelte new file mode 100644 index 00000000..9b776b77 --- /dev/null +++ b/examples/ratchet-train-toy/src/routes/+layout.svelte @@ -0,0 +1,6 @@ + + +{@render children()} diff --git a/examples/ratchet-train-toy/src/routes/+layout.ts b/examples/ratchet-train-toy/src/routes/+layout.ts new file mode 100644 index 00000000..189f71e2 --- /dev/null +++ b/examples/ratchet-train-toy/src/routes/+layout.ts @@ -0,0 +1 @@ +export const prerender = true; diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte new file mode 100644 index 00000000..056e425b --- /dev/null +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -0,0 +1,1033 @@ + + +
+ {#if !hasWebGPU} + + {/if} +
+
+
+

toy transformer

+
+ @vinhowe + @grantpitt + github +
+
+
+

train loss: {loss.toFixed(4)}

+

val loss: -.----

+
+
+ +
+ + + {#if isTraining} +
+
+ + +
+ + {#if showAttention && attentionCanvases.length > 0} + +
+ {#each attentionCanvases as layerCanvases, layerIdx} +
+

Layer {layerIdx + 1}

+
+ {#each layerCanvases as canvas, headIdx} +
+ +
Head {headIdx + 1}
+
+ {/each} +
+
+ {/each} +
+ {/if} +
+ {/if} +
+ +
+
+ +
+
+ +
+ +
+
+ {#each messages as message} +
+ [{message.timestamp}] + {message.text} +
+ {/each} +
+
+
+
+
+ + {#if isTraining} + + {/if} +
+
+

Dataset

+
+ +
+ +
+ +
+
+ +
+
+
+

Model Architecture

+ + + + +
+ `${v} per head`} + /> +
+ +
+ + +
+ +
+ +
+ +
+ + + +
+
+
+ +
+ +
+ +
+ + + +
+
+
+ +
+
+ + +
+
+
+ +
+

Optimizer

+ +
+ +
+ +
+ + + +
+
+
+ + + + {#if optimizer_type === 'adamw'} + + + {#if showAdvanced} +
+
+
+ + +
+ +
+ + +
+
+ +
+ +
+ +
+ +
+
+ {/if} + {/if} + +
+ +
+ +
+ + + +
+
+
+ + {#if scheduler_type !== 'none'} +
+
+ + +
+ + {#if scheduler_type === 'constant' || scheduler_type === 'linear'} +
+ + +
+ {/if} + + {#if scheduler_type === 'cosine'} +
+ + +
+ {/if} +
+ {/if} +
+ +
+

Training Options

+ +
+ +
+ +
+ + +
+
+
+
+
diff --git a/examples/ratchet-train-toy/src/trainWorker.ts b/examples/ratchet-train-toy/src/trainWorker.ts new file mode 100644 index 00000000..babcadb2 --- /dev/null +++ b/examples/ratchet-train-toy/src/trainWorker.ts @@ -0,0 +1,109 @@ +import { Trainer } from '@ratchet-ml/ratchet-web-train'; + +let trainer: Trainer; +let sessionCounter = 0; +let currentSession = 0; +const trainingSessions: Record = {}; + +export interface TrainerConfig { + vocab_size: number; + n_embd: number; + n_layer: number; + n_head: number; + block_size: number; + batch_size: number; + dataset: string; + activation: string; + attention_only: boolean; + position_encoding: string; + seed?: number; + layernorm_position: string; + optimizer: { + optimizer_type: string; + lr: number; + beta1: number; + beta2: number; + eps: number; + weight_decay: number; + momentum: number; + scheduler_type: string; + scheduler_factor: number; + scheduler_steps: number; + scheduler_eta_min: number; + }; +} + +function markStopTraining() { + Object.keys(trainingSessions).forEach((key) => { + trainingSessions[Number(key)] = false; + }); +} + +async function initializeTrainer(config: TrainerConfig) { + // Stop all existing training sessions + markStopTraining(); + + trainer = await new Trainer(config); + self.postMessage({ type: 'modelReady' }); + currentSession = sessionCounter++; + trainingSessions[currentSession] = true; + trainingLoop(currentSession); +} + +async function trainingLoop(sessionId: number) { + if (!trainer) { + console.error('Trainer not initialized'); + return; + } + while (trainingSessions[sessionId]) { + // Skip if this isn't the current session anymore + if (sessionId !== currentSession) { + break; + } + + try { + const batch = await trainer.next_batch(); + const result: Map = await trainer.train_step(batch); + const attn_masks = result.get('attn_masks') as Map; + const usage_bytes = trainer.usage_bytes(); + + // Only send message if this is still the current session + if (sessionId === currentSession) { + self.postMessage({ + type: 'step', + loss: result.get('loss'), + learning_rate: result.get('learning_rate'), + usage_bytes, + attn_masks: { + data: attn_masks.get('data'), + shape: attn_masks.get('shape') + } + }); + } + } catch (error: Error | unknown) { + console.error('Training error in worker:', error); + if (sessionId === currentSession) { + self.postMessage({ + type: 'error', + error: error instanceof Error ? error.message : String(error) + }); + } + break; + } + // Yield to keep the worker responsive + await new Promise((resolve) => setTimeout(resolve, 0)); + } +} + +self.onmessage = async (e: MessageEvent) => { + if (e.data.type === 'stop') { + markStopTraining(); + return; + } + // If we receive a configuration object, initialize a new trainer + if (typeof e.data === 'object') { + await initializeTrainer(e.data); + } +}; + +self.postMessage({ type: 'ready' }); diff --git a/examples/ratchet-train-toy/svelte.config.js b/examples/ratchet-train-toy/svelte.config.js new file mode 100644 index 00000000..92d0e09f --- /dev/null +++ b/examples/ratchet-train-toy/svelte.config.js @@ -0,0 +1,15 @@ +import adapter from "@sveltejs/adapter-static"; +import { vitePreprocess } from '@sveltejs/vite-plugin-svelte'; + +/** @type {import('@sveltejs/kit').Config} */ +const config = { + // Consult https://svelte.dev/docs/kit/integrations + // for more information about preprocessors + preprocess: vitePreprocess(), + + kit: { + adapter: adapter() + } +}; + +export default config; diff --git a/examples/ratchet-train-toy/tsconfig.json b/examples/ratchet-train-toy/tsconfig.json new file mode 100644 index 00000000..0b2d8865 --- /dev/null +++ b/examples/ratchet-train-toy/tsconfig.json @@ -0,0 +1,19 @@ +{ + "extends": "./.svelte-kit/tsconfig.json", + "compilerOptions": { + "allowJs": true, + "checkJs": true, + "esModuleInterop": true, + "forceConsistentCasingInFileNames": true, + "resolveJsonModule": true, + "skipLibCheck": true, + "sourceMap": true, + "strict": true, + "moduleResolution": "bundler" + } + // Path aliases are handled by https://svelte.dev/docs/kit/configuration#alias + // except $lib which is handled by https://svelte.dev/docs/kit/configuration#files + // + // If you want to overwrite includes/excludes, make sure to copy over the relevant includes/excludes + // from the referenced tsconfig.json - TypeScript does not merge them in +} diff --git a/examples/ratchet-train-toy/vite.config.ts b/examples/ratchet-train-toy/vite.config.ts new file mode 100644 index 00000000..6b6a3913 --- /dev/null +++ b/examples/ratchet-train-toy/vite.config.ts @@ -0,0 +1,18 @@ +import tailwindcss from '@tailwindcss/vite'; +import { sveltekit } from '@sveltejs/kit/vite'; +import { defineConfig } from 'vite'; +import wasm from 'vite-plugin-wasm'; +import topLevelAwait from 'vite-plugin-top-level-await'; + +export default defineConfig({ + plugins: [sveltekit(), tailwindcss(), wasm(), topLevelAwait()], + worker: { + format: 'es', + plugins: () => [wasm(), topLevelAwait()] + }, + esbuild: { + supported: { + 'top-level-await': true + } + } +}); From 06b66404f624eb01e8b5dc51e916f032382e8e4c Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 16 Feb 2025 17:04:38 -0700 Subject: [PATCH 003/146] Target bundler with wasm builds --- justfile | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/justfile b/justfile index 5cf75054..003dd30f 100644 --- a/justfile +++ b/justfile @@ -5,9 +5,9 @@ install-pyo3: pyenv local 3.10.6 echo $(python --version) wasm CRATE: - node_modules/.bin/wasm-pack build -s ratchet --target web -d `pwd`/target/pkg/{{CRATE}} --out-name {{CRATE}} ./crates/{{CRATE}} --release + node_modules/.bin/wasm-pack build -s ratchet --target bundler -d `pwd`/target/pkg/{{CRATE}} --out-name {{CRATE}} ./crates/{{CRATE}} --release wasm-dbg CRATE: - node_modules/.bin/wasm-pack build -s ratchet --target web -d `pwd`/target/pkg/{{CRATE}} --out-name {{CRATE}} ./crates/{{CRATE}} --dev + node_modules/.bin/wasm-pack build -s ratchet --target bundler -d `pwd`/target/pkg/{{CRATE}} --out-name {{CRATE}} ./crates/{{CRATE}} --dev wasm-test CRATE BROWSER: cp ./config/webdriver-macos.json ./crates/{{CRATE}}/webdriver.json node_modules/.bin/wasm-pack test --{{BROWSER}} --headless `pwd`/crates/{{CRATE}} From d75b38b964f5e943cd60511772ce2e05c1f36d91 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 16 Feb 2025 17:05:10 -0700 Subject: [PATCH 004/146] Update pnpm lock (: --- pnpm-lock.yaml | 2251 ++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 2202 insertions(+), 49 deletions(-) diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml index ba57a17d..3f4932cc 100644 --- a/pnpm-lock.yaml +++ b/pnpm-lock.yaml @@ -23,9 +23,9 @@ importers: '@ffmpeg/util': specifier: ^0.12.1 version: 0.12.1 - '@ratchet-ml/ratchet-web': - specifier: link:../../target/pkg/ratchet-web - version: link:../../target/pkg/ratchet-web + '@ratchet-ml/ratchet-web-train': + specifier: link:../../target/pkg/ratchet-web-train + version: link:../../target/pkg/ratchet-web-train fix-webm-duration: specifier: ^1.0.5 version: 1.0.5 @@ -67,6 +67,76 @@ importers: specifier: ^5.3.3 version: 5.3.3 + examples/ratchet-train-toy: + dependencies: + chart.js: + specifier: ^4.4.7 + version: 4.4.7 + mathjs: + specifier: ^14.2.1 + version: 14.2.1 + devDependencies: + '@eslint/compat': + specifier: ^1.2.5 + version: 1.2.6(eslint@9.20.1) + '@eslint/js': + specifier: ^9.18.0 + version: 9.20.0 + '@sveltejs/adapter-static': + specifier: ^3.0.8 + version: 3.0.8(@sveltejs/kit@2.17.1) + '@sveltejs/kit': + specifier: ^2.16.0 + version: 2.17.1(@sveltejs/vite-plugin-svelte@5.0.3)(svelte@5.19.10)(vite@6.1.0) + '@sveltejs/vite-plugin-svelte': + specifier: ^5.0.0 + version: 5.0.3(svelte@5.19.10)(vite@6.1.0) + '@tailwindcss/vite': + specifier: ^4.0.0 + version: 4.0.6(vite@6.1.0) + eslint: + specifier: ^9.18.0 + version: 9.20.1 + eslint-config-prettier: + specifier: ^10.0.1 + version: 10.0.1(eslint@9.20.1) + eslint-plugin-svelte: + specifier: ^2.46.1 + version: 2.46.1(eslint@9.20.1)(svelte@5.19.10) + globals: + specifier: ^15.14.0 + version: 15.14.0 + prettier: + specifier: ^3.4.2 + version: 3.5.0 + prettier-plugin-svelte: + specifier: ^3.3.3 + version: 3.3.3(prettier@3.5.0)(svelte@5.19.10) + svelte: + specifier: ^5.0.0 + version: 5.19.10 + svelte-check: + specifier: ^4.0.0 + version: 4.1.4(svelte@5.19.10)(typescript@5.3.3) + tailwindcss: + specifier: ^4.0.0 + version: 4.0.6 + typescript: + specifier: ^5.0.0 + version: 5.3.3 + typescript-eslint: + specifier: ^8.20.0 + version: 8.24.0(eslint@9.20.1)(typescript@5.3.3) + vite: + specifier: ^6.1.0 + version: 6.1.0 + vite-plugin-top-level-await: + specifier: ^1.4.4 + version: 1.4.4(vite@6.1.0) + vite-plugin-wasm: + specifier: ^3.4.1 + version: 3.4.1(vite@6.1.0) + examples/ratchet-whisper: dependencies: '@ffmpeg/ffmpeg': @@ -126,6 +196,21 @@ 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postcss: 8.5.2 + rollup: 4.34.6 + optionalDependencies: + fsevents: 2.3.3 + dev: true + + /vitefu@1.0.5(vite@6.1.0): + resolution: {integrity: sha512-h4Vflt9gxODPFNGPwp4zAMZRpZR7eslzwH2c5hn5kNZ5rhnKyRJ50U+yGCdc2IRaBs8O4haIgLNGrV5CrpMsCA==} + peerDependencies: + vite: ^3.0.0 || ^4.0.0 || ^5.0.0 || ^6.0.0 + peerDependenciesMeta: + vite: + optional: true + dependencies: + vite: 6.1.0 + dev: true + /wasm-pack@0.12.1: resolution: {integrity: sha512-dIyKWUumPFsGohdndZjDXRFaokUT/kQS+SavbbiXVAvA/eN4riX5QNdB6AhXQx37zNxluxQkuixZUgJ8adKjOg==} hasBin: true - requiresBuild: true dependencies: binary-install: 1.1.0 transitivePeerDependencies: @@ -1626,6 +3760,11 @@ packages: isexe: 2.0.0 dev: true + /word-wrap@1.2.5: + resolution: {integrity: sha512-BN22B5eaMMI9UMtjrGd5g5eCYPpCPDUy0FJXbYsaT5zYxjFOckS53SQDE3pWkVoWpHXVb3BrYcEN4Twa55B5cA==} + engines: {node: '>=0.10.0'} + dev: true + /wrap-ansi@7.0.0: resolution: {integrity: 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/zod-package-json@1.0.3: resolution: {integrity: sha512-Mb6GzuRyUEl8X+6V6xzHbd4XV0au/4gOYrYP+CAfHL32uPmGswES+v2YqonZiW1NZWVA3jkssCKSU2knonm/aQ==} engines: {node: '>=20'} From b56154e624068bda0b272dbadd8a711163a26c7e Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 16 Feb 2025 17:06:39 -0700 Subject: [PATCH 005/146] I think this is important? --- package.json | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/package.json b/package.json index 6cbe15d0..1061aeac 100644 --- a/package.json +++ b/package.json @@ -6,5 +6,10 @@ "devDependencies": { "pkg-pr-new": "0.0.15", "wasm-pack": "0.12.1" + }, + "pnpm": { + "onlyBuiltDependencies": [ + "esbuild" + ] } -} +} \ No newline at end of file From e0d2fac8c123a0ba4b2f5366fcb24ed223023787 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 16 Feb 2025 17:18:26 -0700 Subject: [PATCH 006/146] Yeah we're just gonna switch this for now --- .cargo/config.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.cargo/config.toml b/.cargo/config.toml index 6330d419..a14c7a91 100644 --- a/.cargo/config.toml +++ b/.cargo/config.toml @@ -2,4 +2,4 @@ [build] rustflags = [ "--cfg=web_sys_unstable_apis" ] rustdocflags = [ "--cfg=web_sys_unstable_apis" ] -#target = "wasm32-unknown-unknown" +target = "wasm32-unknown-unknown" From d802af9a7e496acc4167d0e6c60f8cff9421684e Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 16 Feb 2025 17:23:07 -0700 Subject: [PATCH 007/146] Remove tokenizers import for now? --- crates/ratchet-datasets/Cargo.toml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/crates/ratchet-datasets/Cargo.toml b/crates/ratchet-datasets/Cargo.toml index 79f7f358..5eb88f7f 100644 --- a/crates/ratchet-datasets/Cargo.toml +++ b/crates/ratchet-datasets/Cargo.toml @@ -28,9 +28,9 @@ wasm-opt = ['-O3', '--enable-simd'] ratchet = { path = "../ratchet-core" } ratchet-loader = { path = "../ratchet-loader" } log.workspace = true -tokenizers = { version = "0.19.1", default-features = false, features = [ - "unstable_wasm", -] } +# tokenizers = { version = "0.19.1", default-features = false, features = [ +# "unstable_wasm", +# ] } anyhow.workspace = true memmap2.workspace = true rand.workspace = true From de2e0689a846e6ac0532382788250c29ec777ca2 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 16 Feb 2025 17:26:28 -0700 Subject: [PATCH 008/146] Revert "Remove tokenizers import for now?" This reverts commit d802af9a7e496acc4167d0e6c60f8cff9421684e. --- crates/ratchet-datasets/Cargo.toml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/crates/ratchet-datasets/Cargo.toml b/crates/ratchet-datasets/Cargo.toml index 5eb88f7f..79f7f358 100644 --- a/crates/ratchet-datasets/Cargo.toml +++ b/crates/ratchet-datasets/Cargo.toml @@ -28,9 +28,9 @@ wasm-opt = ['-O3', '--enable-simd'] ratchet = { path = "../ratchet-core" } ratchet-loader = { path = "../ratchet-loader" } log.workspace = true -# tokenizers = { version = "0.19.1", default-features = false, features = [ -# "unstable_wasm", -# ] } +tokenizers = { version = "0.19.1", default-features = false, features = [ + "unstable_wasm", +] } anyhow.workspace = true memmap2.workspace = true rand.workspace = true From 57ba9ce4ba3f31efeb30ebbaed34ed2e8df5029e Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Mon, 17 Feb 2025 22:20:14 -0700 Subject: [PATCH 009/146] Add sort of hacky cached inference --- crates/ratchet-models/src/gpt2/attn.rs | 30 +++-- crates/ratchet-models/src/gpt2/generate.rs | 128 ++++++++++++++------- crates/ratchet-models/src/gpt2/mod.rs | 5 +- crates/ratchet-models/src/gpt2/model.rs | 79 +++++++++++-- crates/ratchet-nn/src/kv_cache.rs | 33 +++++- 5 files changed, 212 insertions(+), 63 deletions(-) diff --git a/crates/ratchet-models/src/gpt2/attn.rs b/crates/ratchet-models/src/gpt2/attn.rs index f92481ca..7d2ca833 100644 --- a/crates/ratchet-models/src/gpt2/attn.rs +++ b/crates/ratchet-models/src/gpt2/attn.rs @@ -104,19 +104,31 @@ impl Module for GPT2SelfAttention { let mut q = q.view(qkv_shape.clone())?.permute(&[0, 2, 1, 3])?; let v = v.view(qkv_shape.clone())?.permute(&[0, 2, 1, 3])?; + let cache_entry = if cache.borrow_mut().use_kv_cache() { + let cache_ref = cache.borrow_mut(); + let entry = cache_ref[block_idx].clone(); + Some(entry) + } else { + None + }; + let offset = cache_entry.as_ref().map(|kv| kv.entries).unwrap_or(0); // Apply RoPE if enabled if let Some(rope) = &self.rope { - q = rope.schedule(RotaryInput { - input: q, - offset: index_pos, - })?; - k = rope.schedule(RotaryInput { - input: k, - offset: index_pos, - })?; + q = rope.schedule(RotaryInput { input: q, offset })?; + k = rope.schedule(RotaryInput { input: k, offset })?; } - let mut att = q.matmul(k, false, true)?.mul(self.softmax_scale.clone())?; + let (k, v) = if let Some(cache_entry) = cache_entry { + let k_cache = cache_entry.k_cache.cache(k, 2, offset)?; + let v_cache = cache_entry.v_cache.cache(v, 2, offset)?; + (k_cache, v_cache) + } else { + (k, v) + }; + + let mut att = q + .matmul(k.clone(), false, true)? + .mul(self.softmax_scale.clone())?; // Apply ALiBi if enabled if let Some(alibi) = &self.alibi { diff --git a/crates/ratchet-models/src/gpt2/generate.rs b/crates/ratchet-models/src/gpt2/generate.rs index 984c242b..5c3e1fbd 100644 --- a/crates/ratchet-models/src/gpt2/generate.rs +++ b/crates/ratchet-models/src/gpt2/generate.rs @@ -1,57 +1,103 @@ -#![cfg(target_arch = "wasm32")] -use crate::gpt2::GPT2; -use crate::TokenOutputStream; -use ndarray::Axis; +use crate::gpt2::{GPT2Input, GPT2}; +use maybe_async::maybe_async; +use ndarray::{Array3, Axis, Ix3}; use ndarray_stats::QuantileExt; use ratchet::{shape, Device, Tensor}; use ratchet_nn::Module; -use tokenizers::Tokenizer; +#[maybe_async] pub async fn generate( model: &mut GPT2, - tokenizer: Tokenizer, - prompt: String, - callback: impl Fn(String), -) -> anyhow::Result<()> { - use web_time::Instant; - log::warn!("Prompt: {}", prompt); - - let mut tos = TokenOutputStream::new(tokenizer); - let encoding = tos.tokenizer().encode(prompt, true).unwrap(); - let mut tokens = encoding - .get_ids() - .iter() - .map(|&x| x as i32) - .collect::>(); - let mut all_tokens = tokens.clone(); - let mut loop_cnt = 0; - let start = Instant::now(); - while tokens[tokens.len() - 1] != 50256 && loop_cnt < 256 { + prompt: Vec, + // The callback now receives: + // - A Vec of the tokens fed in this pass (either the prompt, or the latest token) + // - An ndarray (shape: [1, seq_len, vocab_size]) containing the logits for that pass. + callback: impl Fn(Vec, Array3), + max_tokens: usize, +) -> anyhow::Result>> { + // Preserve original cache setting and enable kv-cache for generation. + let use_kv_cache = model.cache_mut().use_kv_cache(); + model.cache_mut().set_use_kv_cache(true); + + // This vector will accumulate the logits (as ndarray on CPU) from each model call. + let mut all_logits_ndarray: Vec> = Vec::new(); + + // all_tokens holds the entire context (prompt + generated tokens). + let mut all_tokens = prompt.clone(); + // Count only the tokens that are generated (not in the original prompt) + let mut generated_count = 0; + + while generated_count < max_tokens { + // For the first pass, feed the entire prompt. + // For subsequent passes, feed only the latest generated token. + let tokens_to_feed = if generated_count == 0 { + &all_tokens[..] + } else { + &all_tokens[all_tokens.len() - 1..] + }; + + // Build the input tensor from tokens_to_feed. let input = Tensor::from_data( - tokens.clone(), - shape![1, tokens.len()], + tokens_to_feed, + shape![1, tokens_to_feed.len()], model.device.clone(), ); - let result = model.schedule(input)?; - let logits = result.to(&Device::CPU).await?; - model.cache_mut().update(tokens.len()); - tokens = logits + // The index_pos is the total length of the context so far. + let (result, _) = model.schedule(GPT2Input { + x: input, + index_pos: all_tokens.len(), + })?; + + // Bring the logits to the CPU. + let logits_cpu = result.to(&Device::CPU).await?; + + // Update the kv-cache: + // - For the first pass, update with the full length. + // - For subsequent passes, update only with the new token. + if generated_count == 0 { + model.cache_mut().update(all_tokens.len() + 1); + } else { + model.cache_mut().update(1); + } + + // Convert the logits to an owned ndarray. + // The logits have shape [1, seq_len, vocab_size] where: + // - seq_len == prompt.len() on first pass, or 1 on subsequent passes. + let logits_nd = logits_cpu .to_ndarray_view::() - .map_axis(Axis(2), |row| row.argmax_skipnan().unwrap()) - .iter() - .map(|&x| x as i32) - .collect::>(); + .into_owned() + .into_dimensionality::() + .unwrap(); + // Store them in our accumulator. + all_logits_ndarray.push(logits_nd.clone()); + + // *** Stream the current pass via the callback *** + // Pass the tokens that were fed (as a Vec) and the corresponding logits ndarray. + callback(tokens_to_feed.to_vec(), logits_nd.clone()); - if let Some(t) = tos.next_token(tokens[0] as u32)? { - callback(t); + // Extract the logits for the last token in this pass: + // - For the first pass, that's at index (prompt.len() - 1). + // - For later passes, the only token is at index 0. + let seq_len_this_pass = tokens_to_feed.len(); + let last_logits = logits_nd.index_axis(Axis(1), seq_len_this_pass - 1); + // last_logits has shape [1, vocab_size]; take the 0th row. + let vocab_logits = last_logits.index_axis(Axis(0), 0); + // Use argmax_skipnan from ndarray_stats to get the next token id. + let next_token_id = vocab_logits.argmax_skipnan().unwrap() as i32; + + // Stop if the end-of-text token is generated. + if next_token_id == 50256 { + break; } - all_tokens.extend(tokens.clone()); - loop_cnt += 1; + + // Append the generated token to the full context. + all_tokens.push(next_token_id); + generated_count += 1; } - let elapsed = start.elapsed(); - log::warn!("Elapsed: {:?}", elapsed); - log::warn!("Tok/s {}", all_tokens.len() as f64 / elapsed.as_secs_f64()); + + // Clean up: reset model state and restore the original kv-cache setting. model.reset(); - Ok(()) + model.cache_mut().set_use_kv_cache(use_kv_cache); + Ok(all_logits_ndarray) } diff --git a/crates/ratchet-models/src/gpt2/mod.rs b/crates/ratchet-models/src/gpt2/mod.rs index da60582c..2a4edae6 100644 --- a/crates/ratchet-models/src/gpt2/mod.rs +++ b/crates/ratchet-models/src/gpt2/mod.rs @@ -1,5 +1,5 @@ mod attn; -// mod generate; +mod generate; mod linear; mod mlp; mod model; @@ -10,5 +10,4 @@ pub use model::LayerNormPosition; pub use model::PositionalEncoding; pub use model::GPT2; -// #[cfg(target_arch = "wasm32")] -// pub use generate::generate; +pub use generate::generate; diff --git a/crates/ratchet-models/src/gpt2/model.rs b/crates/ratchet-models/src/gpt2/model.rs index e3f12af7..fb81853d 100644 --- a/crates/ratchet-models/src/gpt2/model.rs +++ b/crates/ratchet-models/src/gpt2/model.rs @@ -217,7 +217,7 @@ impl Module for GPT2 { impl GPT2 { const MAX_CACHE: usize = 4096; - pub async fn new(cfg: &Config, vb: VarBuilder<'_>) -> anyhow::Result { + pub async fn new(cfg: &Config, vb: VarBuilder<'_>, use_kv_cache: bool) -> anyhow::Result { let vb_m = vb.pp("model"); let wte = embedding(cfg.vocab_size, cfg.n_embd, vb_m.pp("wte")).await?; @@ -246,7 +246,7 @@ impl GPT2 { let ln_post = layer_norm(cfg.n_embd, Default::default(), vb_m.pp("norm")).await?; let lm_head = linear_no_bias_gpt2(cfg.n_embd, cfg.vocab_size, vb.pp("lm_head")).await?; - let cache_shape = shape![1, n_layers as _, Self::MAX_CACHE, cfg.head_dim() as _]; + let cache_shape = shape![1, cfg.n_head as _, Self::MAX_CACHE, cfg.head_dim() as _]; Ok(Self { wte, @@ -257,13 +257,21 @@ impl GPT2 { lm_head, kv_cache: Rc::new(RefCell::new(KVCache::new::( n_layers as _, - false, + use_kv_cache, cache_shape, vb.device(), ))), device: vb.device().clone(), }) } + + pub fn reset(&mut self) { + self.kv_cache.borrow_mut().reset(); + } + + pub fn cache_mut(&mut self) -> std::cell::RefMut<'_, KVCache> { + (*self.kv_cache).borrow_mut() + } } #[cfg(all(test, not(target_arch = "wasm32"), feature = "pyo3"))] @@ -282,7 +290,11 @@ mod tests { }; use super::GPT2; - use crate::gpt2::model::{Config, GPT2Input, PositionalEncoding}; + use crate::gpt2::{ + generate, + model::{Config, GPT2Input, PositionalEncoding}, + LayerNormPosition, + }; #[test] #[cfg_attr(feature = "ci", ignore)] @@ -308,7 +320,7 @@ mod tests { let varmap = VarMap::new(); let vb = VarBuilder::from_varmap(&varmap, ratchet::DType::F32, &device.clone()); - let model = GPT2::new(&config, vb)?; + let model = GPT2::new(&config, vb, false)?; let params = ParamsAdamW { lr: 1e-4, @@ -377,7 +389,7 @@ mod tests { let varmap = VarMap::new(); let vb = VarBuilder::from_varmap(&varmap, ratchet::DType::F32, &device.clone()); - let model = GPT2::new(&config, vb)?; + let model = GPT2::new(&config, vb, false)?; const BATCH_SIZE: usize = 10; @@ -429,7 +441,7 @@ mod tests { let varmap = VarMap::new(); let vb = VarBuilder::from_varmap(&varmap, DType::F32, &device.clone()); - let model = GPT2::new(&config, vb).unwrap(); + let mut model = GPT2::new(&config, vb, false).unwrap(); let params = ParamsAdamW { lr: 1e-4, @@ -475,6 +487,20 @@ mod tests { println!("{:?} loss: {:?}, norm: {:?}", batch_index, loss_vec[0], "?"); } + + model.reset(); + + generate( + &mut model, + "12,35,07,99,03:134=".chars().map(|c| c as i32).collect(), + |s, _logits| { + println!("{}", s.iter().map(|&c| c as u8 as char).collect::()); + // println!("{:?}", logits); + }, + 24, + ) + .unwrap(); + Ok(()) } @@ -517,7 +543,7 @@ mod tests { let iter = DatasetRandomIter::new(&dataset, false, config.block_size, device.clone()); let batch_iter = Batcher::new_r2(iter).batch_size(BATCH_SIZE); - let model = GPT2::new(&config, vb)?; + let model = GPT2::new(&config, vb, false)?; let params = ParamsAdamW { lr: 0.0001, @@ -556,4 +582,41 @@ mod tests { Ok(()) } + + #[test] + fn generate_from_initialization() -> anyhow::Result<()> { + let _ = env_logger::builder().is_test(true).try_init(); + + let device = Device::request_device(DeviceRequest::GPU).unwrap(); + + let varmap = VarMap::new(); + let vb = VarBuilder::from_varmap(&varmap, ratchet::DType::F32, &device.clone()); + + let config = Config { + vocab_size: 256, + hidden_act: ratchet_nn::Activation::Relu2, + n_embd: 128, + n_layer: 1, + n_head: 1, + block_size: 20, + attention_only: false, + positional_encoding: PositionalEncoding::Learned, + layernorm_position: LayerNormPosition::Pre, + }; + + let mut model = GPT2::new(&config, vb, false)?; + + generate( + &mut model, + "Hello, world".chars().map(|c| c as i32).collect(), + |s, logits| { + println!("{:?}", s); + println!("{:?}", logits); + }, + 24, + ) + .unwrap(); + + Ok(()) + } } diff --git a/crates/ratchet-nn/src/kv_cache.rs b/crates/ratchet-nn/src/kv_cache.rs index cb5a16eb..932cafdb 100644 --- a/crates/ratchet-nn/src/kv_cache.rs +++ b/crates/ratchet-nn/src/kv_cache.rs @@ -24,6 +24,9 @@ pub struct KVCache { use_kv_cache: bool, masks: HashMap, device: Device, + n_layers: usize, + allocated: bool, + shape: Shape, } impl std::ops::Index for KVCache { @@ -42,14 +45,22 @@ impl KVCache { device: &Device, ) -> Self { let mut entries = Vec::with_capacity(n_layers as _); - for _ in 0..n_layers { - entries.push(KVEntry::allocate::(&shape, device)); + // TODO: This is really bad; look at actual patterns for how people do KV caches + let mut allocated = false; + if use_kv_cache { + for _ in 0..n_layers { + entries.push(KVEntry::allocate::(&shape, device)); + } + allocated = true; } KVCache { entries, masks: HashMap::default(), device: device.clone(), + n_layers: n_layers as _, use_kv_cache, + allocated, + shape, } } @@ -69,6 +80,24 @@ impl KVCache { } } + pub fn use_kv_cache(&self) -> bool { + self.use_kv_cache + } + + pub fn set_use_kv_cache(&mut self, use_kv_cache: bool) { + self.use_kv_cache = use_kv_cache; + if !use_kv_cache && self.allocated { + self.entries.clear(); + self.allocated = false; + } else if use_kv_cache && !self.allocated { + for _ in 0..self.n_layers { + self.entries + .push(KVEntry::allocate::(&self.shape, &self.device)); + } + self.allocated = true; + } + } + pub fn mask(&mut self, t: usize) -> anyhow::Result { if let Some(mask) = self.masks.get(&t) { log::debug!("Using existing mask for {:?}", t); From 8c8e2532fad909c2d0b44b4574379fa291861f3c Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Mon, 17 Feb 2025 22:23:49 -0700 Subject: [PATCH 010/146] Generate batches/toy tasks on frontend --- crates/ratchet-web-train/src/model.rs | 215 ++++++------------ examples/ratchet-train-toy/src/tasks.ts | 186 +++++++++++++++ examples/ratchet-train-toy/src/trainWorker.ts | 20 +- 3 files changed, 275 insertions(+), 146 deletions(-) create mode 100644 examples/ratchet-train-toy/src/tasks.ts diff --git a/crates/ratchet-web-train/src/model.rs b/crates/ratchet-web-train/src/model.rs index 8b6a43be..c6e56ff7 100644 --- a/crates/ratchet-web-train/src/model.rs +++ b/crates/ratchet-web-train/src/model.rs @@ -1,6 +1,6 @@ use anyhow::Result; use async_trait::async_trait; -use ratchet::{DType, Device, DeviceRequest, GradStore, Tensor, Var}; +use ratchet::{shape, DType, Device, DeviceRequest, GradStore, Tensor, Var}; use ratchet_datasets::batcher::IterResult2; use ratchet_datasets::{ nlp::{ @@ -330,7 +330,6 @@ pub struct Trainer { optimizer: Box + Send + Sync>, device: Device, config: TrainerConfig, - batcher: BatcherType<'static>, } #[wasm_bindgen] @@ -380,7 +379,7 @@ impl Trainer { }, }; // Initialize the GPT2 model. - let model = GPT2::new(&gpt2_config, vb) + let model = GPT2::new(&gpt2_config, vb, false) .await .map_err(|e| e.to_string())?; @@ -427,135 +426,66 @@ impl Trainer { _ => Box::new(NoopScheduler::new(base_optimizer)), // Default to no scheduler }; - // Based on the config.dataset value, choose the dataset iterator and wrap it in a Batcher. - // Supported options (case-insensitive): "two_sum" (default), "zeros", "tinystories", "sort", "add", "count", "slapjack", "mod_add" - let batcher = match cfg.dataset.to_lowercase().as_str() { - "zeros" => { - let task = ZerosTask::new(cfg.block_size); - let dataset_iter = ToyTaskIter::new(task, device.clone()); - BatcherType::ToyZeros(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) - } - "sort" => { - let task = SortTask::new(20, cfg.seed); - let dataset_iter = ToyTaskIter::new(task, device.clone()); - BatcherType::ToySort(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) - } - "add" => { - let task = AddTask::new(1000, cfg.seed); - let dataset_iter = ToyTaskIter::new(task, device.clone()); - BatcherType::ToyAdd(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) - } - "count" => { - let task = CountTask::new(10, 'd', cfg.seed); - let dataset_iter = ToyTaskIter::new(task, device.clone()); - BatcherType::ToyCount(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) - } - "slapjack" => { - let task = SlapjackTask::new(48, cfg.seed); - let dataset_iter = ToyTaskIter::new(task, device.clone()); - BatcherType::ToySlapjack(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) - } - "mod_add" => { - let task = ModAddTask::new(113, cfg.seed); - let dataset_iter = ToyTaskIter::new(task, device.clone()); - BatcherType::ToyModAdd(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) - } - // "tinystories" => { - // let dataset = TinyStoriesDataset::new(); - // let dataset_iter = TinyStoriesDatasetRandomIter::new(dataset, device.clone()); - // BatcherEnum::TinyStories(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) - // } - // Default (including "two_sum" and unrecognized values): use the TwoSum task. - _ => { - let task = TwoSumTask::new(5, 5, cfg.seed); - let dataset_iter = ToyTaskIter::new(task, device.clone()); - BatcherType::ToyTwoSum(Batcher::new_r2(dataset_iter).batch_size(cfg.batch_size)) - } - }; - Ok(Trainer { model, optimizer, device, config: cfg, - batcher, }) } - /// Asynchronously retrieve the next batch as a BatchHandle. - /// The returned BatchHandle wraps a Batch consisting of (input, target) tensors, - /// which reside on the device. + /// Train on a single batch of data provided directly from JavaScript #[wasm_bindgen] - pub async fn next_batch(&mut self) -> Result { - // Pull the next (input, target) tuple from the dataset iterator. - let (input, target) = match &mut self.batcher { - BatcherType::ToyTwoSum(batcher) => batcher - .next() - .ok_or_else(|| { - JsValue::from_str("No more data available in the ToyTwoSum dataset") - })? - .map_err(|e| e.to_string())?, - BatcherType::ToyZeros(batcher) => batcher - .next() - .ok_or_else(|| JsValue::from_str("No more data available in the ToyZeros dataset"))? - .map_err(|e| e.to_string())?, - BatcherType::ToySort(batcher) => batcher - .next() - .ok_or_else(|| JsValue::from_str("No more data available in the ToySort dataset"))? - .map_err(|e| e.to_string())?, - BatcherType::ToyAdd(batcher) => batcher - .next() - .ok_or_else(|| JsValue::from_str("No more data available in the ToyAdd dataset"))? - .map_err(|e| e.to_string())?, - BatcherType::ToyCount(batcher) => batcher - .next() - .ok_or_else(|| JsValue::from_str("No more data available in the ToyCount dataset"))? - .map_err(|e| e.to_string())?, - BatcherType::ToySlapjack(batcher) => batcher - .next() - .ok_or_else(|| { - JsValue::from_str("No more data available in the ToySlapjack dataset") - })? - .map_err(|e| e.to_string())?, - BatcherType::ToyModAdd(batcher) => batcher - .next() - .ok_or_else(|| { - JsValue::from_str("No more data available in the ToyModAdd dataset") - })? - .map_err(|e| e.to_string())?, - BatcherType::TinyStories(batcher) => batcher - .next() - .ok_or_else(|| { - JsValue::from_str("No more data available in the TinyStories dataset") - })? - .map_err(|e| e.to_string())?, - }; - Ok(BatchHandle { - inner: Batch { input, target }, - }) - } + pub async fn train_on_batch( + &mut self, + input: JsValue, + target: JsValue, + ) -> Result { + // Convert input and target from JS arrays to Vec> + let input: Vec> = + serde_wasm_bindgen::from_value(input).map_err(|e| JsValue::from(e.to_string()))?; + let target: Vec> = + serde_wasm_bindgen::from_value(target).map_err(|e| JsValue::from(e.to_string()))?; + + // Validate batch dimensions + if input.is_empty() || target.is_empty() { + return Err("Empty batch provided".into()); + } + let batch_size = input.len(); + let seq_len = input[0].len(); + if batch_size != target.len() + || input.iter().any(|x| x.len() != seq_len) + || target.iter().any(|x| x.len() != seq_len) + { + return Err("Inconsistent batch dimensions".into()); + } - /// Asynchronously train on the provided batch. - /// Here we assume that `batch.input` and `batch.target` are already on the correct device. - /// They are passed directly into the model; loss, backpropagation, and the optimizer step - /// are performed, and the scalar loss value is returned. - #[wasm_bindgen] - pub async fn train_step(&mut self, batch_handle: BatchHandle) -> Result { - // Extract the batch from the handle. - let batch = batch_handle.inner; + // Flatten the vectors and create tensors + let input_flat: Vec = input.into_iter().flatten().collect(); + let target_flat: Vec = target.into_iter().flatten().collect(); + + // Create tensors and move to device + let input_tensor = + Tensor::from_data(input_flat, shape![batch_size, seq_len], self.device.clone()); + + let target_tensor = Tensor::from_data( + target_flat, + shape![batch_size, seq_len], + self.device.clone(), + ); // Forward pass: compute logits from the model. let (logits, attn_masks) = self .model .schedule(GPT2Input { - x: batch.input, + x: input_tensor, index_pos: 0, }) .map_err(|e| e.to_string())?; // Flatten the logits and targets. let logits_flat = logits.flatten_to(1).map_err(|e| e.to_string())?; - let target_flat = batch.target.flatten_to(1).map_err(|e| e.to_string())?; + let target_flat = target_tensor.flatten_to(1).map_err(|e| e.to_string())?; // Compute the cross-entropy loss. let loss = cross_entropy(logits_flat, target_flat).map_err(|e| e.to_string())?; @@ -652,35 +582,36 @@ mod tests { wasm_bindgen_test::wasm_bindgen_test_configure!(run_in_browser); - #[wasm_bindgen_test] - async fn train_browser() -> Result<(), JsValue> { - log_init(); - let json_config = r#"{ - "vocab_size": 1024, - "n_embd": 768, - "n_layer": 6, - "n_head": 6, - "block_size": 24, - "batch_size": 1, - "dataset": "two_sum", - "optimizer": { - "lr": 1e-3 - } - }"#; - // Parse the JSON string into a TrainerConfig first to validate it - let config: TrainerConfig = - serde_json::from_str(json_config).map_err(|e| JsValue::from(e.to_string()))?; - // Convert to JsValue - let config_js = - serde_wasm_bindgen::to_value(&config).map_err(|e| JsValue::from(e.to_string()))?; - - let mut trainer = Trainer::new(config_js).await.unwrap(); - for i in 0..10 { - let batch = trainer.next_batch().await.unwrap(); - let loss = trainer.train_step(batch).await.unwrap(); - log::error!("step {}: loss: {:?}", i, loss); - } - // log::error!("config_js: {:?}", config_js); - Ok(()) - } + // #[wasm_bindgen_test] + // async fn train_browser() -> Result<(), JsValue> { + // log_init(); + // let json_config = r#"{ + // "vocab_size": 1024, + // "n_embd": 768, + // "n_layer": 6, + // "n_head": 6, + // "block_size": 24, + // "batch_size": 1, + // "dataset": "two_sum", + // "optimizer": { + // "lr": 1e-3 + // } + // }"#; + // // Parse the JSON string into a TrainerConfig first to validate it + // let config: TrainerConfig = + // serde_json::from_str(json_config).map_err(|e| JsValue::from(e.to_string()))?; + // // Convert to JsValue + // let config_js = + // serde_wasm_bindgen::to_value(&config).map_err(|e| JsValue::from(e.to_string()))?; + + // let mut trainer = Trainer::new(config_js).await.unwrap(); + // for i in 0..10 { + // let input = vec![vec![1, 2, 3, 4]]; + // let target = vec![vec![5, 6, 7, 8]]; + // let loss = trainer.train_on_batch(input, target).await.unwrap(); + // log::error!("step {}: loss: {:?}", i, loss); + // } + // // log::error!("config_js: {:?}", config_js); + // Ok(()) + // } } diff --git a/examples/ratchet-train-toy/src/tasks.ts b/examples/ratchet-train-toy/src/tasks.ts new file mode 100644 index 00000000..cace7811 --- /dev/null +++ b/examples/ratchet-train-toy/src/tasks.ts @@ -0,0 +1,186 @@ +// Type for task generation functions +export type TaskGenerator = ( + maxNum: number, + seqLen: number, + batchSize: number +) => [number[][], number[][]]; + +// Helper function to convert a sequence to tokens +function sequenceToTokens(sequence: string): number[] { + return sequence.split('').map((c) => c.charCodeAt(0)); +} + +// Helper function to pad a number to 2 digits +function pad2(num: number): string { + return num.toString().padStart(2, '0'); +} + +// Helper function to pad a number to 3 digits +function pad3(num: number): string { + return num.toString().padStart(3, '0'); +} + +export function generateTwoSumTask( + maxNum: number, + seqLen: number, + batchSize: number +): [number[][], number[][]] { + const input: number[][] = []; + const target: number[][] = []; + + for (let b = 0; b < batchSize; b++) { + const nums = Array.from({ length: seqLen }, () => Math.floor(Math.random() * maxNum)); + const i = Math.floor(Math.random() * seqLen); + const j = Math.floor(Math.random() * seqLen); + const sum = nums[i] + nums[j]; + + const sequence = `${nums.map((n) => pad2(n)).join(',')}:${pad3(sum)}=${pad2(nums[i])},${pad2(nums[j])}`; + const tokens = sequenceToTokens(sequence); + + input.push(tokens.slice(0, -1)); + target.push(tokens.slice(1)); + } + + return [input, target]; +} + +export function generateSortTask( + maxNum: number, + seqLen: number, + batchSize: number +): [number[][], number[][]] { + const input: number[][] = []; + const target: number[][] = []; + + for (let b = 0; b < batchSize; b++) { + const nums = Array.from({ length: seqLen }, () => Math.floor(Math.random() * maxNum)); + const sorted = [...nums].sort((a, b) => a - b); + + const sequence = `${nums.map((n) => pad2(n)).join(',')}:${sorted.map((n) => pad2(n)).join(',')}`; + const tokens = sequenceToTokens(sequence); + + input.push(tokens.slice(0, -1)); + target.push(tokens.slice(1)); + } + + return [input, target]; +} + +export function generateAddTask( + maxNum: number, + seqLen: number, + batchSize: number +): [number[][], number[][]] { + const input: number[][] = []; + const target: number[][] = []; + + for (let b = 0; b < batchSize; b++) { + const num1 = Math.floor(Math.random() * maxNum); + const num2 = Math.floor(Math.random() * maxNum); + const sum = num1 + num2; + + const sequence = `${pad2(num1)}+${pad2(num2)}=${pad3(sum)}`; + const tokens = sequenceToTokens(sequence); + + input.push(tokens.slice(0, -1)); + target.push(tokens.slice(1)); + } + + return [input, target]; +} + +export function generateModAddTask( + maxNum: number, + seqLen: number, + batchSize: number +): [number[][], number[][]] { + const input: number[][] = []; + const target: number[][] = []; + + for (let b = 0; b < batchSize; b++) { + const num1 = Math.floor(Math.random() * maxNum); + const num2 = Math.floor(Math.random() * maxNum); + const sum = (num1 + num2) % maxNum; + + const sequence = `${pad2(num1)}+${pad2(num2)}%${pad2(maxNum)}=${pad2(sum)}`; + const tokens = sequenceToTokens(sequence); + + input.push(tokens.slice(0, -1)); + target.push(tokens.slice(1)); + } + + return [input, target]; +} + +export function generateCountTask( + maxNum: number, + seqLen: number, + batchSize: number +): [number[][], number[][]] { + const input: number[][] = []; + const target: number[][] = []; + + for (let b = 0; b < batchSize; b++) { + const start = Math.floor(Math.random() * (maxNum - seqLen)); + const sequence = Array.from({ length: seqLen }, (_, i) => pad2(start + i)).join(','); + const tokens = sequenceToTokens(sequence); + + input.push(tokens.slice(0, -1)); + target.push(tokens.slice(1)); + } + + return [input, target]; +} + +export function generateSlapjackTask( + maxNum: number, + seqLen: number, + batchSize: number +): [number[][], number[][]] { + const input: number[][] = []; + const target: number[][] = []; + + for (let b = 0; b < batchSize; b++) { + const nums = Array.from({ length: seqLen }, () => Math.floor(Math.random() * maxNum)); + const jackPosition = Math.floor(Math.random() * seqLen); + nums[jackPosition] = maxNum - 1; // Use max number as "jack" + + const sequence = `${nums.map((n) => pad2(n)).join(',')}:${pad2(jackPosition)}`; + const tokens = sequenceToTokens(sequence); + + input.push(tokens.slice(0, -1)); + target.push(tokens.slice(1)); + } + + return [input, target]; +} + +export function generateZerosTask( + _maxNum: number, + seqLen: number, + batchSize: number +): [number[][], number[][]] { + const input: number[][] = []; + const target: number[][] = []; + + for (let b = 0; b < batchSize; b++) { + const sequence = Array(seqLen).fill('00').join(','); + const tokens = sequenceToTokens(sequence); + + input.push(tokens.slice(0, -1)); + target.push(tokens.slice(1)); + } + + return [input, target]; +} + +// Map of task names to their generator functions +export const taskGenerators: Record = { + two_sum: generateTwoSumTask, + sort: generateSortTask, + add: generateAddTask, + mod_add: generateModAddTask, + count: generateCountTask, + slapjack: generateSlapjackTask, + zeros: generateZerosTask +}; diff --git a/examples/ratchet-train-toy/src/trainWorker.ts b/examples/ratchet-train-toy/src/trainWorker.ts index babcadb2..13233669 100644 --- a/examples/ratchet-train-toy/src/trainWorker.ts +++ b/examples/ratchet-train-toy/src/trainWorker.ts @@ -1,4 +1,5 @@ import { Trainer } from '@ratchet-ml/ratchet-web-train'; +import { taskGenerators } from './tasks'; let trainer: Trainer; let sessionCounter = 0; @@ -47,14 +48,22 @@ async function initializeTrainer(config: TrainerConfig) { self.postMessage({ type: 'modelReady' }); currentSession = sessionCounter++; trainingSessions[currentSession] = true; - trainingLoop(currentSession); + trainingLoop(currentSession, config); } -async function trainingLoop(sessionId: number) { +async function trainingLoop(sessionId: number, config: TrainerConfig) { if (!trainer) { console.error('Trainer not initialized'); return; } + + // Get the appropriate task generator + const taskGenerator = taskGenerators[config.dataset]; + if (!taskGenerator) { + console.error(`Unknown dataset type: ${config.dataset}`); + return; + } + while (trainingSessions[sessionId]) { // Skip if this isn't the current session anymore if (sessionId !== currentSession) { @@ -62,8 +71,11 @@ async function trainingLoop(sessionId: number) { } try { - const batch = await trainer.next_batch(); - const result: Map = await trainer.train_step(batch); + // Generate a new batch using the selected task generator + const [input, target] = taskGenerator(100, 5, 1); // maxNum, seqLen, batchSize + + // Train on the batch + const result = await trainer.train_on_batch(input, target); const attn_masks = result.get('attn_masks') as Map; const usage_bytes = trainer.usage_bytes(); From 1caa0abc998b8a6b7ad0a1adac867f3f6531fd7d Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Mon, 17 Feb 2025 22:24:20 -0700 Subject: [PATCH 011/146] Not clear that this is needed --- .../src/gpu/buffer_allocator/lazy_graph_executor.rs | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/crates/ratchet-core/src/gpu/buffer_allocator/lazy_graph_executor.rs b/crates/ratchet-core/src/gpu/buffer_allocator/lazy_graph_executor.rs index b5660a13..7b328b94 100644 --- a/crates/ratchet-core/src/gpu/buffer_allocator/lazy_graph_executor.rs +++ b/crates/ratchet-core/src/gpu/buffer_allocator/lazy_graph_executor.rs @@ -559,9 +559,9 @@ impl LazyGraphExecutor { return Ok(()); } - // On a cache miss: Clear cache because currently I don't know how to make sure - // allocations are compatible between runs. - self.cache.clear(); + // // On a cache miss: Clear cache because currently I don't know how to make sure + // // allocations are compatible between runs. + // self.cache.clear(); } #[cfg(feature = "plotting")] From 0fc5191b12255f3cf77a4253b397fc19755ab09b Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Mon, 17 Feb 2025 22:24:36 -0700 Subject: [PATCH 012/146] Update pnpm-lock.yaml --- pnpm-lock.yaml | 2288 ++---------------------------------------------- 1 file changed, 63 insertions(+), 2225 deletions(-) diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml index 3f4932cc..acae9285 100644 --- a/pnpm-lock.yaml +++ b/pnpm-lock.yaml @@ -4,6 +4,9 @@ settings: autoInstallPeers: true excludeLinksFromLockfile: false +onlyBuiltDependencies: + - esbuild + importers: .: @@ -67,76 +70,6 @@ importers: specifier: ^5.3.3 version: 5.3.3 - examples/ratchet-train-toy: - 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Do not use it. 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dev: true - /zod-package-json@1.0.3: resolution: {integrity: sha512-Mb6GzuRyUEl8X+6V6xzHbd4XV0au/4gOYrYP+CAfHL32uPmGswES+v2YqonZiW1NZWVA3jkssCKSU2knonm/aQ==} engines: {node: '>=20'} From d783088a393dd262ad5a350c78aa3a29d262b024 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Mon, 17 Feb 2025 22:29:45 -0700 Subject: [PATCH 013/146] Remove more rust batch code --- crates/ratchet-web-train/src/model.rs | 100 -------------------------- 1 file changed, 100 deletions(-) diff --git a/crates/ratchet-web-train/src/model.rs b/crates/ratchet-web-train/src/model.rs index c6e56ff7..058150b7 100644 --- a/crates/ratchet-web-train/src/model.rs +++ b/crates/ratchet-web-train/src/model.rs @@ -175,106 +175,6 @@ fn string_to_activation(s: &str) -> Activation { } } -// ------------------------------------------------------------------- -// Batch and BatchHandle definitions. -// The inner Batch holds the (input, target) tensors on the current device. -// ------------------------------------------------------------------- -pub struct Batch { - pub input: Tensor, - pub target: Tensor, -} - -#[wasm_bindgen(js_name = "Batch")] -pub struct BatchHandle { - inner: Batch, -} - -#[wasm_bindgen] -impl BatchHandle { - /// Asynchronously converts the underlying batch data into a JS object. - /// This operation transfers the tensors to the CPU and then converts them into Vec. - #[wasm_bindgen] - pub async fn to_js(&self) -> Result { - // Transfer the input and target tensors to CPU. - let input_cpu = self - .inner - .input - .to(&Device::CPU) - .await - .map_err(|e| e.to_string())?; - let target_cpu = self - .inner - .target - .to(&Device::CPU) - .await - .map_err(|e| e.to_string())?; - // Convert the tensors to Vec. - let input_vec = input_cpu.to_vec::().map_err(|e| e.to_string())?; - let target_vec = target_cpu.to_vec::().map_err(|e| e.to_string())?; - // Create a JS-friendly object. - let batch_obj = serde_json::json!({ - "input": input_vec, - "target": target_vec, - }); - serde_wasm_bindgen::to_value(&batch_obj).map_err(|e| e.to_string().into()) - } -} - -// Updated to: - -enum BatcherType<'a> { - ToyTwoSum( - Batcher< - IterResult2< - ratchet_datasets::nlp::toy::ToyTaskIter, - >, - >, - ), - ToyZeros( - Batcher< - IterResult2< - ratchet_datasets::nlp::toy::ToyTaskIter, - >, - >, - ), - ToySort( - Batcher< - IterResult2< - ratchet_datasets::nlp::toy::ToyTaskIter, - >, - >, - ), - ToyAdd( - Batcher< - IterResult2< - ratchet_datasets::nlp::toy::ToyTaskIter, - >, - >, - ), - ToyCount( - Batcher< - IterResult2< - ratchet_datasets::nlp::toy::ToyTaskIter, - >, - >, - ), - ToySlapjack( - Batcher< - IterResult2< - ratchet_datasets::nlp::toy::ToyTaskIter, - >, - >, - ), - ToyModAdd( - Batcher< - IterResult2< - ratchet_datasets::nlp::toy::ToyTaskIter, - >, - >, - ), - TinyStories(Batcher>>), -} - /// An enum for optimizer configurations #[derive(Debug, Clone)] pub enum OptimizerConfigEnum { From 0cb319c2631dee52d2455a067a0b07a7bc544e34 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Mon, 17 Feb 2025 22:58:13 -0700 Subject: [PATCH 014/146] Add web-visible generation api --- crates/ratchet-web-train/src/model.rs | 59 +++++++++++++++++++++++++++ 1 file changed, 59 insertions(+) diff --git a/crates/ratchet-web-train/src/model.rs b/crates/ratchet-web-train/src/model.rs index 058150b7..d93b554d 100644 --- a/crates/ratchet-web-train/src/model.rs +++ b/crates/ratchet-web-train/src/model.rs @@ -1,5 +1,6 @@ use anyhow::Result; use async_trait::async_trait; +use js_sys::Function; use ratchet::{shape, DType, Device, DeviceRequest, GradStore, Tensor, Var}; use ratchet_datasets::batcher::IterResult2; use ratchet_datasets::{ @@ -14,6 +15,7 @@ use ratchet_datasets::{ }, Batcher, }; +use ratchet_models::gpt2::generate; use ratchet_models::gpt2::{Config, GPT2Input, PositionalEncoding}; use ratchet_models::gpt2::{LayerNormPosition, GPT2}; use ratchet_nn::{ @@ -430,6 +432,63 @@ impl Trainer { pub fn usage_bytes(&self) -> u64 { self.device.try_gpu().unwrap().usage_bytes() } + + /// Autoregressive generation with streaming callback. + /// `prompt` is a JS array of i32 tokens. + /// `max_tokens` is how many tokens to generate. + /// `callback` is invoked once per model call with: + /// callback(tokens_to_feed, { shape: [...], data: [...] }) + #[wasm_bindgen] + pub async fn generate( + &mut self, + prompt: JsValue, + max_tokens: usize, + callback: Function, + ) -> Result<(), JsValue> { + // Convert prompt from JsValue -> Vec + let prompt_vec: Vec = + serde_wasm_bindgen::from_value(prompt).map_err(|e| JsValue::from(e.to_string()))?; + + // Call existing GPT-2 generate + generate( + &mut self.model, + prompt_vec, + // This closure is invoked for each new pass with the tokens we just fed + // and an ndarray of logits. We serialize them to JS inside. + |tokens, logits_nd| { + // Convert the tokens to JS + let tokens_js = serde_wasm_bindgen::to_value(&tokens).unwrap_or(JsValue::NULL); + + // Turn the [1, seq_len, vocab_size] logits into a plain object + let shape = vec![ + logits_nd.shape()[0], + logits_nd.shape()[1], + logits_nd.shape()[2], + ]; + let data: Vec = logits_nd.into_iter().collect(); + + let logits_obj = js_sys::Object::new(); + let _ = js_sys::Reflect::set( + &logits_obj, + &JsValue::from_str("shape"), + &serde_wasm_bindgen::to_value(&shape).unwrap_or(JsValue::NULL), + ); + let _ = js_sys::Reflect::set( + &logits_obj, + &JsValue::from_str("data"), + &serde_wasm_bindgen::to_value(&data).unwrap_or(JsValue::NULL), + ); + + // Finally, call the JS callback with (tokens, logitsObj) + let _ = callback.call2(&JsValue::NULL, &tokens_js, &logits_obj); + }, + max_tokens, + ) + .await + .map_err(|e| JsValue::from(e.to_string()))?; + + Ok(()) + } } /// A scheduler that does nothing, just passes through to the underlying optimizer. From 0295c2b1c7d65407c56a5de9d6f459b3327e9d68 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:17:01 -0700 Subject: [PATCH 015/146] Cache non mark_step forward passes --- .../src/gpu/buffer_allocator/lazy_graph_executor.rs | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/crates/ratchet-core/src/gpu/buffer_allocator/lazy_graph_executor.rs b/crates/ratchet-core/src/gpu/buffer_allocator/lazy_graph_executor.rs index 7b328b94..03603bab 100644 --- a/crates/ratchet-core/src/gpu/buffer_allocator/lazy_graph_executor.rs +++ b/crates/ratchet-core/src/gpu/buffer_allocator/lazy_graph_executor.rs @@ -153,7 +153,7 @@ impl LazyGraphExecutor { tensors.into_iter().map(|t| (t.id(), t.clone())).collect(), None, gpu_device, - false, + true, ) } From 033b065ffa5b8255d81e79235953e0f12bb7230f Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:17:25 -0700 Subject: [PATCH 016/146] Provisionally mark 256 as the end of sequence token --- crates/ratchet-models/src/gpt2/generate.rs | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/crates/ratchet-models/src/gpt2/generate.rs b/crates/ratchet-models/src/gpt2/generate.rs index 5c3e1fbd..43b71898 100644 --- a/crates/ratchet-models/src/gpt2/generate.rs +++ b/crates/ratchet-models/src/gpt2/generate.rs @@ -27,7 +27,7 @@ pub async fn generate( // Count only the tokens that are generated (not in the original prompt) let mut generated_count = 0; - while generated_count < max_tokens { + while generated_count < max_tokens && all_tokens[all_tokens.len() - 1] != 256 { // For the first pass, feed the entire prompt. // For subsequent passes, feed only the latest generated token. let tokens_to_feed = if generated_count == 0 { From e3140dd0d520d15bf7b06365d24997cf8f9f3bb9 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:19:51 -0700 Subject: [PATCH 017/146] Return per-token losses for visualization --- crates/ratchet-nn/src/loss.rs | 3 +-- crates/ratchet-web-train/src/model.rs | 33 +++++++++++++++++++-------- 2 files changed, 24 insertions(+), 12 deletions(-) diff --git a/crates/ratchet-nn/src/loss.rs b/crates/ratchet-nn/src/loss.rs index ea6e66d9..f86a27a9 100644 --- a/crates/ratchet-nn/src/loss.rs +++ b/crates/ratchet-nn/src/loss.rs @@ -14,7 +14,6 @@ pub fn nll(inp: Tensor, target: Tensor) -> anyhow::Result { dims => anyhow::bail!("the target tensor should have two dimensions ({dims:?})"), } inp.gather(target.clone().unsqueeze(1)?, 1)? - .sum_all()? .affine(-1f32 / b_sz as f32, 0.) } @@ -31,7 +30,7 @@ pub fn cross_entropy(inp: Tensor, target: Tensor) -> anyhow::Result { anyhow::bail!("cross_entropy expects an input tensor of rank 2") } let inp = log_softmax(inp, 1)?; - nll(inp, target) + nll(inp, target)?.sum_all() } #[cfg(all(test, feature = "pyo3"))] diff --git a/crates/ratchet-web-train/src/model.rs b/crates/ratchet-web-train/src/model.rs index d93b554d..e0199212 100644 --- a/crates/ratchet-web-train/src/model.rs +++ b/crates/ratchet-web-train/src/model.rs @@ -19,8 +19,9 @@ use ratchet_models::gpt2::generate; use ratchet_models::gpt2::{Config, GPT2Input, PositionalEncoding}; use ratchet_models::gpt2::{LayerNormPosition, GPT2}; use ratchet_nn::{ - clip_grad_norm, cross_entropy, Activation, AdamW, ConstantLR, CosineAnnealingLR, LRScheduler, - LRSchedulerCore, LinearLR, Module, Optimizer, ParamsAdamW, VarBuilder, VarMap, SGD, + clip_grad_norm, cross_entropy, log_softmax, nll, Activation, AdamW, ConstantLR, + CosineAnnealingLR, LRScheduler, LRSchedulerCore, LinearLR, Module, Optimizer, ParamsAdamW, + VarBuilder, VarMap, SGD, }; use serde::{Deserialize, Serialize}; use std::iter::Iterator; @@ -385,15 +386,15 @@ impl Trainer { }) .map_err(|e| e.to_string())?; - // Flatten the logits and targets. - let logits_flat = logits.flatten_to(1).map_err(|e| e.to_string())?; + // Flatten the logits and targets, compute the cross-entropy loss. + let logits_flat = logits.clone().flatten_to(1).map_err(|e| e.to_string())?; let target_flat = target_tensor.flatten_to(1).map_err(|e| e.to_string())?; - - // Compute the cross-entropy loss. - let loss = cross_entropy(logits_flat, target_flat).map_err(|e| e.to_string())?; + let inp = log_softmax(logits_flat, 1).map_err(|e| e.to_string())?; + let loss = nll(inp, target_flat).map_err(|e| e.to_string())?; + let loss_summed = loss.clone().sum_all().map_err(|e| e.to_string())?; // Backpropagate to compute gradients. - let grads = loss.backward().map_err(|e| e.to_string())?; + let grads = loss_summed.backward().map_err(|e| e.to_string())?; // Run an optimizer step (updating model parameters). self.optimizer @@ -415,13 +416,25 @@ impl Trainer { let attn_masks_shape = attn_masks_cpu.shape().to_vec(); let attn_masks_data = attn_masks_cpu.to_vec::().map_err(|e| e.to_string())?; - // Create a JS-friendly object with both loss and attention masks + // Add logits to the result: + let logits_cpu = logits.to(&Device::CPU).await.map_err(|e| e.to_string())?; + let logits_shape = logits_cpu.shape().to_vec(); + let logits_data = logits_cpu.to_vec::().map_err(|e| e.to_string())?; + + // Build a JS-friendly JSON with loss, LR, attn masks, and logits let result = serde_json::json!({ - "loss": loss_vec[0], + "loss": { + "tokens": loss_vec, + "total": loss_vec.iter().sum::(), + }, "learning_rate": self.optimizer.get_lr(), "attn_masks": { "data": attn_masks_data, "shape": attn_masks_shape, + }, + "logits": { + "data": logits_data, + "shape": logits_shape, } }); From 6e2104fffd9dcbe8b9f597882c46980b81aef63d Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:21:05 -0700 Subject: [PATCH 018/146] Allow running generate without streaming --- crates/ratchet-web-train/src/model.rs | 148 ++++++++++++++++++-------- 1 file changed, 102 insertions(+), 46 deletions(-) diff --git a/crates/ratchet-web-train/src/model.rs b/crates/ratchet-web-train/src/model.rs index e0199212..d91a8600 100644 --- a/crates/ratchet-web-train/src/model.rs +++ b/crates/ratchet-web-train/src/model.rs @@ -446,61 +446,117 @@ impl Trainer { self.device.try_gpu().unwrap().usage_bytes() } - /// Autoregressive generation with streaming callback. - /// `prompt` is a JS array of i32 tokens. - /// `max_tokens` is how many tokens to generate. - /// `callback` is invoked once per model call with: - /// callback(tokens_to_feed, { shape: [...], data: [...] }) + /// Autoregressive generation with an optional streaming callback. + /// + /// - `prompt` is a JS array of i32 tokens. + /// - `max_tokens` is how many tokens to generate. + /// - `callback` is optional; if provided, it is invoked once per model call with: + /// `callback(tokens_to_feed, { shape: [...], data: [...] })` + /// - If `callback` is not provided (i.e., `null` or `undefined`), + /// we accumulate the final tokens and logits internally, and return them as a single + /// JS object of the form: + /// ```json + /// { + /// "tokens": [...], + /// "logits": { + /// "shape": [1, total_seq_len, vocab_size], + /// "data": [...] + /// } + /// } + /// ``` #[wasm_bindgen] pub async fn generate( &mut self, prompt: JsValue, max_tokens: usize, - callback: Function, - ) -> Result<(), JsValue> { + callback: Option, + ) -> Result { // Convert prompt from JsValue -> Vec let prompt_vec: Vec = serde_wasm_bindgen::from_value(prompt).map_err(|e| JsValue::from(e.to_string()))?; - // Call existing GPT-2 generate - generate( - &mut self.model, - prompt_vec, - // This closure is invoked for each new pass with the tokens we just fed - // and an ndarray of logits. We serialize them to JS inside. - |tokens, logits_nd| { - // Convert the tokens to JS - let tokens_js = serde_wasm_bindgen::to_value(&tokens).unwrap_or(JsValue::NULL); - - // Turn the [1, seq_len, vocab_size] logits into a plain object - let shape = vec![ - logits_nd.shape()[0], - logits_nd.shape()[1], - logits_nd.shape()[2], - ]; - let data: Vec = logits_nd.into_iter().collect(); - - let logits_obj = js_sys::Object::new(); - let _ = js_sys::Reflect::set( - &logits_obj, - &JsValue::from_str("shape"), - &serde_wasm_bindgen::to_value(&shape).unwrap_or(JsValue::NULL), - ); - let _ = js_sys::Reflect::set( - &logits_obj, - &JsValue::from_str("data"), - &serde_wasm_bindgen::to_value(&data).unwrap_or(JsValue::NULL), - ); - - // Finally, call the JS callback with (tokens, logitsObj) - let _ = callback.call2(&JsValue::NULL, &tokens_js, &logits_obj); - }, - max_tokens, - ) - .await - .map_err(|e| JsValue::from(e.to_string()))?; - - Ok(()) + // If a callback is provided, we do the streaming approach. + if let Some(callback_fn) = callback { + // Call existing GPT-2 generate with a streaming closure: + generate( + &mut self.model, + prompt_vec, + |tokens, logits_nd| { + // Convert the tokens to JS + let tokens_js = serde_wasm_bindgen::to_value(&tokens).unwrap_or(JsValue::NULL); + + // Convert the logits to a {shape, data} object + let shape = vec![ + logits_nd.shape()[0], + logits_nd.shape()[1], + logits_nd.shape()[2], + ]; + let data: Vec = logits_nd.into_iter().collect(); + + let logits_obj = js_sys::Object::new(); + let _ = js_sys::Reflect::set( + &logits_obj, + &JsValue::from_str("shape"), + &serde_wasm_bindgen::to_value(&shape).unwrap_or(JsValue::NULL), + ); + let _ = js_sys::Reflect::set( + &logits_obj, + &JsValue::from_str("data"), + &serde_wasm_bindgen::to_value(&data).unwrap_or(JsValue::NULL), + ); + + // Finally, call the JS callback with (tokens, logitsObj) + let _ = callback_fn.call2(&JsValue::NULL, &tokens_js, &logits_obj); + }, + max_tokens, + ) + .await + .map_err(|e| JsValue::from(e.to_string()))?; + + // Return undefined if we're streaming via callback + Ok(JsValue::UNDEFINED) + } else { + // No callback was provided, so we accumulate only the final tokens/logits and return them. + let mut final_tokens: Vec = Vec::new(); + let mut final_logits_data: Vec = Vec::new(); + let mut final_logits_shape: Vec = Vec::new(); + + let prompt_len = prompt_vec.len(); + + // We capture these as mut so we can overwrite them at each step with the latest pass + generate( + &mut self.model, + prompt_vec, + |tokens, logits_nd| { + // Update tokens + final_tokens.extend_from_slice(&tokens); + + // Convert the logits into shape/data only for the final pass + final_logits_shape.extend_from_slice(&[ + logits_nd.shape()[0], + logits_nd.shape()[1], + logits_nd.shape()[2], + ]); + + final_logits_data.extend(logits_nd.into_iter()); + }, + max_tokens, + ) + .await + .map_err(|e| JsValue::from(e.to_string()))?; + + // Build a JSON object with final tokens and final logits + let result = serde_json::json!({ + "tokens": final_tokens[prompt_len..].to_vec(), + "logits": { + "shape": final_logits_shape, + "data": final_logits_data, + }, + }); + + // Convert to JsValue + Ok(serde_wasm_bindgen::to_value(&result).map_err(|e| e.to_string())?) + } } } From 114d27f141d93f17050adfc7c5f236e0b331d89f Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:26:03 -0700 Subject: [PATCH 019/146] Rework task generation to be configurable --- .../ratchet-train-toy/src/routes/+page.svelte | 57 +- examples/ratchet-train-toy/src/tasks.ts | 500 +++++++++++++----- examples/ratchet-train-toy/src/trainWorker.ts | 44 +- 3 files changed, 446 insertions(+), 155 deletions(-) diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte index 056e425b..0e8247e7 100644 --- a/examples/ratchet-train-toy/src/routes/+page.svelte +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -6,6 +6,7 @@ import LogSlider from '$lib/components/LogSlider.svelte'; import TickSlider from '$lib/components/TickSlider.svelte'; import ActivationPicker from '$lib/components/ActivationPicker.svelte'; + import { taskMetadata } from '../tasks'; let loss = 0; let worker: Worker; @@ -52,6 +53,7 @@ // Track last parameter values to detect actual changes let lastParams: Record | null = null; + let lastTaskParams: Record | null = null; // Add reactive statement to restart training when parameters change $: { @@ -82,13 +84,21 @@ if (lastParams === null) { // First time through, just store the parameters lastParams = { ...currentParams }; + lastTaskParams = { ...taskParameters }; } else { // Check if any parameter actually changed const hasChanges = Object.entries(currentParams).some( ([key, value]) => lastParams![key] !== value ); - if (worker && isTraining && hasChanges) { + // Check which task parameters changed + const hasTaskChanges = + Object.keys(lastTaskParams!).length > 0 && + Object.entries(taskParameters).some(([key, value]) => lastTaskParams![key] !== value); + + lastTaskParams = { ...taskParameters }; + + if (worker && isTraining && (hasChanges || hasTaskChanges)) { // Update last params before restarting lastParams = { ...currentParams }; // Restart training with new parameters @@ -117,6 +127,21 @@ let scheduler_steps = 1000; let scheduler_eta_min = 1e-4; + // Add task parameter state + let taskParameters: Record = {}; + + // Initialize task parameters with defaults + $: { + if (dataset && taskMetadata[dataset]) { + const metadata = taskMetadata[dataset]; + for (const [key, param] of Object.entries(metadata.parameters)) { + if (!(key in taskParameters)) { + taskParameters[key] = param.default; + } + } + } + } + function initializeAttentionCanvases(numLayers: number, numHeads: number) { if (typeof document === 'undefined') return; // Check if we're in the browser @@ -252,6 +277,7 @@ block_size: 24, batch_size, dataset, + task_parameters: taskParameters, activation, attention_only: attentionOnly, positional_encoding, @@ -389,7 +415,7 @@ const stepsPerSecond = 1000 / (currentTime - lastStepTime); lastStepTime = currentTime; - loss = data.loss; + loss = data.loss.total; const currentLossDataset = chart.data.datasets[chart.data.datasets.length - 1]; const currentSpeedDataset = speedChart.data.datasets[speedChart.data.datasets.length - 1]; const currentMemoryDataset = @@ -752,13 +778,9 @@ bind:value={dataset} class="w-full p-2 pr-12 border focus:outline-none focus:border-gray-400 border-gray-400 bg-white appearance-none" > - - - - - - - + {#each Object.entries(taskMetadata) as [key, meta]} + + {/each}
- + {#if dataset && taskMetadata[dataset]} +

{taskMetadata[dataset].description}

+
+ {#each Object.entries(taskMetadata[dataset].parameters) as [key, param]} +
+ +

{param.description}

+
+ {/each} +
+ {/if}
diff --git a/examples/ratchet-train-toy/src/tasks.ts b/examples/ratchet-train-toy/src/tasks.ts index cace7811..034bdb48 100644 --- a/examples/ratchet-train-toy/src/tasks.ts +++ b/examples/ratchet-train-toy/src/tasks.ts @@ -1,87 +1,171 @@ -// Type for task generation functions -export type TaskGenerator = ( - maxNum: number, - seqLen: number, - batchSize: number -) => [number[][], number[][]]; - -// Helper function to convert a sequence to tokens -function sequenceToTokens(sequence: string): number[] { - return sequence.split('').map((c) => c.charCodeAt(0)); +// Task-specific configuration types +interface TrainBatchConfig { + batchSize: number; } -// Helper function to pad a number to 2 digits -function pad2(num: number): string { - return num.toString().padStart(2, '0'); +interface NumberSequenceConfig { + seqLen: number; + maxNum: number; } -// Helper function to pad a number to 3 digits -function pad3(num: number): string { - return num.toString().padStart(3, '0'); +interface AdditionConfig { + maxNum: number; } -export function generateTwoSumTask( - maxNum: number, - seqLen: number, - batchSize: number -): [number[][], number[][]] { - const input: number[][] = []; - const target: number[][] = []; - - for (let b = 0; b < batchSize; b++) { - const nums = Array.from({ length: seqLen }, () => Math.floor(Math.random() * maxNum)); - const i = Math.floor(Math.random() * seqLen); - const j = Math.floor(Math.random() * seqLen); - const sum = nums[i] + nums[j]; - - const sequence = `${nums.map((n) => pad2(n)).join(',')}:${pad3(sum)}=${pad2(nums[i])},${pad2(nums[j])}`; - const tokens = sequenceToTokens(sequence); - - input.push(tokens.slice(0, -1)); - target.push(tokens.slice(1)); - } - - return [input, target]; +interface ModAdditionConfig { + maxNum: number; } -export function generateSortTask( - maxNum: number, - seqLen: number, - batchSize: number -): [number[][], number[][]] { - const input: number[][] = []; - const target: number[][] = []; +interface FixedLengthConfig { + seqLen: number; +} - for (let b = 0; b < batchSize; b++) { - const nums = Array.from({ length: seqLen }, () => Math.floor(Math.random() * maxNum)); - const sorted = [...nums].sort((a, b) => a - b); +// Task metadata for UI configuration +export interface TaskParameter { + name: string; + description: string; + min: number; + max: number; + default: number; +} - const sequence = `${nums.map((n) => pad2(n)).join(',')}:${sorted.map((n) => pad2(n)).join(',')}`; - const tokens = sequenceToTokens(sequence); +export interface TaskMetadata { + name: string; + description: string; + parameters: Record; +} - input.push(tokens.slice(0, -1)); - target.push(tokens.slice(1)); +export const taskMetadata: Record = { + sort: { + name: 'Sorting', + description: 'Learn to sort a sequence of numbers', + parameters: { + seqLen: { + name: 'Sequence Length', + description: 'Length of the sequence to sort', + min: 2, + max: 10, + default: 2 + }, + maxNum: { + name: 'Max Number', + description: 'Maximum value in the sequence', + min: 10, + max: 100, + default: 100 + } + } + }, + add: { + name: 'Addition', + description: 'Learn to add two numbers', + parameters: { + maxNum: { + name: 'Max Number', + description: 'Maximum value for each addend', + min: 10, + max: 100, + default: 100 + } + } + }, + mod_add: { + name: 'Modular Addition', + description: 'Learn to add two numbers with modulo', + parameters: { + maxNum: { + name: 'Modulo', + description: 'The modulo to use', + min: 10, + max: 100, + default: 100 + } + } + }, + // count: { + // name: 'Counting', + // description: 'Learn to count the occurrences of a character in a sequence', + // parameters: { + // seqLen: { + // name: 'Sequence Length', + // description: 'Length of the counting sequence', + // min: 2, + // max: 10, + // default: 5 + // }, + // maxNum: { + // name: 'Max Number', + // description: 'Maximum starting number', + // min: 10, + // max: 100, + // default: 100 + // } + // } + // }, + // slapjack: { + // name: 'Slapjack', + // description: 'Learn to find a specific number in a sequence', + // parameters: { + // seqLen: { + // name: 'Sequence Length', + // description: 'Length of the sequence', + // min: 2, + // max: 10, + // default: 5 + // } + // } + // }, + zeros: { + name: 'Zeros', + description: 'Learn to output zeros (baseline/debug task)', + parameters: { + seqLen: { + name: 'Sequence Length', + description: 'Length of the sequence', + min: 2, + max: 10, + default: 5 + } + } + }, + two_sum: { + name: 'Two Sum', + description: 'Find two numbers in a sequence that sum to a target', + parameters: { + seqLen: { + name: 'Sequence Length', + description: 'Length of the sequence', + min: 2, + max: 10, + default: 5 + }, + maxNum: { + name: 'Max Number', + description: 'Maximum value in the sequence', + min: 10, + max: 100, + default: 100 + } + } } +}; - return [input, target]; -} +// Type for single sequence generation +type SequenceGenerator = ( + config: TaskConfigMap[K] +) => [string, string]; -export function generateAddTask( - maxNum: number, - seqLen: number, - batchSize: number +// Helper function to handle batch processing and tokenization +function generateTrainBatch( + generator: SequenceGenerator, + config: TrainBatchConfig & TaskConfigMap[K] ): [number[][], number[][]] { const input: number[][] = []; const target: number[][] = []; - for (let b = 0; b < batchSize; b++) { - const num1 = Math.floor(Math.random() * maxNum); - const num2 = Math.floor(Math.random() * maxNum); - const sum = num1 + num2; - - const sequence = `${pad2(num1)}+${pad2(num2)}=${pad3(sum)}`; + for (let b = 0; b < config.batchSize; b++) { + const sequence = generator(config).join(''); const tokens = sequenceToTokens(sequence); - input.push(tokens.slice(0, -1)); target.push(tokens.slice(1)); } @@ -89,98 +173,234 @@ export function generateAddTask( return [input, target]; } -export function generateModAddTask( - maxNum: number, - seqLen: number, - batchSize: number -): [number[][], number[][]] { - const input: number[][] = []; - const target: number[][] = []; +function generateEvalExample( + generator: SequenceGenerator, + config: TaskConfigMap[K] +): [number[], number[]] { + const [sequence, completion] = generator(config); + const sequenceTokens = sequenceToTokens(sequence); + const completionTokens = sequenceToTokens(completion); + return [sequenceTokens, completionTokens]; +} - for (let b = 0; b < batchSize; b++) { - const num1 = Math.floor(Math.random() * maxNum); - const num2 = Math.floor(Math.random() * maxNum); - const sum = (num1 + num2) % maxNum; +// Helper function to convert a sequence to tokens +export function sequenceToTokens(sequence: string): number[] { + return sequence.split('').map((c) => c.charCodeAt(0)); +} - const sequence = `${pad2(num1)}+${pad2(num2)}%${pad2(maxNum)}=${pad2(sum)}`; - const tokens = sequenceToTokens(sequence); +export function tokensToString(tokens: number[]): string { + return tokens.map((t) => String.fromCharCode(t)).join(''); +} - input.push(tokens.slice(0, -1)); - target.push(tokens.slice(1)); - } +// Helper function to pad a number to 2 digits +function pad2(num: number): string { + return num.toString().padStart(2, '0'); +} - return [input, target]; +// Helper function to pad a number to 3 digits +function pad3(num: number): string { + return num.toString().padStart(3, '0'); } -export function generateCountTask( - maxNum: number, - seqLen: number, - batchSize: number -): [number[][], number[][]] { - const input: number[][] = []; - const target: number[][] = []; +// Task-specific sequence generators +function twoSumSequence(config: NumberSequenceConfig): [string, string] { + const { maxNum, seqLen } = config; + const nums = Array.from({ length: seqLen }, () => Math.floor(Math.random() * maxNum)); + const i = Math.floor(Math.random() * seqLen); + const j = Math.floor(Math.random() * seqLen); + const sum = nums[i] + nums[j]; + return [ + `${nums.map((n) => pad2(n)).join(',')}:${pad3(sum)}=`, + `${pad2(nums[i])},${pad2(nums[j])}` + ]; +} - for (let b = 0; b < batchSize; b++) { - const start = Math.floor(Math.random() * (maxNum - seqLen)); - const sequence = Array.from({ length: seqLen }, (_, i) => pad2(start + i)).join(','); - const tokens = sequenceToTokens(sequence); +function sortSequence(config: NumberSequenceConfig): [string, string] { + const { maxNum, seqLen } = config; + const nums = Array.from({ length: seqLen }, () => Math.floor(Math.random() * maxNum)); + const sorted = [...nums].sort((a, b) => a - b); + return [`${nums.map((n) => pad2(n)).join(',')}:`, `${sorted.map((n) => pad2(n)).join(',')}`]; +} - input.push(tokens.slice(0, -1)); - target.push(tokens.slice(1)); - } +function addSequence(config: AdditionConfig): [string, string] { + const { maxNum } = config; + const num1 = Math.floor(Math.random() * maxNum); + const num2 = Math.floor(Math.random() * maxNum); + const sum = num1 + num2; + return [`${pad2(num1)}+${pad2(num2)}=`, `${pad3(sum)}`]; +} - return [input, target]; +function modAddSequence(config: ModAdditionConfig): [string, string] { + const { maxNum } = config; + const num1 = Math.floor(Math.random() * maxNum); + const num2 = Math.floor(Math.random() * maxNum); + const sum = (num1 + num2) % maxNum; + return [`${pad2(num1)}+${pad2(num2)}%${pad2(maxNum)}=`, `${pad2(sum)}`]; } -export function generateSlapjackTask( - maxNum: number, - seqLen: number, - batchSize: number -): [number[][], number[][]] { - const input: number[][] = []; - const target: number[][] = []; +// function countSequence(config: NumberSequenceConfig): [string, string] { +// const { maxNum, seqLen } = config; +// const start = Math.floor(Math.random() * (maxNum - seqLen)); +// const sequence = Array.from({ length: seqLen - 1 }, (_, i) => pad2(start + i)).join(','); +// return [sequence, `,${pad2(start + seqLen - 1)}`]; +// } + +// function slapjackSequence(config: FixedLengthConfig): [string, string] { +// const { seqLen } = config; +// const maxNum = 100; // Fixed max number for consistency +// const nums = Array.from({ length: seqLen }, () => Math.floor(Math.random() * maxNum)); +// const jackPosition = Math.floor(Math.random() * seqLen); +// nums[jackPosition] = maxNum - 1; // Use max number as "jack" +// return [ +// `${nums.map((n) => pad2(n)).join(',')}`, +// `:${pad2(jackPosition)}` +// ]; +// } + +function zerosSequence(config: FixedLengthConfig): [string, string] { + const { seqLen } = config; + const sequence = Array(seqLen - 1) + .fill('0') + .join(''); + return ['', sequence]; +} - for (let b = 0; b < batchSize; b++) { - const nums = Array.from({ length: seqLen }, () => Math.floor(Math.random() * maxNum)); - const jackPosition = Math.floor(Math.random() * seqLen); - nums[jackPosition] = maxNum - 1; // Use max number as "jack" +export type TaskConfigMap = { + two_sum: NumberSequenceConfig; + sort: NumberSequenceConfig; + add: AdditionConfig; + mod_add: ModAdditionConfig; + zeros: FixedLengthConfig; +}; - const sequence = `${nums.map((n) => pad2(n)).join(',')}:${pad2(jackPosition)}`; - const tokens = sequenceToTokens(sequence); +// Update TrainBatchGenerator to be generic over task keys +export type TrainBatchGenerator = ( + config: TrainBatchConfig & TaskConfigMap[K] +) => [number[][], number[][]]; - input.push(tokens.slice(0, -1)); - target.push(tokens.slice(1)); +// Map of task names to their generator functions +export const trainBatchGenerators: { + [K in keyof TaskConfigMap]: TrainBatchGenerator; +} = { + two_sum: (config: TrainBatchConfig & NumberSequenceConfig) => { + const { seqLen, maxNum } = config; + return generateTrainBatch((c) => twoSumSequence({ ...c, seqLen, maxNum }), config); + }, + sort: (config: TrainBatchConfig & NumberSequenceConfig) => { + const { seqLen, maxNum } = config; + return generateTrainBatch((c) => sortSequence({ ...c, seqLen, maxNum }), config); + }, + add: (config: TrainBatchConfig & AdditionConfig) => { + const { maxNum } = config; + return generateTrainBatch((c) => addSequence({ ...c, maxNum }), config); + }, + mod_add: (config: TrainBatchConfig & ModAdditionConfig) => { + const { maxNum } = config; + return generateTrainBatch((c) => modAddSequence({ ...c, maxNum }), config); + }, + // count: (config: BaseTaskConfig) => { + // const { seqLen, maxNum } = config as NumberSequenceConfig; + // return generateBatch((c) => countSequence({ ...c, seqLen, maxNum }), config); + // }, + // slapjack: (config: BaseTaskConfig) => { + // const { seqLen } = config as FixedLengthConfig; + // return generateBatch((c) => slapjackSequence({ ...c, seqLen }), config); + // }, + zeros: (config: TrainBatchConfig & FixedLengthConfig) => { + const { seqLen } = config; + return generateTrainBatch((c) => zerosSequence({ ...c, seqLen }), config); } +}; - return [input, target]; -} - -export function generateZerosTask( - _maxNum: number, - seqLen: number, - batchSize: number -): [number[][], number[][]] { - const input: number[][] = []; - const target: number[][] = []; - - for (let b = 0; b < batchSize; b++) { - const sequence = Array(seqLen).fill('00').join(','); - const tokens = sequenceToTokens(sequence); +export type EvalExampleGenerator = ( + config: TaskConfigMap[K] +) => [number[], number[]]; - input.push(tokens.slice(0, -1)); - target.push(tokens.slice(1)); - } +export type EvalMetric = ( + completion: number[], + target: number[], + sequence: number[], + config: TaskConfigMap[K] +) => Array; - return [input, target]; -} +export type EvalConfig = { + metric: EvalMetric; + generator: EvalExampleGenerator; +}; -// Map of task names to their generator functions -export const taskGenerators: Record = { - two_sum: generateTwoSumTask, - sort: generateSortTask, - add: generateAddTask, - mod_add: generateModAddTask, - count: generateCountTask, - slapjack: generateSlapjackTask, - zeros: generateZerosTask +export const evalExampleGenerators: { + [K in keyof TaskConfigMap]: EvalConfig; +} = { + two_sum: (() => { + return { + generator: (config: NumberSequenceConfig) => { + const { seqLen, maxNum } = config as NumberSequenceConfig; + return generateEvalExample((c) => twoSumSequence({ ...c, seqLen, maxNum }), config); + }, + metric: (completion, _, sequence, config) => { + // Passing is binary in this case, and depends on the whole completion + const shouldPass = (() => { + const completionString = tokensToString(completion); + // Count the number of commas + const numCommas = (completionString.match(/,/g) || []).length; + if (numCommas !== 1) { + return false; + } + + // Use log to find the number length + const numberLength = Math.floor(Math.log10(config.maxNum)); + // Check that there are two numbers of the correct length, separated + // by a comma + // Match pattern of two 2-digit numbers separated by comma + const pattern = new RegExp(`^\\d{${numberLength}},\\d{${numberLength}}$`); + return pattern.test(completionString); + })(); + return completion.map(() => shouldPass); + } + }; + })(), + sort: (() => { + return { + generator: (config: NumberSequenceConfig) => { + const { seqLen, maxNum } = config as NumberSequenceConfig; + return generateEvalExample((c) => sortSequence({ ...c, seqLen, maxNum }), config); + }, + metric: (completion, target) => { + return completion.map((c, i) => c === target[i]); + } + }; + })(), + add: (() => { + return { + generator: (config: AdditionConfig) => { + const { maxNum } = config as AdditionConfig; + return generateEvalExample((c) => addSequence({ ...c, maxNum }), config); + }, + metric: (completion, target) => { + return completion.map((c, i) => c === target[i]); + } + }; + })(), + mod_add: (() => { + return { + generator: (config: ModAdditionConfig) => { + const { maxNum } = config as ModAdditionConfig; + return generateEvalExample((c) => modAddSequence({ ...c, maxNum }), config); + }, + metric: (completion, target) => { + return completion.map((c, i) => c === target[i]); + } + }; + })(), + zeros: (() => { + return { + generator: (config: FixedLengthConfig) => { + const { seqLen } = config as FixedLengthConfig; + return generateEvalExample((c) => zerosSequence({ ...c, seqLen }), config); + }, + metric: (completion, target) => { + return completion.map((c, i) => c === target[i]); + } + }; + })() }; diff --git a/examples/ratchet-train-toy/src/trainWorker.ts b/examples/ratchet-train-toy/src/trainWorker.ts index 13233669..007dc67d 100644 --- a/examples/ratchet-train-toy/src/trainWorker.ts +++ b/examples/ratchet-train-toy/src/trainWorker.ts @@ -1,5 +1,10 @@ import { Trainer } from '@ratchet-ml/ratchet-web-train'; -import { taskGenerators } from './tasks'; +import { + evalExampleGenerators, + trainBatchGenerators, + type EvalConfig, + type TaskConfigMap +} from './tasks'; let trainer: Trainer; let sessionCounter = 0; @@ -13,7 +18,8 @@ export interface TrainerConfig { n_head: number; block_size: number; batch_size: number; - dataset: string; + dataset: keyof typeof trainBatchGenerators; + task_parameters: TaskConfigMap[keyof TaskConfigMap]; activation: string; attention_only: boolean; position_encoding: string; @@ -58,12 +64,14 @@ async function trainingLoop(sessionId: number, config: TrainerConfig) { } // Get the appropriate task generator - const taskGenerator = taskGenerators[config.dataset]; + const taskGenerator = trainBatchGenerators[config.dataset]; + const evalConfig = evalExampleGenerators[config.dataset] as EvalConfig; if (!taskGenerator) { console.error(`Unknown dataset type: ${config.dataset}`); return; } + let step = 0; while (trainingSessions[sessionId]) { // Skip if this isn't the current session anymore if (sessionId !== currentSession) { @@ -72,10 +80,12 @@ async function trainingLoop(sessionId: number, config: TrainerConfig) { try { // Generate a new batch using the selected task generator - const [input, target] = taskGenerator(100, 5, 1); // maxNum, seqLen, batchSize + const [input, target] = generateTask(config); // Train on the batch const result = await trainer.train_on_batch(input, target); + const logits = result.get('logits') as Map; + const loss = result.get('loss') as Map; const attn_masks = result.get('attn_masks') as Map; const usage_bytes = trainer.usage_bytes(); @@ -83,12 +93,21 @@ async function trainingLoop(sessionId: number, config: TrainerConfig) { if (sessionId === currentSession) { self.postMessage({ type: 'step', - loss: result.get('loss'), + input: input, + target: target, + loss: { + total: loss.get('total'), + tokens: loss.get('tokens') + }, learning_rate: result.get('learning_rate'), usage_bytes, attn_masks: { data: attn_masks.get('data'), shape: attn_masks.get('shape') + }, + logits: { + data: logits.get('data'), + shape: logits.get('shape') } }); } @@ -107,6 +126,21 @@ async function trainingLoop(sessionId: number, config: TrainerConfig) { } } +function generateTask(config: TrainerConfig): [number[][], number[][]] { + const taskGenerator = trainBatchGenerators[config.dataset]; + if (!taskGenerator) { + throw new Error(`Unknown dataset: ${config.dataset}`); + } + + // Combine batch size with task-specific parameters + const taskConfig = { + batchSize: config.batch_size, + ...config.task_parameters + }; + + return taskGenerator(taskConfig); +} + self.onmessage = async (e: MessageEvent) => { if (e.data.type === 'stop') { markStopTraining(); From b58aba9cbb2034cdd4c2c745bd923eb1c6827025 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:28:46 -0700 Subject: [PATCH 020/146] Visualize train batches --- .../ratchet-train-toy/src/routes/+page.svelte | 72 +++++++++++++++++++ 1 file changed, 72 insertions(+) diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte index 0e8247e7..b3045605 100644 --- a/examples/ratchet-train-toy/src/routes/+page.svelte +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -9,6 +9,7 @@ import { taskMetadata } from '../tasks'; let loss = 0; + let initialTotalLoss: number | null = null; let worker: Worker; let chart: Chart; let speedChart: Chart; @@ -127,6 +128,15 @@ let scheduler_steps = 1000; let scheduler_eta_min = 1e-4; + // Add new state for batch visualization + let batchHistory: Array<{ + input: string[]; + target: string[]; + losses: number[]; + initialLoss: number; + }> = []; + const MAX_HISTORY = 5; // Keep last 10 batches + // Add task parameter state let taskParameters: Record = {}; @@ -261,6 +271,9 @@ function startTraining() { currentStepCount = 0; + // Clear batch history + batchHistory = []; + // isTraining = true; // Store the current model configuration currentModelLayers = n_layer; @@ -416,6 +429,30 @@ lastStepTime = currentTime; loss = data.loss.total; + if (initialTotalLoss === null) { + initialTotalLoss = loss; + } + + // Process batch data for visualization + const inputStrings = data.input.map((x: Array) => + x.map((y: number) => String.fromCharCode(y)) + ); + const targetStrings = data.target.map((x: Array) => + x.map((y: number) => String.fromCharCode(y)) + ); + const tokenLosses = data.loss.tokens.map((x: number) => x * data.loss.tokens.length); + + // Update batch history + batchHistory = [ + { + input: inputStrings, + target: targetStrings, + losses: tokenLosses, + initialLoss: initialTotalLoss / 2 + }, + ...batchHistory.slice(0, MAX_HISTORY - 1) + ]; + const currentLossDataset = chart.data.datasets[chart.data.datasets.length - 1]; const currentSpeedDataset = speedChart.data.datasets[speedChart.data.datasets.length - 1]; const currentMemoryDataset = @@ -729,6 +766,41 @@ {/if}
{/if} + + {#if isTraining} +
+
+

Train Batches

+
Showing last {MAX_HISTORY} batches
+
+
+ {#each batchHistory as batch} +
+ {#each batch.input as input, batchIdx} +
+
+ {input[0]}{#each [...input.slice(1), batch.target[batchIdx][batch.target[batchIdx].length - 1]] as char, i} + + {char} + + {/each} +
+
+ {/each} +
+ {/each} +
+
+ {/if}
From 106d692359a18b4d6ee48dc16b07f65e26954dc5 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:29:03 -0700 Subject: [PATCH 021/146] Make tick slider look less busy --- .../src/lib/components/TickSlider.svelte | 29 ++++++++++++------- 1 file changed, 19 insertions(+), 10 deletions(-) diff --git a/examples/ratchet-train-toy/src/lib/components/TickSlider.svelte b/examples/ratchet-train-toy/src/lib/components/TickSlider.svelte index 02fc9868..747def43 100644 --- a/examples/ratchet-train-toy/src/lib/components/TickSlider.svelte +++ b/examples/ratchet-train-toy/src/lib/components/TickSlider.svelte @@ -13,16 +13,24 @@ const ticks = []; const range = max - min; const totalTicks = range / step; - const skipFactor = Math.ceil(totalTicks / 10); // Show at most 10 ticks + const majorTickCount = 10; // Show 10 major ticks + const minorTickCount = 40; // Show at most 20 minor ticks + + const majorStep = Math.ceil(totalTicks / majorTickCount) * step; + const minorStep = Math.ceil(totalTicks / minorTickCount) * step; - for (let i = min; i <= max; i += step) { - if ((i - min) % (step * skipFactor) === 0) { - ticks.push({ - value: i, - label: formatter(i), - type: 'major' - }); - } else if ((i - min) % step === 0) { + // Add major ticks + for (let i = min; i <= max; i += majorStep) { + ticks.push({ + value: i, + label: formatter(i), + type: 'major' + }); + } + + // Add minor ticks + for (let i = min; i <= max; i += minorStep) { + if (!ticks.some(t => Math.abs(t.value - i) < step/2)) { ticks.push({ value: i, label: '', @@ -30,7 +38,8 @@ }); } } - return ticks; + + return ticks.sort((a, b) => a.value - b.value); } const ticks = generateTicks(); From 604e8746b6be48a367daab40b7ec10c3195f9f6a Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:30:19 -0700 Subject: [PATCH 022/146] Add eval + eval eample visualization --- .../ratchet-train-toy/src/routes/+page.svelte | 157 +++++++++++++++++- examples/ratchet-train-toy/src/trainWorker.ts | 69 ++++++++ 2 files changed, 225 insertions(+), 1 deletion(-) diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte index b3045605..0ffd8283 100644 --- a/examples/ratchet-train-toy/src/routes/+page.svelte +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -15,10 +15,12 @@ let speedChart: Chart; let memoryChart: Chart; let lrChart: Chart; + let accuracyChart: Chart; let canvas: HTMLCanvasElement; let speedCanvas: HTMLCanvasElement; let memoryCanvas: HTMLCanvasElement; let lrCanvas: HTMLCanvasElement; + let accuracyCanvas: HTMLCanvasElement; let attentionCanvases: HTMLCanvasElement[][] = []; let showAdvanced = false; let runCount = 0; @@ -137,6 +139,16 @@ }> = []; const MAX_HISTORY = 5; // Keep last 10 batches + // Add eval history state + let evalHistory: Array<{ + sequence: string; + completion: string; + target: string; + results: Array; + logits: number[]; + }> = []; + const MAX_EVAL_HISTORY = 5; + // Add task parameter state let taskParameters: Record = {}; @@ -271,7 +283,8 @@ function startTraining() { currentStepCount = 0; - // Clear batch history + // Clear evaluation and batch histories + evalHistory = []; batchHistory = []; // isTraining = true; @@ -369,6 +382,16 @@ pointStyle: false }); + // Add dataset to accuracy chart + accuracyChart.data.datasets.push({ + label: '', // Will be set by updateAllLabels + data: [], + borderColor: colors[runCount % colors.length], + tension: 0.1, + order: -runCount, + pointStyle: false + }); + updateAllLabels(); lastStepTime = performance.now(); @@ -414,6 +437,38 @@ case 'modelReady': addMessage('Model initialized and ready'); break; + case 'evalStreaming': + // Convert sequence and completion to strings + const sequence = data.sequence.map((x: number) => String.fromCharCode(x)).join(''); + const completion = data.completion.map((x: number) => String.fromCharCode(x)).join(''); + const target = data.target.map((x: number) => String.fromCharCode(x)).join(''); + + // Update eval history - find existing entry or create new one + const existingIndex = evalHistory.findIndex((entry) => entry.sequence === sequence); + if (existingIndex !== -1) { + // Update existing entry + evalHistory[existingIndex] = { + ...evalHistory[existingIndex], + completion, + target, + results: data.evalResult, + logits: data.logits.data + }; + evalHistory = evalHistory; // Trigger reactivity + } else { + // Create new entry + evalHistory = [ + { + sequence, + completion, + target, + results: data.evalResult, + logits: data.logits.data + }, + ...evalHistory.slice(0, MAX_EVAL_HISTORY - 1) + ]; + } + break; case 'step': currentStepCount++; if (!isTraining) { @@ -464,6 +519,18 @@ currentMemoryDataset.data.push(Number(data.usage_bytes) / (1024 * 1024)); // Convert bigint to number then to MB currentLrDataset.data.push(data.learning_rate); + // Update accuracy chart only when we have valid accuracy data + if (data.accuracy !== null && data.accuracy !== undefined) { + const currentAccuracyDataset = + accuracyChart.data.datasets[accuracyChart.data.datasets.length - 1]; + // Store both the step number and accuracy value + currentAccuracyDataset.data.push({ + x: currentStepCount, + y: data.accuracy + }); + accuracyChart.update(); + } + // Update labels if this is the longest run const maxLength = Math.max(...chart.data.datasets.map((d) => d.data.length)); const labels = Array.from({ length: maxLength }, (_, i) => i.toString()); @@ -471,6 +538,7 @@ speedChart.data.labels = labels; memoryChart.data.labels = labels; lrChart.data.labels = labels; + accuracyChart.data.labels = labels; if (isNaN(loss)) { addMessage('Loss is NaN; stopped training'); @@ -534,6 +602,7 @@ speedChart.update(); memoryChart.update(); lrChart.update(); + accuracyChart.update(); break; case 'error': addMessage(`Error: ${data.error}`); @@ -680,6 +749,57 @@ } } }); + + // Initialize accuracy chart + accuracyChart = new Chart(accuracyCanvas, { + type: 'line', + data: { + labels: [], + datasets: [] + }, + options: { + responsive: true, + animation: false, + aspectRatio: 4, + scales: { + x: { + type: 'linear', + display: true, + title: { + display: true, + text: 'Steps' + } + }, + y: { + beginAtZero: true, + max: 1, + title: { + display: true, + text: 'Accuracy' + } + } + }, + plugins: { + legend: { + display: false + }, + title: { + display: true, + text: 'Validation Accuracy', + font: { + weight: 'bold' + } + } + }, + datasets: { + line: { + order: -1, + showLine: true, // Connect points with lines + spanGaps: true // Connect points across gaps + } + } + } + }); }); @@ -728,6 +848,9 @@
+
+ +
{#if isTraining} @@ -800,6 +923,38 @@ {/each} + + {#if evalHistory.length > 0} +
+
+

Eval Results

+
Showing last {MAX_EVAL_HISTORY} evaluations
+
+
+ {#each evalHistory as evalEntry} +
+
+
+ {evalEntry.sequence}{#each evalEntry.completion.split('') as char, i} + + {char} + + {/each} + → {evalEntry.target} +
+
+
+ {/each} +
+
+ {/if} {/if}
diff --git a/examples/ratchet-train-toy/src/trainWorker.ts b/examples/ratchet-train-toy/src/trainWorker.ts index 007dc67d..5828d640 100644 --- a/examples/ratchet-train-toy/src/trainWorker.ts +++ b/examples/ratchet-train-toy/src/trainWorker.ts @@ -89,12 +89,80 @@ async function trainingLoop(sessionId: number, config: TrainerConfig) { const attn_masks = result.get('attn_masks') as Map; const usage_bytes = trainer.usage_bytes(); + let winCount = null; + const EVAL_TRIAL_COUNT = 5; + + // After every 10 steps, evaluate the model + if (step % 10 === 0) { + const [streamingSequence, streamingTarget] = evalConfig.generator(config.task_parameters); + let streamingExampleCompletion: number[] | null = null; + const streamingExampleLogits: number[] = []; + let streamingExampleMetric: boolean | null = null; + + // For the first eval, we'll stream it to the frontend + await trainer.generate( + streamingSequence, + /* max_tokens= */ streamingTarget.length + 1, + (tokens: number[], logitsObj: { shape: number[]; data: number[] }) => { + // For the first call (prompt), just store logits + if (streamingExampleCompletion === null) { + streamingExampleCompletion = []; + streamingExampleLogits.push(...logitsObj.data); + return; + } + + // For each subsequent token, append it and evaluate + streamingExampleCompletion.push(...tokens); + streamingExampleLogits.push(...logitsObj.data); + + // Run the metric on the current completion + const evalResult = evalConfig.metric( + streamingExampleCompletion, + streamingTarget, + streamingSequence, + config.task_parameters + ); + + streamingExampleMetric = evalResult.every((result) => result); + + // Send the streaming eval result to the frontend + if (sessionId === currentSession) { + self.postMessage({ + type: 'evalStreaming', + sequence: streamingSequence, + completion: streamingExampleCompletion, + target: streamingTarget, + evalResult, + logits: { + data: streamingExampleLogits, + shape: logitsObj.shape + } + }); + } + } + ); + + winCount = streamingExampleMetric === true ? 1 : 0; + + // We'll do best of 5 evals, so we'll do the rest non-streaming + for (let i = 0; i < EVAL_TRIAL_COUNT - 1; i++) { + const [sequence, target] = evalConfig.generator(config.task_parameters); + const result = await trainer.generate(sequence, target.length + 1); + const tokens = result.get('tokens') as number[]; + const evalResult = evalConfig.metric(tokens, target, sequence, config.task_parameters); + if (evalResult.every((result) => result)) { + winCount++; + } + } + } + // Only send message if this is still the current session if (sessionId === currentSession) { self.postMessage({ type: 'step', input: input, target: target, + accuracy: winCount === null ? null : winCount / EVAL_TRIAL_COUNT, loss: { total: loss.get('total'), tokens: loss.get('tokens') @@ -121,6 +189,7 @@ async function trainingLoop(sessionId: number, config: TrainerConfig) { } break; } + step++; // Yield to keep the worker responsive await new Promise((resolve) => setTimeout(resolve, 0)); } From 746bfa991d71e8dbf975a635c9e445f470590769 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:30:53 -0700 Subject: [PATCH 023/146] Add eslint rule to ignore _ vars --- examples/ratchet-train-toy/eslint.config.js | 59 +++++++++++++-------- 1 file changed, 36 insertions(+), 23 deletions(-) diff --git a/examples/ratchet-train-toy/eslint.config.js b/examples/ratchet-train-toy/eslint.config.js index e18311fa..85d7229a 100644 --- a/examples/ratchet-train-toy/eslint.config.js +++ b/examples/ratchet-train-toy/eslint.config.js @@ -1,34 +1,47 @@ -import prettier from "eslint-config-prettier"; +import prettier from 'eslint-config-prettier'; import js from '@eslint/js'; import { includeIgnoreFile } from '@eslint/compat'; import svelte from 'eslint-plugin-svelte'; import globals from 'globals'; import { fileURLToPath } from 'node:url'; import ts from 'typescript-eslint'; -const gitignorePath = fileURLToPath(new URL("./.gitignore", import.meta.url)); +const gitignorePath = fileURLToPath(new URL('./.gitignore', import.meta.url)); export default ts.config( - includeIgnoreFile(gitignorePath), - js.configs.recommended, - ...ts.configs.recommended, - ...svelte.configs["flat/recommended"], - prettier, - ...svelte.configs['flat/prettier'], - { - languageOptions: { - globals: { - ...globals.browser, - ...globals.node - } - } - }, - { - files: ["**/*.svelte"], + includeIgnoreFile(gitignorePath), + js.configs.recommended, + ...ts.configs.recommended, + ...svelte.configs['flat/recommended'], + prettier, + ...svelte.configs['flat/prettier'], + { + languageOptions: { + globals: { + ...globals.browser, + ...globals.node + } + } + }, + { + files: ['**/*.svelte'], - languageOptions: { - parserOptions: { - parser: ts.parser - } + languageOptions: { + parserOptions: { + parser: ts.parser + } + } + }, + { + rules: { + 'no-unused-vars': 'off', + '@typescript-eslint/no-unused-vars': [ + 'warn', + { + argsIgnorePattern: '^_', + varsIgnorePattern: '^_', + caughtErrorsIgnorePattern: '^_' + } + ] + } } - } ); From 89cbed639acd2ce8c671743068370cd7b098e65b Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:31:00 -0700 Subject: [PATCH 024/146] Update pnpm-lock.yaml --- pnpm-lock.yaml | 2278 ++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 2220 insertions(+), 58 deletions(-) diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml index acae9285..687c2abf 100644 --- a/pnpm-lock.yaml +++ b/pnpm-lock.yaml @@ -4,9 +4,6 @@ settings: autoInstallPeers: true excludeLinksFromLockfile: false -onlyBuiltDependencies: - - esbuild - importers: .: @@ -70,6 +67,76 @@ importers: specifier: ^5.3.3 version: 5.3.3 + examples/ratchet-train-toy: + dependencies: + chart.js: + specifier: ^4.4.7 + version: 4.4.7 + mathjs: + specifier: ^14.2.1 + version: 14.2.1 + devDependencies: + '@eslint/compat': + specifier: ^1.2.5 + version: 1.2.6(eslint@9.20.1) + '@eslint/js': + specifier: ^9.18.0 + version: 9.20.0 + '@sveltejs/adapter-static': + specifier: ^3.0.8 + version: 3.0.8(@sveltejs/kit@2.17.2) + '@sveltejs/kit': + specifier: ^2.16.0 + version: 2.17.2(@sveltejs/vite-plugin-svelte@5.0.3)(svelte@5.20.1)(vite@6.1.0) + '@sveltejs/vite-plugin-svelte': + specifier: ^5.0.0 + version: 5.0.3(svelte@5.20.1)(vite@6.1.0) + '@tailwindcss/vite': + specifier: ^4.0.0 + version: 4.0.6(vite@6.1.0) + eslint: + specifier: ^9.18.0 + version: 9.20.1 + eslint-config-prettier: + specifier: ^10.0.1 + version: 10.0.1(eslint@9.20.1) + eslint-plugin-svelte: + specifier: ^2.46.1 + version: 2.46.1(eslint@9.20.1)(svelte@5.20.1) + globals: + specifier: ^15.14.0 + version: 15.15.0 + prettier: + specifier: ^3.4.2 + version: 3.5.1 + prettier-plugin-svelte: + specifier: ^3.3.3 + version: 3.3.3(prettier@3.5.1)(svelte@5.20.1) + svelte: + specifier: ^5.0.0 + version: 5.20.1 + svelte-check: + specifier: ^4.0.0 + version: 4.1.4(svelte@5.20.1)(typescript@5.3.3) + tailwindcss: + specifier: ^4.0.0 + version: 4.0.6 + typescript: + specifier: ^5.0.0 + version: 5.3.3 + typescript-eslint: + specifier: ^8.20.0 + version: 8.24.1(eslint@9.20.1)(typescript@5.3.3) + vite: + specifier: ^6.1.0 + version: 6.1.0 + vite-plugin-top-level-await: + specifier: ^1.4.4 + version: 1.5.0(vite@6.1.0) + vite-plugin-wasm: + specifier: ^3.4.1 + version: 3.4.1(vite@6.1.0) + examples/ratchet-whisper: dependencies: '@ffmpeg/ffmpeg': @@ -129,6 +196,21 @@ packages: engines: {node: '>=10'} dev: true + /@ampproject/remapping@2.3.0: + resolution: {integrity: sha512-30iZtAPgz+LTIYoeivqYo853f02jBYSd5uGnGpkFV0M3xOt9aN73erkgYAmZU43x4VfqcnLxW9Kpg3R5LC4YYw==} + engines: {node: '>=6.0.0'} + dependencies: + '@jridgewell/gen-mapping': 0.3.5 + '@jridgewell/trace-mapping': 0.3.25 + dev: true + + /@babel/runtime@7.26.9: + resolution: {integrity: sha512-aA63XwOkcl4xxQa3HjPMqOP6LiK0ZDv3mUPYEFXkpHbaFjtGggE1A61FjFzJnB+p7/oy2gA8E+rcBNl/zC1tMg==} + engines: {node: '>=6.9.0'} + dependencies: + 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postcss: 8.5.2 + rollup: 4.34.8 + optionalDependencies: + fsevents: 2.3.3 + dev: true + + /vitefu@1.0.5(vite@6.1.0): + resolution: {integrity: sha512-h4Vflt9gxODPFNGPwp4zAMZRpZR7eslzwH2c5hn5kNZ5rhnKyRJ50U+yGCdc2IRaBs8O4haIgLNGrV5CrpMsCA==} + peerDependencies: + vite: ^3.0.0 || ^4.0.0 || ^5.0.0 || ^6.0.0 + peerDependenciesMeta: + vite: + optional: true + dependencies: + vite: 6.1.0 + dev: true + /wasm-pack@0.12.1: resolution: {integrity: sha512-dIyKWUumPFsGohdndZjDXRFaokUT/kQS+SavbbiXVAvA/eN4riX5QNdB6AhXQx37zNxluxQkuixZUgJ8adKjOg==} hasBin: true @@ -1617,6 +3760,11 @@ packages: isexe: 2.0.0 dev: true + /word-wrap@1.2.5: + resolution: {integrity: sha512-BN22B5eaMMI9UMtjrGd5g5eCYPpCPDUy0FJXbYsaT5zYxjFOckS53SQDE3pWkVoWpHXVb3BrYcEN4Twa55B5cA==} + engines: {node: '>=0.10.0'} + dev: true + /wrap-ansi@7.0.0: resolution: {integrity: sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q==} engines: {node: '>=10'} @@ -1643,12 +3791,26 @@ packages: 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'>=20'} From 2160384d35d3793b21887f6b05e48c85862f2a23 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:31:23 -0700 Subject: [PATCH 025/146] Formatting, I can only assume --- examples/ratchet-train-toy/src/routes/+page.svelte | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte index 0ffd8283..93638459 100644 --- a/examples/ratchet-train-toy/src/routes/+page.svelte +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -630,7 +630,7 @@ plugins: { legend: { reverse: true - }, + } // title: { // display: false, // // text: 'Training Loss', From 5bc060fba8b0d2f5810f1e78a262fc9f55e766ab Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:48:14 -0700 Subject: [PATCH 026/146] Turn val loss ticker into val accuracy --- examples/ratchet-train-toy/src/routes/+page.svelte | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte index 93638459..388ba100 100644 --- a/examples/ratchet-train-toy/src/routes/+page.svelte +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -9,6 +9,7 @@ import { taskMetadata } from '../tasks'; let loss = 0; + let evalAccuracy = 0; let initialTotalLoss: number | null = null; let worker: Worker; let chart: Chart; @@ -523,6 +524,7 @@ if (data.accuracy !== null && data.accuracy !== undefined) { const currentAccuracyDataset = accuracyChart.data.datasets[accuracyChart.data.datasets.length - 1]; + evalAccuracy = data.accuracy; // Store both the step number and accuracy value currentAccuracyDataset.data.push({ x: currentStepCount, @@ -841,9 +843,9 @@ >
-
+

train loss: {loss.toFixed(4)}

-

val loss: -.----

+

val accuracy: {evalAccuracy.toFixed(4)}

From c85cf0c55f0f96110a81b7fe8b05da0e8b3ba624 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:48:25 -0700 Subject: [PATCH 027/146] Fix alignment of links on mobile --- examples/ratchet-train-toy/src/routes/+page.svelte | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte index 388ba100..6f9b537d 100644 --- a/examples/ratchet-train-toy/src/routes/+page.svelte +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -835,10 +835,10 @@

toy transformer

-
- @vinhowe - @grantpitt - + @vinhowe + @grantpitt + github
From 185f57cf52816279073a764b32d478b7afb2e278 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Tue, 18 Feb 2025 04:48:38 -0700 Subject: [PATCH 028/146] Move sidebar to the left in a responsive way --- examples/ratchet-train-toy/src/routes/+page.svelte | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte index 6f9b537d..f4b7c1c7 100644 --- a/examples/ratchet-train-toy/src/routes/+page.svelte +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -981,7 +981,7 @@
-
+
{}] {}\n", - Self::format_timestamp(segment.start, false, "."), - Self::format_timestamp(segment.stop, false, "."), - fragment_text.trim().replace("-->", "->") - ) - } - - pub fn as_oai(&self, tokenizer: &WhisperTokenizer) -> String { - self.segments - .iter() - .map(|segment| self.format_single(segment, tokenizer)) - .collect::() - } - - fn format_timestamp(num: f64, always_include_hours: bool, decimal_marker: &str) -> String { - assert!(num >= 0.0, "non-negative timestamp expected"); - let milliseconds: i64 = (num * 1000.0) as i64; - - let hours = div_floor(milliseconds, 3_600_000); - let minutes = div_floor(milliseconds % 3_600_000, 60_000); - let seconds = div_floor(milliseconds % 60_000, 1000); - let milliseconds = milliseconds % 1000; - - let hours_marker = if always_include_hours || hours != 0 { - format!("{:02}:", hours) - } else { - String::new() - }; - - format!( - "{}{:02}:{:02}{}{:03}", - hours_marker, minutes, seconds, decimal_marker, milliseconds - ) - } -} - -#[derive(Debug, Serialize, Deserialize, derive_new::new)] -pub struct Segment { - pub start: f64, - pub stop: f64, - pub tokens: Vec, - pub last: bool, -} - -impl Segment { - pub fn from_tokens( - tokenizer: &WhisperTokenizer, - sliced_tokens: &[i32], - offset: f64, - last: bool, - ) -> Self { - let input_stride = N_FRAMES / N_AUDIO_CTX; // mel frames per output token: 2 - let time_precision: f64 = input_stride as f64 * (HOP_LENGTH as f64) / (SAMPLE_RATE as f64); // time per output token: 0.02 (seconds) - - let start_timestamp_pos = sliced_tokens[0] - tokenizer.timestamp_begin(); - let end_timestamp_pos = - sliced_tokens[sliced_tokens.len() - 1] - tokenizer.timestamp_begin(); - - let segment_tokens = sliced_tokens.iter().map(|x| *x as u32).collect::>(); - - let st = offset + (start_timestamp_pos as f64 * time_precision); - let et = offset + (end_timestamp_pos as f64 * time_precision); - let st = (st * 100.).round() / 100.; - let et = (et * 100.).round() / 100.; - Segment::new(st, et, segment_tokens, last) - } -} - -#[cfg_attr( - target_arch = "wasm32", - wasm_bindgen(getter_with_clone, js_name = Segment), - derive(serde::Serialize, serde::Deserialize) -)] -#[derive(Debug, derive_new::new)] -pub struct StreamedSegment { - pub start: f64, - pub stop: f64, - pub text: String, - pub last: bool, -} - -impl std::fmt::Display for StreamedSegment { - fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result { - write!( - f, - "[{} --> {}] {}", - TranscriptionResult::format_timestamp(self.start, false, "."), - TranscriptionResult::format_timestamp(self.stop, false, "."), - self.text.trim().replace("-->", "->") - ) - } -} - -#[cfg_attr(target_arch = "wasm32", wasm_bindgen)] -impl StreamedSegment { - pub fn start(&self) -> f64 { - self.start - } - - pub fn stop(&self) -> f64 { - self.stop - } - - pub fn text(&self) -> String { - self.text.clone() - } - - pub fn last(&self) -> bool { - self.last - } - - pub(crate) fn from_tokens( - tokenizer: &WhisperTokenizer, - sliced_tokens: &[i32], - offset: f64, - last: bool, - ) -> Self { - let segment = Segment::from_tokens(tokenizer, sliced_tokens, offset, last); - let segment_tokens = segment - .tokens - .into_iter() - .filter(|t| *t < tokenizer.timestamp_begin() as _) - .collect::>(); - let segment_text = tokenizer.decode(segment_tokens.as_slice(), true).unwrap(); - StreamedSegment::new(segment.start, segment.stop, segment_text, last) - } -} diff --git a/crates/ratchet-models/tests/whisper.rs b/crates/ratchet-models/tests/whisper.rs deleted file mode 100644 index f34ced21..00000000 --- a/crates/ratchet-models/tests/whisper.rs +++ /dev/null @@ -1,218 +0,0 @@ -#![cfg(target_arch = "wasm32")] -wasm_bindgen_test::wasm_bindgen_test_configure!(run_in_browser); - -use ndarray::{s, Axis}; -use ndarray_stats::QuantileExt; -use ratchet::{shape, Device, DeviceRequest, Tensor}; -use ratchet_hub::{ApiBuilder, RepoType}; -use ratchet_loader::gguf::gguf; -use ratchet_models::whisper::{Config, Whisper, WhisperDecoder, WhisperEncoder}; -use ratchet_nn::Module; -use std::path::PathBuf; -use wasm_bindgen::prelude::*; -use wasm_bindgen_test::*; - -fn log_init() { - console_error_panic_hook::set_once(); - log::set_max_level(log::LevelFilter::Off); - console_log::init_with_level(log::Level::Debug).unwrap(); -} - -/* -#[wasm_bindgen_test] -async fn distil_large_v3_encoder() -> Result<(), JsValue> { - log_init(); - let model_repo = - ApiBuilder::from_hf("FL33TW00D-HF/distil-whisper-large-v3", RepoType::Model).build(); - let model_data = model_repo.get("distil-large-v3_q8_0.gguf").await?; - let config_data = model_repo.get("config.json").await?; - - let ground_repo = ApiBuilder::from_hf("FL33TW00D-HF/ratchet-util", RepoType::Dataset).build(); - let input_npy = ground_repo.get("distil_large_v3_q80_mm0_input.npy").await?; - let ground_npy = ground_repo.get("distil_large_v3_q80_mm0_hs.npy").await?; - - let mut reader = std::io::BufReader::new(std::io::Cursor::new(model_data.to_vec())); - let header = gguf::Header::read(&mut reader).unwrap(); - let config: Config = serde_json::from_slice(&config_data.to_vec()).unwrap(); - - let device = Device::request_device(DeviceRequest::GPU).await.unwrap(); - - let input_data = &input_npy.to_vec(); - let input = Tensor::from_npy_bytes::(input_data, &device).unwrap(); - let ground = Tensor::from_npy_bytes::(&ground_npy.to_vec(), &Device::CPU).unwrap(); - - let encoder = WhisperEncoder::load(&header, &config, &mut reader, &device).unwrap(); - let result = encoder - .schedule(input) - .unwrap() - .full() - .unwrap() - .resolve() - .unwrap(); - let ours = result.to(&Device::CPU).await.unwrap(); - ground.all_close(&ours, 1e-3, 1e-3).unwrap(); - Ok(()) -}*/ - -/* -#[wasm_bindgen_test] -async fn distil_large_v3_decoder() -> Result<(), JsValue> { - log_init(); - let model_repo = - ApiBuilder::from_hf("FL33TW00D-HF/distil-whisper-large-v3", RepoType::Model).build(); - let model_data = model_repo.get("distil-large-v3_q8_0.gguf").await?; - let config_data = model_repo.get("config.json").await?; - - let ground_repo = ApiBuilder::from_hf("FL33TW00D-HF/ratchet-util", RepoType::Dataset).build(); - let hs_data = ground_repo.get("distil_large_v3_q80_mm0_hs.npy").await?; - - let mut reader = std::io::BufReader::new(std::io::Cursor::new(model_data.to_vec())); - let header = gguf::Header::read(&mut reader).unwrap(); - let config: Config = serde_json::from_slice(&config_data.to_vec()).unwrap(); - - let device = Device::request_device(DeviceRequest::GPU).await.unwrap(); - let audio_ctx = Tensor::from_npy_bytes::(&hs_data.to_vec(), &device) - .unwrap() - .half() - .unwrap() - .resolve() - .unwrap(); - log::debug!("Audio Context: {:?}", audio_ctx); - let mut decoder = WhisperDecoder::load(&header, &config, &mut reader, &device).unwrap(); - - let mut tokens = vec![50258, 50259, 50360]; - let mut all_tokens = tokens.clone(); - let mut all_logits = vec![]; - while tokens[tokens.len() - 1] != 50257 { - let token_t = Tensor::from_data(tokens.clone(), shape![1, tokens.len()], device.clone()); - let result = decoder - .schedule([audio_ctx.clone(), token_t]) - .unwrap() - .resolve_debug() - .unwrap(); - - let our_logits = result.to(&Device::CPU).await.unwrap(); - all_logits.push(our_logits.clone()); - let nd_logits = our_logits.to_ndarray_view::(); - log::info!("Logits: {:?}", nd_logits); - - let sliced = nd_logits.slice(s![.., -1.., ..51866]).remove_axis(Axis(1)); - decoder.cache_mut().update(tokens.len()); - - tokens = sliced - .map_axis(Axis(1), |row| row.argmax_skipnan().unwrap()) - .iter() - .map(|&x| x as i32) - .collect::>(); - println!("Token: {:?}", tokens); - panic!(); - all_tokens.extend(tokens.clone()); - } - - let ground_tokens = vec![ - 50258, 50259, 50360, 50365, 639, 307, 264, 4532, 3479, 587, 11, 15578, 264, 881, 2062, 847, - 11, 34674, 5932, 30340, 295, 3123, 4397, 608, 1652, 13, 50517, 50530, 6947, 472, 575, - 12023, 4365, 11, 20899, 11, 10445, 11, 18356, 11, 4225, 4782, 11, 50624, 50626, 1804, 4651, - 3123, 4397, 34922, 8963, 862, 6352, 13, 50695, 50701, 821, 311, 257, 3804, 5214, 11, 2610, - 5214, 11, 6383, 11, 2643, 5214, 11, 293, 544, 13, 50797, 50807, 10246, 8963, 2436, 2965, - 281, 747, 604, 1081, 13, 50875, 50881, 400, 456, 366, 867, 34674, 862, 365, 11, 293, 1184, - 472, 1487, 365, 1080, 1065, 2121, 11377, 11, 51002, 51007, 4532, 3479, 5864, 293, 1019, 11, - 5456, 4122, 300, 30686, 25038, 1286, 13, 51120, 51135, 30062, 264, 6582, 29814, 412, 264, - 10155, 11, 1849, 1426, 11, 587, 11, 264, 3874, 34544, 412, 264, 7267, 3096, 13, 51243, - 51246, 18463, 428, 1032, 412, 264, 1032, 5675, 13, 51287, 51290, 30062, 264, 16629, 7283, - 13, 51320, 51328, 400, 613, 862, 6352, 3318, 1214, 281, 1254, 257, 3123, 4397, 34922, 8963, - 1081, 6352, 11, 370, 27985, 11, 51504, 51504, 370, 6239, 11, 370, 44078, 1688, 356, 9942, - 11, 291, 603, 528, 281, 8963, 552, 439, 13, 51623, 51635, 25642, 12089, 1652, 366, 1027, - 14759, 490, 7336, 836, 65, 13, 51743, 51743, 440, 4356, 436, 366, 11, 264, 1101, 436, 366, - 13, 51834, - ]; - assert_eq!(all_tokens, ground_tokens); - Ok(()) -}*/ - -/* -#[wasm_bindgen_test] -async fn tiny_encoder() -> Result<(), JsValue> { - log_init(); - let model_repo = ApiBuilder::from_hf("FL33TW00D-HF/whisper-tiny", RepoType::Model).build(); - let model_data = model_repo.get("tiny_f32.gguf").await?; - let config_data = model_repo.get("config.json").await?; - - let ground_repo = ApiBuilder::from_hf("FL33TW00D-HF/ratchet-util", RepoType::Dataset).build(); - let input_npy = ground_repo.get("jfk_tiny_encoder_input.npy").await?; - let ground_npy = ground_repo.get("jfk_tiny_encoder_hs.npy").await?; - - let mut reader = std::io::BufReader::new(std::io::Cursor::new(model_data.to_vec())); - let header = gguf::Header::read(&mut reader).unwrap(); - let config: Config = serde_json::from_slice(&config_data.to_vec()).unwrap(); - - let device = Device::request_device(DeviceRequest::GPU).await.unwrap(); - - let input_data = &input_npy.to_vec(); - let input = Tensor::from_npy_bytes::(input_data, &device).unwrap(); - let ground = Tensor::from_npy_bytes::(&ground_npy.to_vec(), &Device::CPU).unwrap(); - - let encoder = WhisperEncoder::load(&header, &config, &mut reader, &device).unwrap(); - let result = encoder.schedule(input).unwrap().resolve().unwrap(); - let ours = result.to(&Device::CPU).await.unwrap(); - ground.all_close(&ours, 1e-3, 1e-3).unwrap(); - Ok(()) -} -*/ - -#[wasm_bindgen_test] -async fn tiny_decoder() -> Result<(), JsValue> { - log_init(); - let model_repo = ApiBuilder::from_hf("FL33TW00D-HF/whisper-tiny", RepoType::Model).build(); - let model_data = model_repo.get("tiny_f32.gguf").await?; - let config_data = model_repo.get("config.json").await?; - - let ground_repo = ApiBuilder::from_hf("FL33TW00D-HF/ratchet-util", RepoType::Dataset).build(); - let hs_data = ground_repo.get("jfk_tiny_encoder_hs.npy").await?; - - let mut reader = std::io::BufReader::new(std::io::Cursor::new(model_data.to_vec())); - let header = gguf::Header::read(&mut reader).unwrap(); - let config: Config = serde_json::from_slice(&config_data.to_vec()).unwrap(); - - let device = Device::request_device(DeviceRequest::GPU).await.unwrap(); - - let audio_ctx = Tensor::from_npy_bytes::(&hs_data.to_vec(), &device).unwrap(); - let mut decoder = WhisperDecoder::load(&header, &config, &mut reader, &device).unwrap(); - - let mut tokens = vec![50258, 50259, 50359]; - let mut all_tokens = tokens.clone(); - let mut all_logits = vec![]; - let vocab_size = 51865; - while tokens[tokens.len() - 1] != 50257 { - let token_t = Tensor::from_data(tokens.clone(), shape![1, tokens.len()], device.clone()); - let result = decoder - .schedule([audio_ctx.clone(), token_t]) - .unwrap() - .resolve() - .unwrap(); - - let our_logits = result.to(&Device::CPU).await.unwrap(); - all_logits.push(our_logits.clone()); - let nd_logits = our_logits.to_ndarray_view::(); - log::debug!("ND LOGITS: {:?}", nd_logits); - let sliced = nd_logits - .slice(s![.., -1.., ..vocab_size]) - .remove_axis(Axis(1)); - decoder.cache_mut().update(tokens.len()); - - tokens = sliced - .map_axis(Axis(1), |row| row.argmax_skipnan().unwrap()) - .iter() - .map(|&x| x as i32) - .collect::>(); - println!("Token: {:?}", tokens); - all_tokens.extend(tokens.clone()); - } - - let ground_tokens = vec![ - 50258, 50259, 50359, 50363, 400, 370, 452, 7177, 6280, 1029, 406, 437, 428, 1941, 393, 360, - 337, 291, 1029, 437, 291, 393, 360, 337, 428, 1941, 13, 50257, - ]; - assert_eq!(all_tokens, ground_tokens); - Ok(()) -} diff --git a/crates/ratchet-web/src/model.rs b/crates/ratchet-web/src/model.rs index e08101f3..e0df45da 100644 --- a/crates/ratchet-web/src/model.rs +++ b/crates/ratchet-web/src/model.rs @@ -8,14 +8,12 @@ use ratchet_models::phi2; use ratchet_models::phi2::Phi2; use ratchet_models::phi3::{self, Phi3}; use ratchet_models::registry::{AvailableModels, PhiVariants, Quantization}; -use ratchet_models::whisper::{transcribe::transcribe, transcript::StreamedSegment, Whisper}; use ratchet_models::TensorMap; use tokenizers::Tokenizer; use wasm_bindgen::prelude::*; #[derive(Debug)] pub enum WebModel { - Whisper(Whisper), Phi2(Phi2), Phi3(Phi3), Moondream(Moondream), @@ -24,25 +22,6 @@ pub enum WebModel { impl WebModel { pub async fn run(&mut self, input: JsValue) -> Result { match self { - WebModel::Whisper(model) => { - let input: WhisperInputs = serde_wasm_bindgen::from_value(input)?; - let options = serde_wasm_bindgen::from_value(input.decode_options)?; - - let callback = if !input.callback.is_null() { - let rs_callback = |decoded: StreamedSegment| { - let js_decoded = serde_wasm_bindgen::to_value(&decoded).unwrap(); - let _ = input.callback.call1(&JsValue::NULL, &js_decoded); - }; - Some(rs_callback) - } else { - None - }; - - let result = transcribe(model, input.audio, options, callback) - .await - .unwrap(); - serde_wasm_bindgen::to_value(&result).map_err(|e| e.into()) - } WebModel::Phi2(model) => { let input: PhiInputs = serde_wasm_bindgen::from_value(input)?; let rs_callback = |output: String| { @@ -104,10 +83,6 @@ impl WebModel { ) -> Result { let header = serde_wasm_bindgen::from_value::
(model_record.header).unwrap(); match model_record.model { - AvailableModels::Whisper(variant) => { - let model = Whisper::from_web(header, tensor_map, variant).await?; - Ok(WebModel::Whisper(model)) - } AvailableModels::Phi(variant) => match variant { PhiVariants::Phi2 => { let model = Phi2::from_web(header, tensor_map).await?; @@ -127,15 +102,6 @@ impl WebModel { } } -#[derive(serde::Serialize, serde::Deserialize)] -pub struct WhisperInputs { - pub audio: Vec, - #[serde(with = "serde_wasm_bindgen::preserve")] - pub decode_options: JsValue, - #[serde(with = "serde_wasm_bindgen::preserve")] - pub callback: js_sys::Function, -} - #[derive(serde::Serialize, serde::Deserialize)] pub struct PhiInputs { pub prompt: String, @@ -285,124 +251,4 @@ impl Model { Ok(()) } -} - -#[cfg(all(test, target_arch = "wasm32"))] -mod tests { - use super::*; - use ratchet_hub::{ApiBuilder, RepoType}; - use ratchet_models::registry::PhiVariants; - use ratchet_models::registry::WhisperVariants; - use ratchet_models::whisper::options::DecodingOptionsBuilder; - use tokenizers::Tokenizer; - use wasm_bindgen_test::*; - - wasm_bindgen_test::wasm_bindgen_test_configure!(run_in_browser); - - fn log_init() { - console_error_panic_hook::set_once(); - let logger = fern::Dispatch::new() - .format(|out, message, record| { - out.finish(format_args!( - "{}[{}][{}] {}", - chrono::Local::now().format("[%Y-%m-%d][%H:%M:%S]"), - record.target(), - record.level(), - message - )) - }) - .level_for("tokenizers", log::LevelFilter::Off) - .level(log::LevelFilter::Warn) - .chain(fern::Output::call(console_log::log)) - .apply(); - match logger { - Ok(_) => log::info!("Logging initialized."), - Err(error) => eprintln!("Error initializing logging: {:?}", error), - } - } - - fn load_sample(bytes: &[u8]) -> Vec { - let mut reader = hound::WavReader::new(std::io::Cursor::new(bytes)).unwrap(); - reader - .samples::() - .map(|x| x.unwrap() as f32 / 32768.0) - .collect::>() - } - - #[wasm_bindgen_test] - async fn whisper_browser() -> Result<(), JsValue> { - log_init(); - let download_cb: Closure = Closure::new(|p| { - log::info!("Provided closure got progress: {}", p); - }); - let js_cb: &js_sys::Function = download_cb.as_ref().unchecked_ref(); - - let mut model = Model::load( - AvailableModels::Whisper(WhisperVariants::Base), - Quantization::F16, - js_cb, - ) - .await - .unwrap(); - - let data_repo = ApiBuilder::from_hf("FL33TW00D-HF/ratchet-util", RepoType::Dataset).build(); - let audio_bytes = data_repo.get("mm0.wav").await?; - let sample = load_sample(&audio_bytes.to_vec()); - - let decode_options = DecodingOptionsBuilder::default().build(); - - let cb: Closure = Closure::new(|s| { - log::info!("GENERATED SEGMENT: {:?}", s); - }); - let js_cb: &js_sys::Function = cb.as_ref().unchecked_ref(); - - let input = WhisperInputs { - audio: sample, - decode_options, - callback: js_cb.clone(), - }; - let input = serde_wasm_bindgen::to_value(&input).unwrap(); - let result = model.run(input).await.unwrap(); - log::warn!("Result: {:?}", result); - Ok(()) - } - - #[wasm_bindgen_test] - async fn whisper_browser_custom() -> Result<(), JsValue> { - log_init(); - let download_cb: Closure = Closure::new(|p| { - log::info!("Provided closure got progress: {}", p); - }); - let js_cb: &js_sys::Function = download_cb.as_ref().unchecked_ref(); - - let mut model = Model::load_custom( - "https://huggingface.co/FL33TW00D-HF/whisper-base/resolve/main".to_string(), - AvailableModels::Whisper(WhisperVariants::Base), - Quantization::F16, - js_cb, - ) - .await - .unwrap(); - - let data_repo = ApiBuilder::from_hf("FL33TW00D-HF/ratchet-util", RepoType::Dataset).build(); - let audio_bytes = data_repo.get("mm0.wav").await?; - let sample = load_sample(&audio_bytes.to_vec()); - - let decode_options = DecodingOptionsBuilder::default().build(); - - let cb: Closure = Closure::new(|s| { - log::info!("GENERATED SEGMENT: {:?}", s); - }); - let js_cb: &js_sys::Function = cb.as_ref().unchecked_ref(); - - let input = WhisperInputs { - audio: sample, - decode_options, - callback: js_cb.clone(), - }; - let input = serde_wasm_bindgen::to_value(&input).unwrap(); - let result = model.run(input).await.unwrap(); - log::warn!("Result: {:?}", result); - Ok(()) - } -} +} \ No newline at end of file diff --git a/examples/ratchet-whisper/.gitignore b/examples/ratchet-whisper/.gitignore deleted file mode 100644 index fd3dbb57..00000000 --- a/examples/ratchet-whisper/.gitignore +++ /dev/null @@ -1,36 +0,0 @@ -# See https://help.github.com/articles/ignoring-files/ for more about ignoring files. - -# dependencies -/node_modules -/.pnp -.pnp.js -.yarn/install-state.gz - -# testing -/coverage - -# next.js -/.next/ -/out/ - -# production -/build - -# misc -.DS_Store -*.pem - -# debug -npm-debug.log* -yarn-debug.log* -yarn-error.log* - -# local env files -.env*.local - -# vercel -.vercel - -# typescript -*.tsbuildinfo -next-env.d.ts diff --git a/examples/ratchet-whisper/README.md b/examples/ratchet-whisper/README.md deleted file mode 100644 index c4033664..00000000 --- a/examples/ratchet-whisper/README.md +++ /dev/null @@ -1,36 +0,0 @@ -This is a [Next.js](https://nextjs.org/) project bootstrapped with [`create-next-app`](https://github.com/vercel/next.js/tree/canary/packages/create-next-app). - -## Getting Started - -First, run the development server: - -```bash -npm run dev -# or -yarn dev -# or -pnpm dev -# or -bun dev -``` - -Open [http://localhost:3000](http://localhost:3000) with your browser to see the result. - -You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file. - -This project uses [`next/font`](https://nextjs.org/docs/basic-features/font-optimization) to automatically optimize and load Inter, a custom Google Font. - -## Learn More - -To learn more about Next.js, take a look at the following resources: - -- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API. -- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial. - -You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js/) - your feedback and contributions are welcome! - -## Deploy on Vercel - -The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js. - -Check out our [Next.js deployment documentation](https://nextjs.org/docs/deployment) for more details. diff --git a/examples/ratchet-whisper/next.config.mjs b/examples/ratchet-whisper/next.config.mjs deleted file mode 100644 index 15eff7c7..00000000 --- a/examples/ratchet-whisper/next.config.mjs +++ /dev/null @@ -1,6 +0,0 @@ -/** @type {import('next').NextConfig} */ -const nextConfig = { - output: 'export' -}; - -export default nextConfig; diff --git a/examples/ratchet-whisper/package.json b/examples/ratchet-whisper/package.json deleted file mode 100644 index 52597369..00000000 --- a/examples/ratchet-whisper/package.json +++ /dev/null @@ -1,31 +0,0 @@ -{ - "name": "ratchet-whisper", - "version": "0.1.0", - "private": true, - "scripts": { - "dev": "next dev", - "build": "next build", - "start": "next start", - "lint": "next lint" - }, - "dependencies": { - "@ffmpeg/ffmpeg": "0.12.6", - "@ffmpeg/util": "^0.12.1", - "@ratchet-ml/ratchet-web": "link:../../target/pkg/ratchet-web", - "fix-webm-duration": "^1.0.5", - "next": "14.1.0", - "react": "^18.2.0", - "react-dom": "^18.2.0", - "react-hot-toast": "^2.4.1", - "react-responsive-modal": "^6.4.2" - }, - "devDependencies": { - "@types/node": "^20.11.24", - "@types/react": "^18.2.61", - "@types/react-dom": "^18.2.19", - "autoprefixer": "^10.4.18", - "postcss": "^8.4.35", - "tailwindcss": "^3.4.1", - "typescript": "^5.3.3" - } -} diff --git a/examples/ratchet-whisper/postcss.config.js b/examples/ratchet-whisper/postcss.config.js deleted file mode 100644 index 33ad091d..00000000 --- a/examples/ratchet-whisper/postcss.config.js +++ /dev/null @@ -1,6 +0,0 @@ -module.exports = { - plugins: { - tailwindcss: {}, - autoprefixer: {}, - }, -} diff --git a/examples/ratchet-whisper/src/app/audio.ts b/examples/ratchet-whisper/src/app/audio.ts deleted file mode 100644 index 0ece4b79..00000000 --- a/examples/ratchet-whisper/src/app/audio.ts +++ /dev/null @@ -1,88 +0,0 @@ -import fixWebmDuration from "fix-webm-duration"; - -export interface Recording { - blob: Blob; - buffer: ArrayBuffer; -} - -export class MicRecorder { - private currentStart: number | null = null; - private currentStream: MediaStream | null = null; - private inner: MediaRecorder | null = null; - private audioChunks: Blob[] = []; - private static readonly supportedMimes = [ - "audio/webm", // Chrome - "audio/ogg", // Firefox - ]; - - private constructor(recorder: MediaRecorder) { - this.inner = recorder; - } - - public static async start(): Promise { - if (!navigator.mediaDevices) { - throw new Error("Media device not available"); - } - - const stream = await navigator.mediaDevices.getUserMedia({ - audio: true, - }); - let mimeType = MicRecorder.supportedMimes.find((mime: string) => - MediaRecorder.isTypeSupported(mime) - ); - const inner = new MediaRecorder(stream, { - mimeType - }); - const recorder = new MicRecorder(inner); - recorder.currentStream = stream; - - inner.addEventListener("dataavailable", (event) => { - recorder.audioChunks.push(event.data); - }); - inner.start(); - recorder.currentStart = Date.now(); - return recorder; - } - - public isRecording(): boolean { - return this.inner !== null && this.inner.state === "recording"; - } - - public async stop(): Promise { - if (!this.inner) { - throw new Error("Please start the recorder first"); - } - - const promise: Promise = new Promise( - (resolve) => { - this.inner!.addEventListener("stop", async () => { - const duration = Date.now() - this.currentStart!; - let blob = new Blob(this.audioChunks, { - type: this.inner!.mimeType, - }); - - if (this.inner!.mimeType.includes("webm")) { - blob = await fixWebmDuration(blob, duration, { - logger: false, - }); - } - - const buffer = await blob.arrayBuffer(); - - resolve({ - blob, - buffer, - }); - }); - this.inner!.stop(); - this.currentStream!.getTracks().forEach((track) => - track.stop() - ); - } - ); - return promise; - } -} - -export default MicRecorder; - diff --git a/examples/ratchet-whisper/src/app/components/WebGPUModal.tsx b/examples/ratchet-whisper/src/app/components/WebGPUModal.tsx deleted file mode 100644 index 91ff1134..00000000 --- a/examples/ratchet-whisper/src/app/components/WebGPUModal.tsx +++ /dev/null @@ -1,79 +0,0 @@ -import React, { useState, useEffect } from "react"; -import Modal from "react-responsive-modal"; - -const WebGPUModal = () => { - const [hasWebGPU, setHasWebGPU] = useState(false); - const [isModalOpen, setIsModalOpen] = useState(false); - - useEffect(() => { - //@ts-ignore - if (!navigator.gpu) { - setIsModalOpen(true); - return; - } - setHasWebGPU(true); - }, []); - - const handleModalClose = () => { - setIsModalOpen(false); - }; - - const closeIcon = ( - - - - - - - - - - - - - - - - - - ); - - return ( - <> - {!hasWebGPU ? ( - -
-
-

- Uh oh! It looks like your browser doesn't - support WebGPU. Please try again in supported browser (Chrome 121+). -

-
-
- - ) : ( - <> - )} - - ); -}; - -export default WebGPUModal; - diff --git a/examples/ratchet-whisper/src/app/components/configModal.tsx b/examples/ratchet-whisper/src/app/components/configModal.tsx deleted file mode 100644 index 0674fcf6..00000000 --- a/examples/ratchet-whisper/src/app/components/configModal.tsx +++ /dev/null @@ -1,52 +0,0 @@ -import React, { useState, useEffect } from "react"; -import Modal from "react-responsive-modal"; -import LanguageDropdown from "./languageDropdown"; -import SuppressComponent from "./suppressSelector"; -import TaskComponent from "./taskSelector"; -import { Task } from "@ratchet-ml/ratchet-web"; - -interface ConfigModalProps { - isModalOpen: boolean; - setIsModalOpen: React.Dispatch>; - configOptions: ConfigOptions; - setConfigOptions: React.Dispatch>; -} - -export interface ConfigOptions { - language: string | null; - task: Task; - suppress_non_speech: boolean; -} - -const ConfigModal = (props: ConfigModalProps) => { - const handleModalClose = () => { - props.setIsModalOpen(false); - }; - - return ( - <> - -
-
- - - -
-
- - - ); -}; - -export default ConfigModal; - diff --git a/examples/ratchet-whisper/src/app/components/languageDropdown.tsx b/examples/ratchet-whisper/src/app/components/languageDropdown.tsx deleted file mode 100644 index 9d67359d..00000000 --- a/examples/ratchet-whisper/src/app/components/languageDropdown.tsx +++ /dev/null @@ -1,191 +0,0 @@ -import React, { useState } from "react"; -import { ConfigOptions } from "./configModal"; -import { DecodingOptionsBuilder } from "@ratchet-ml/ratchet-web"; - -const AvailableLanguages = { - en: "English", - zh: "Chinese", - de: "German", - es: "Spanish", - ru: "Russian", - ko: "Korean", - fr: "French", - ja: "Japanese", - pt: "Portuguese", - tr: "Turkish", - pl: "Polish", - ca: "Catalan", - nl: "Dutch", - ar: "Arabic", - sv: "Swedish", - it: "Italian", - id: "Indonesian", - hi: "Hindi", - fi: "Finnish", - vi: "Vietnamese", - he: "Hebrew", - uk: "Ukrainian", - el: "Greek", - ms: "Malay", - cs: "Czech", - ro: "Romanian", - da: "Danish", - hu: "Hungarian", - ta: "Tamil", - no: "Norwegian", - th: "Thai", - ur: "Urdu", - hr: "Croatian", - bg: "Bulgarian", - lt: "Lithuanian", - la: "Latin", - mi: "Maori", - ml: "Malayalam", - cy: "Welsh", - sk: "Slovak", - te: "Telugu", - fa: "Persian", - lv: "Latvian", - bn: "Bengali", - sr: "Serbian", - az: "Azerbaijani", - sl: "Slovenian", - kn: "Kannada", - et: "Estonian", - mk: "Macedonian", - br: "Breton", - eu: "Basque", - is: "Icelandic", - hy: "Armenian", - ne: "Nepali", - mn: "Mongolian", - bs: "Bosnian", - kk: "Kazakh", - sq: "Albanian", - sw: "Swahili", - gl: "Galician", - mr: "Marathi", - pa: "Punjabi", - si: "Sinhala", - km: "Khmer", - sn: "Shona", - yo: "Yoruba", - so: "Somali", - af: "Afrikaans", - oc: "Occitan", - ka: "Georgian", - be: "Belarusian", - tg: "Tajik", - sd: "Sindhi", - gu: "Gujarati", - am: "Amharic", - yi: "Yiddish", - lo: "Lao", - uz: "Uzbek", - fo: "Faroese", - ht: "Haitian creole", - ps: "Pashto", - tk: "Turkmen", - nn: "Nynorsk", - mt: "Maltese", - sa: "Sanskrit", - lb: "Luxembourgish", - my: "Myanmar", - bo: "Tibetan", - tl: "Tagalog", - mg: "Malagasy", - as: "Assamese", - tt: "Tatar", - haw: "Hawaiian", - ln: "Lingala", - ha: "Hausa", - ba: "Bashkir", - jw: "Javanese", - su: "Sundanese", - yue: "Cantonese", -}; - -interface LanguageDropdownProps { - configOptions: ConfigOptions; - setConfigOptions: React.Dispatch>; -} - -const LanguageDropdown = (props: LanguageDropdownProps) => { - const [open, setOpen] = useState(false); - const [selectedLanguage, setSelectedLanguage] = useState( - props.configOptions.language - ); - - const toggleOpen = () => setOpen((prev) => !prev); - - const selectLanguage = (lang: string) => { - props.setConfigOptions((prev: ConfigOptions) => ({ - ...prev, - language: lang, - })); - setSelectedLanguage(lang); - setOpen(false); - }; - - return ( -
-
- - -
- - {open && ( -
-
- {Object.entries(AvailableLanguages).map( - ([lang, name]) => ( - selectLanguage(lang)} - > - {name} - - ) - )} -
-
- )} -
- ); -}; - -export default LanguageDropdown; - diff --git a/examples/ratchet-whisper/src/app/components/micButton.tsx b/examples/ratchet-whisper/src/app/components/micButton.tsx deleted file mode 100644 index 4b7d4d0a..00000000 --- a/examples/ratchet-whisper/src/app/components/micButton.tsx +++ /dev/null @@ -1,93 +0,0 @@ -import { useState } from "react"; -import MicRecorder from "../audio"; - -const SAMPLE_RATE = 16000; - -interface MicButtonProps { - setBlobUrl: (blobUrl: string) => void; - setAudioData: (audioData: Float32Array) => void; - setAudioMetadata: (audioMetadata: AudioMetadata) => void; -} - -export interface AudioMetadata { - file: File; - fromMic: boolean; -} - -const MicButton = (props: MicButtonProps) => { - const [mic, setMic] = useState(null); - const [isRecording, setIsRecording] = useState(false); - - const handleRecord = async () => { - setMic(await MicRecorder.start()); - }; - - const handleStop = async () => { - if (!mic) { - return; - } - let recording = await mic.stop(); - let ctx = new AudioContext({ sampleRate: SAMPLE_RATE }); - let resampled = await ctx.decodeAudioData(recording.buffer); - let ch0 = resampled.getChannelData(0); - props.setAudioData(new Float32Array(ch0.buffer)); - - let blob = recording.blob; - props.setAudioMetadata({ - file: new File([blob], "recording.wav"), - fromMic: true, - }); - props.setBlobUrl(URL.createObjectURL(blob)); - setMic(null); - }; - - const handleClick = async () => { - if (isRecording) { - await handleStop(); - } else { - await handleRecord(); - } - setIsRecording(!isRecording); - }; - - return ( -
- -
- ); -}; - -export default MicButton; diff --git a/examples/ratchet-whisper/src/app/components/modelSelector.tsx b/examples/ratchet-whisper/src/app/components/modelSelector.tsx deleted file mode 100644 index b6584ffd..00000000 --- a/examples/ratchet-whisper/src/app/components/modelSelector.tsx +++ /dev/null @@ -1,117 +0,0 @@ -import { useState } from "react"; -import { AvailableModels, Whisper } from "@ratchet-ml/ratchet-web"; - -interface ModelSelectorProps { - selectedModel: AvailableModels | null; - setSelectedModel: (model: AvailableModels) => void; - loaded: boolean; - progress: number; -} - -const UNITS = [ - "byte", - "kilobyte", - "megabyte", - "gigabyte", -]; -const BYTES_PER_KB = 1000; - -export function humanFileSize(sizeBytes: number | bigint): string { - let size = Math.abs(Number(sizeBytes)); - - let u = 0; - while (size >= BYTES_PER_KB && u < UNITS.length - 1) { - size /= BYTES_PER_KB; - ++u; - } - - return new Intl.NumberFormat([], { - style: "unit", - unit: UNITS[u], - unitDisplay: "short", - maximumFractionDigits: 1, - }).format(size); -} - -export function availableModelToString(model: AvailableModels): string { - if ("Whisper" in model) { - return model.Whisper; - } else if ("Llama" in model) { - return model.Llama; - } - return ""; -} - -const ModelSelector = (props: ModelSelectorProps) => { - const { selectedModel, setSelectedModel, loaded, progress } = props; - const [dropdownOpen, setDropdownOpen] = useState(false); - - const whisper = ["tiny", "base", "small", "medium", "large_v2", "large_v3", "distil_large_v3"] as const; - type WhisperIter = typeof whisper[number]; - - const modelNames = [ - ...whisper, - ]; - - const displayModels = () => { - return modelNames.map((model, idx) => ( -
  • - { - const isWhisper = whisper.includes(model as WhisperIter); - if (isWhisper) { - setSelectedModel({ Whisper: model as Whisper }); - } - setDropdownOpen(false); - }} - > - {model} - -
    • - )); - }; - - return ( - <> - {progress > 0 && !loaded && ( -
    - -
    - )} -
    - -
      - {displayModels()} -
    -
    - - ); -}; - -export default ModelSelector; - diff --git a/examples/ratchet-whisper/src/app/components/progressBar.tsx b/examples/ratchet-whisper/src/app/components/progressBar.tsx deleted file mode 100644 index 31fdd199..00000000 --- a/examples/ratchet-whisper/src/app/components/progressBar.tsx +++ /dev/null @@ -1,19 +0,0 @@ -const ProgressBar = ({ progress }: any) => { - return ( - <> - {progress > 0 && progress < 100 && ( -
    -
    -
    -
    -
    - )} - - ); -}; - -export default ProgressBar; - diff --git a/examples/ratchet-whisper/src/app/components/suppressSelector.tsx b/examples/ratchet-whisper/src/app/components/suppressSelector.tsx deleted file mode 100644 index d030be46..00000000 --- a/examples/ratchet-whisper/src/app/components/suppressSelector.tsx +++ /dev/null @@ -1,49 +0,0 @@ -import React, { useState } from "react"; -import { ConfigOptions } from "./configModal"; - -interface SuppressComponentProps { - configOptions: ConfigOptions; - setConfigOptions: React.Dispatch>; -} - -const SuppressComponent = (props: SuppressComponentProps) => { - const [checkedState, setCheckedState] = useState({ - suppress_non_speech: props.configOptions.suppress_non_speech - }); - - const handleOnChange = (event: React.ChangeEvent) => { - setCheckedState({ - ...checkedState, - [event.target.name]: event.target.checked - }); - - props.setConfigOptions({ - ...props.configOptions, - suppress_non_speech: event.target.checked - }); - }; - - return ( -
    - -
    -
    - - -
    -
    -
    - ); -}; - -export default SuppressComponent; - diff --git a/examples/ratchet-whisper/src/app/components/taskSelector.tsx b/examples/ratchet-whisper/src/app/components/taskSelector.tsx deleted file mode 100644 index ff5afd4e..00000000 --- a/examples/ratchet-whisper/src/app/components/taskSelector.tsx +++ /dev/null @@ -1,78 +0,0 @@ -import React, { useState } from "react"; -import { ConfigOptions } from "./configModal"; -import { Task } from "@ratchet-ml/ratchet-web"; - -interface TaskComponentProps { - configOptions: ConfigOptions; - setConfigOptions: React.Dispatch>; -} - -const TaskComponent = (props: TaskComponentProps) => { - let state = { - translate: props.configOptions.task === Task.Translate, - transcribe: props.configOptions.task === Task.Transcribe, - }; - - const [checkedState, setCheckedState] = useState(state); - - const handleOnChange = (event: React.ChangeEvent) => { - setCheckedState({ - ...checkedState, - [event.target.name]: event.target.checked, - }); - if (event.target.name === "translate") - setCheckedState({ - translate: event.target.checked, - transcribe: !event.target.checked, - }); - if (event.target.name === "transcribe") - setCheckedState({ - translate: !event.target.checked, - transcribe: event.target.checked, - }); - props.setConfigOptions((prev: ConfigOptions) => ({ - ...prev, - task: - event.target.name === "translate" - ? Task.Translate - : Task.Transcribe, - })); - }; - - return ( -
    - -
    -
    - - -
    - -
    - - -
    -
    -
    - ); -}; - -export default TaskComponent; diff --git a/examples/ratchet-whisper/src/app/favicon.ico b/examples/ratchet-whisper/src/app/favicon.ico deleted file mode 100644 index 718d6fea4835ec2d246af9800eddb7ffb276240c..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 25931 zcmeHv30#a{`}aL_*G&7qml|y<+KVaDM2m#dVr!KsA!#An?kSQM(q<_dDNCpjEux83 zLb9Z^XxbDl(w>%i@8hT6>)&Gu{h#Oeyszu?xtw#Zb1mO{pgX9699l+Qppw7jXaYf~-84xW z)w4x8?=youko|}Vr~(D$UXIbiXABHh`p1?nn8Po~fxRJv}|0e(BPs|G`(TT%kKVJAdg5*Z|x0leQq0 zkdUBvb#>9F()jo|T~kx@OM8$9wzs~t2l;K=woNssA3l6|sx2r3+kdfVW@e^8e*E}v zA1y5{bRi+3Z`uD3{F7LgFJDdvm;nJilkzDku>BwXH(8ItVCXk*-lSJnR?-2UN%hJ){&rlvg`CDTj z)Bzo!3v7Ou#83zEDEFcKt(f1E0~=rqeEbTnMvWR#{+9pg%7G8y>u1OVRUSoox-ovF z2Ydma(;=YuBY(eI|04{hXzZD6_f(v~H;C~y5=DhAC{MMS>2fm~1H_t2$56pc$NH8( z5bH|<)71dV-_oCHIrzrT`2s-5w_+2CM0$95I6X8p^r!gHp+j_gd;9O<1~CEQQGS8) zS9Qh3#p&JM-G8rHekNmKVewU;pJRcTAog68KYo^dRo}(M>36U4Us zfgYWSiHZL3;lpWT=zNAW>Dh#mB!_@Lg%$ms8N-;aPqMn+C2HqZgz&9~Eu 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transparent, - -30px 10px transparent, - -30px 0px transparent, - -30px -10px transparent, - -20px -20px transparent, - -10px -30px transparent; - } - 6.25% { - box-shadow: - 0px -30px transparent, - 10px -30px #000, - 20px -20px #000, - 30px -10px #000, - 30px 0px #000, - 30px 10px #000, - 20px 20px #000, - 10px 30px #000, - 0px 30px #000, - -10px 30px transparent, - -20px 20px transparent, - -30px 10px transparent, - -30px 0px transparent, - -30px -10px transparent, - -20px -20px transparent, - -10px -30px transparent; - } - 12.5% { - box-shadow: - 0px -30px transparent, - 10px -30px transparent, - 20px -20px #000, - 30px -10px #000, - 30px 0px #000, - 30px 10px #000, - 20px 20px #000, - 10px 30px #000, - 0px 30px #000, - -10px 30px #000, - -20px 20px transparent, - -30px 10px transparent, - -30px 0px transparent, - -30px -10px transparent, - -20px -20px transparent, - -10px -30px transparent; - } - 18.75% { - box-shadow: - 0px -30px transparent, - 10px -30px transparent, - 20px -20px transparent, - 30px -10px #000, - 30px 0px #000, - 30px 10px #000, - 20px 20px #000, - 10px 30px #000, - 0px 30px #000, - -10px 30px #000, - -20px 20px #000, - -30px 10px transparent, - -30px 0px transparent, - -30px -10px transparent, - -20px -20px transparent, - -10px -30px transparent; - } - 25% { - box-shadow: - 0px -30px transparent, - 10px -30px transparent, - 20px -20px transparent, - 30px -10px transparent, - 30px 0px #000, - 30px 10px #000, - 20px 20px #000, - 10px 30px #000, - 0px 30px #000, - -10px 30px #000, - -20px 20px #000, - -30px 10px #000, - -30px 0px transparent, - -30px -10px transparent, - -20px -20px transparent, - -10px -30px transparent; - } - 31.25% { - box-shadow: - 0px -30px transparent, - 10px -30px transparent, - 20px -20px transparent, - 30px -10px transparent, - 30px 0px transparent, - 30px 10px #000, - 20px 20px #000, - 10px 30px #000, - 0px 30px #000, - -10px 30px #000, - -20px 20px #000, - -30px 10px #000, - -30px 0px #000, - -30px -10px transparent, - -20px -20px transparent, - -10px -30px transparent; - } - 37.5% { - box-shadow: - 0px -30px transparent, - 10px -30px transparent, - 20px -20px transparent, - 30px -10px transparent, - 30px 0px transparent, - 30px 10px transparent, - 20px 20px #000, - 10px 30px #000, - 0px 30px #000, - -10px 30px #000, - -20px 20px #000, - -30px 10px #000, - -30px 0px #000, - -30px -10px #000, - -20px -20px transparent, - -10px -30px transparent; - } - 43.75% { - box-shadow: - 0px -30px transparent, - 10px -30px transparent, - 20px -20px transparent, - 30px -10px transparent, - 30px 0px transparent, - 30px 10px transparent, - 20px 20px transparent, - 10px 30px #000, - 0px 30px #000, - -10px 30px #000, - -20px 20px #000, - -30px 10px #000, - -30px 0px #000, - -30px -10px #000, - -20px -20px #000, - -10px -30px transparent; - } - 50% { - box-shadow: - 0px -30px transparent, - 10px -30px transparent, - 20px -20px transparent, - 30px -10px transparent, - 30px 0px transparent, - 30px 10px transparent, - 20px 20px transparent, - 10px 30px transparent, - 0px 30px #000, - -10px 30px #000, - -20px 20px #000, - -30px 10px #000, - -30px 0px #000, - -30px -10px #000, - -20px -20px #000, - -10px -30px #000; - } - 56.25% { - box-shadow: - 0px -30px #000, - 10px -30px transparent, - 20px -20px transparent, - 30px -10px transparent, - 30px 0px transparent, - 30px 10px transparent, - 20px 20px transparent, - 10px 30px transparent, - 0px 30px transparent, - -10px 30px #000, - -20px 20px #000, - -30px 10px #000, - -30px 0px #000, - -30px -10px #000, - -20px -20px #000, - -10px -30px #000; - } - 62.5% { - box-shadow: - 0px -30px #000, - 10px -30px #000, - 20px -20px transparent, - 30px -10px transparent, - 30px 0px transparent, - 30px 10px transparent, - 20px 20px transparent, - 10px 30px transparent, - 0px 30px transparent, - -10px 30px transparent, - -20px 20px #000, - -30px 10px #000, - -30px 0px #000, - -30px -10px #000, - -20px -20px #000, - -10px -30px #000; - } - 68.75% { - box-shadow: - 0px -30px #000, - 10px -30px #000, - 20px -20px #000, - 30px -10px transparent, - 30px 0px transparent, - 30px 10px transparent, - 20px 20px transparent, - 10px 30px transparent, - 0px 30px transparent, - -10px 30px transparent, - -20px 20px transparent, - -30px 10px #000, - -30px 0px #000, - -30px -10px #000, - -20px -20px #000, - -10px -30px #000; - } - 75% { - box-shadow: - 0px -30px #000, - 10px -30px #000, - 20px -20px #000, - 30px -10px #000, - 30px 0px transparent, - 30px 10px transparent, - 20px 20px transparent, - 10px 30px transparent, - 0px 30px transparent, - -10px 30px transparent, - -20px 20px transparent, - -30px 10px transparent, - -30px 0px #000, - -30px -10px #000, - -20px -20px #000, - -10px -30px #000; - } - 81.25% { - box-shadow: - 0px -30px #000, - 10px -30px #000, - 20px -20px #000, - 30px -10px #000, - 30px 0px #000, - 30px 10px transparent, - 20px 20px transparent, - 10px 30px transparent, - 0px 30px transparent, - -10px 30px transparent, - -20px 20px transparent, - -30px 10px transparent, - -30px 0px transparent, - -30px -10px #000, - -20px -20px #000, - -10px -30px #000; - } - 87.5% { - box-shadow: - 0px -30px #000, - 10px -30px #000, - 20px -20px #000, - 30px -10px #000, - 30px 0px #000, - 30px 10px #000, - 20px 20px transparent, - 10px 30px transparent, - 0px 30px transparent, - -10px 30px transparent, - -20px 20px transparent, - -30px 10px transparent, - -30px 0px transparent, - -30px -10px transparent, - -20px -20px #000, - -10px -30px #000; - } - 93.75% { - box-shadow: - 0px -30px #000, - 10px -30px #000, - 20px -20px #000, - 30px -10px #000, - 30px 0px #000, - 30px 10px #000, - 20px 20px #000, - 10px 30px transparent, - 0px 30px transparent, - -10px 30px transparent, - -20px 20px transparent, - -30px 10px transparent, - -30px 0px transparent, - -30px -10px transparent, - -20px -20px transparent, - -10px -30px #000; - } - 100% { - box-shadow: - 0px -30px #000, - 10px -30px #000, - 20px -20px #000, - 30px -10px #000, - 30px 0px #000, - 30px 10px #000, - 20px 20px #000, - 10px 30px #000, - 0px 30px transparent, - -10px 30px transparent, - -20px 20px transparent, - -30px 10px transparent, - -30px 0px transparent, - -30px -10px transparent, - -20px -20px transparent, - -10px -30px transparent; - } -} - diff --git a/examples/ratchet-whisper/src/app/layout.tsx b/examples/ratchet-whisper/src/app/layout.tsx deleted file mode 100644 index 27026da1..00000000 --- a/examples/ratchet-whisper/src/app/layout.tsx +++ /dev/null @@ -1,29 +0,0 @@ -import type { Metadata } from "next"; -import { Inter } from "next/font/google"; -import "./globals.css"; -import { Toaster } from "react-hot-toast"; -import "react-responsive-modal/styles.css"; - -const inter = Inter({ subsets: ["latin"] }); - -export const metadata: Metadata = { - title: "Whisper by Ratchet", - description: "Simple demo of Whisper.", -}; - -export default function RootLayout({ - children, -}: Readonly<{ - children: React.ReactNode; -}>) { - return ( - - -
    - -
    {children}
    -
    - - - ); -} diff --git a/examples/ratchet-whisper/src/app/page.module.css b/examples/ratchet-whisper/src/app/page.module.css deleted file mode 100644 index c13f8527..00000000 --- a/examples/ratchet-whisper/src/app/page.module.css +++ /dev/null @@ -1,236 +0,0 @@ -.main { - display: flex; - flex-direction: column; - justify-content: space-between; - align-items: center; - padding: 6rem; - min-height: 100vh; -} - -.description { - display: inherit; - justify-content: inherit; - align-items: inherit; - font-size: 0.85rem; - max-width: var(--max-width); - width: 100%; - z-index: 2; - font-family: var(--font-mono); -} - -.description a { - display: flex; - justify-content: center; - align-items: center; - gap: 0.5rem; -} - -.description p { - position: relative; - margin: 0; - padding: 1rem; - background-color: rgba(var(--callout-rgb), 0.5); - border: 1px solid rgba(var(--callout-border-rgb), 0.3); - border-radius: var(--border-radius); -} - -.code { - font-weight: 700; - font-family: var(--font-mono); -} - -.grid { - display: grid; - grid-template-columns: repeat(4, minmax(25%, auto)); - max-width: 100%; - width: var(--max-width); -} - -.card { - padding: 1rem 1.2rem; - border-radius: var(--border-radius); - background: rgba(var(--card-rgb), 0); - border: 1px solid rgba(var(--card-border-rgb), 0); - transition: background 200ms, border 200ms; -} - -.card span { - display: inline-block; - transition: transform 200ms; -} - -.card h2 { - font-weight: 600; - margin-bottom: 0.7rem; -} - -.card p { - margin: 0; - opacity: 0.6; - font-size: 0.9rem; - line-height: 1.5; - max-width: 30ch; - text-wrap: balance; -} - -.center { - display: flex; - justify-content: center; - align-items: center; - position: relative; - padding: 4rem 0; -} - -.center::before { - background: var(--secondary-glow); - border-radius: 50%; - width: 480px; - height: 360px; - margin-left: -400px; -} - -.center::after { - background: var(--primary-glow); - width: 240px; - height: 180px; - z-index: -1; -} - -.center::before, -.center::after { - content: ""; - left: 50%; - position: absolute; - filter: blur(45px); - transform: translateZ(0); -} - -.logo { - position: relative; -} -/* Enable hover only on non-touch devices */ -@media (hover: hover) and (pointer: fine) { - .card:hover { - background: rgba(var(--card-rgb), 0.1); - border: 1px solid rgba(var(--card-border-rgb), 0.15); - } - - .card:hover span { - transform: translateX(4px); - } -} - -@media (prefers-reduced-motion) { - .card:hover span { - transform: none; - } -} - -/* Mobile */ -@media (max-width: 700px) { - .content { - padding: 4rem; - } - - .grid { - grid-template-columns: 1fr; - margin-bottom: 120px; - max-width: 320px; - text-align: center; - } - - .card { - padding: 1rem 2.5rem; - } - - .card h2 { - margin-bottom: 0.5rem; - } - - .center { - padding: 8rem 0 6rem; - } - - .center::before { - transform: none; - height: 300px; - } - - .description { - font-size: 0.8rem; - } - - .description a { - padding: 1rem; - } - - .description p, - .description div { - display: flex; - justify-content: center; - position: fixed; - width: 100%; - } - - .description p { - align-items: center; - inset: 0 0 auto; - padding: 2rem 1rem 1.4rem; - border-radius: 0; - border: none; - border-bottom: 1px solid rgba(var(--callout-border-rgb), 0.25); - background: linear-gradient( - to bottom, - rgba(var(--background-start-rgb), 1), - rgba(var(--callout-rgb), 0.5) - ); - background-clip: padding-box; - backdrop-filter: blur(24px); - } - - .description div { - align-items: flex-end; - pointer-events: none; - inset: auto 0 0; - padding: 2rem; - height: 200px; - background: linear-gradient( - to bottom, - transparent 0%, - rgb(var(--background-end-rgb)) 40% - ); - z-index: 1; - } -} - -/* Tablet and Smaller Desktop */ -@media (min-width: 701px) and (max-width: 1120px) { - .grid { - grid-template-columns: repeat(2, 50%); - } -} - -@media (prefers-color-scheme: dark) { - .vercelLogo { - filter: invert(1); - } - - .logo { - filter: invert(1) drop-shadow(0 0 0.3rem #ffffff70); - } -} - -@keyframes rotate { - from { - transform: rotate(360deg); - } - to { - transform: rotate(0deg); - } -} - -.buttonsContainer { - display: flex; - justify-content: center; /* Center buttons horizontally */ - gap: 10px; /* Add some space between the buttons */ -} diff --git a/examples/ratchet-whisper/src/app/page.tsx b/examples/ratchet-whisper/src/app/page.tsx deleted file mode 100644 index 1dd31ef9..00000000 --- a/examples/ratchet-whisper/src/app/page.tsx +++ /dev/null @@ -1,254 +0,0 @@ -'use client' -import { FFmpeg } from '@ffmpeg/ffmpeg' -import { toBlobURL } from '@ffmpeg/util'; -import { useEffect, useRef, useState } from "react"; -import { Model, DecodingOptionsBuilder, default as init, Task, AvailableModels, Quantization, Segment } from "@ratchet-ml/ratchet-web"; -import ConfigModal, { ConfigOptions } from './components/configModal'; -import ModelSelector from './components/modelSelector'; -import ProgressBar from './components/progressBar'; -import MicButton, { AudioMetadata } from './components/micButton'; -import toast from "react-hot-toast"; -import WebGPUModal from './components/WebGPUModal'; - -export default function Home() { - const [selectedModel, setSelectedModel] = useState({ Whisper: "tiny" }); - const [loadedModel, setLoadedModel] = useState(null); - const [model, setModel] = useState(null); - - const ffmpegRef = useRef(new FFmpeg()); - const [ffmpegLoaded, setFFmpegLoaded] = useState(false); - const [blobURL, setBlobURL] = useState(); - const [audioData, setAudioData] = useState(null); - const [audioMetadata, setAudioMetadata] = useState(null); - const [segments, setSegments] = useState([]); - const [isConfigOpen, setIsConfigOpen] = useState(false); - const [configOptions, setConfigOptions] = useState({ - language: null, - task: Task.Transcribe, - suppress_non_speech: true, - }); - const [generating, setGenerating] = useState(false); - const [progress, setProgress] = useState(0); - - - useEffect(() => { - (async () => { - await init(); - })(); - }, []) - - async function loadModel() { - setModel(await Model.load(selectedModel, Quantization.Q8_0, (p: number) => setProgress(p))); - setLoadedModel(selectedModel); - setProgress(0); - } - - const loadFFMPEG = async () => { - console.log("Loading FFmpeg"); - const baseURL = 'https://unpkg.com/@ratchet-ml/ffmpeg-core@0.0.12/dist/umd'; - const ffmpeg = ffmpegRef.current; - ffmpeg.on('log', ({ message }) => { - console.log(message); - }); - await ffmpeg.load({ - coreURL: await toBlobURL(`${baseURL}/ffmpeg-core.js`, 'text/javascript'), - wasmURL: await toBlobURL(`${baseURL}/ffmpeg-core.wasm`, 'application/wasm'), - }); - setFFmpegLoaded(true); - } - - function pcm16ToIntFloat32(pcmData: Uint8Array) { - let int16Array = new Int16Array(pcmData); - let float32Array = new Float32Array(int16Array.length); - for (let i = 0; i < int16Array.length; i++) { - float32Array[i] = int16Array[i] / 32768.0; - } - return float32Array; - } - - const transcode = async (audioData: Uint8Array) => { - if (!ffmpegLoaded) { - await loadFFMPEG(); - } - const ffmpeg = ffmpegRef.current; - await ffmpeg.writeFile('input', audioData); - - const cmd = [ - "-nostdin", - "-threads", "0", - "-i", "input", - "-f", "s16le", - "-ac", "1", - "-acodec", "pcm_s16le", - "-loglevel", "debug", - "-ar", "16000", - "output.pcm" - ]; - - await ffmpeg.exec(cmd); - const data = (await ffmpeg.readFile('output.pcm')) as any; - setBlobURL(URL.createObjectURL(new Blob([data.buffer], { type: 'audio/wav' }))); - return data.buffer; - }; - - - async function runModel() { - if (!model || !audioData || generating) { - return - } - setGenerating(true); - setSegments([]); - let builder = new DecodingOptionsBuilder(); - let options = builder - .setLanguage(configOptions.language ? configOptions.language : "en") - .setTask(configOptions.task) - .setSuppressBlank(configOptions.suppress_non_speech) - .build(); - console.log("Options: ", options); - let callback = (segment: Segment) => { - if (segment.last) { - setGenerating(false); - return; - } - setSegments((currentSegments) => [...currentSegments, segment]); - }; - let result = await model.run({ audio: audioData, decode_options: options, callback: callback }); - console.log("Result: ", result); - console.log("Processing time: ", result.processing_time); - } - - const handleAudioFile = () => async (event: any) => { - const file = event.target.files[0]; - if (!file) { - return; - } - const reader = new FileReader(); - reader.onload = async () => { - let audioBytes = new Uint8Array(reader.result as ArrayBuffer); - let transcoded = await toast.promise( - transcode(audioBytes), - { - loading: 'Transcoding audio...', - success: Transcoded successfully!, - error: Failed to transcode., - } - ); - setAudioData(pcm16ToIntFloat32(transcoded)); - setAudioMetadata({ - file: file, - fromMic: false, - }); - setBlobURL(URL.createObjectURL(file)); - }; - reader.readAsArrayBuffer(file); - }; - - - return ( - <> - -

    Whisper + Ratchet

    -
    -
    - - {progress > 0 && progress < 100 ? : <>} - {loadedModel != selectedModel ? : - <>} -
    -
    - - - -
    - -
    - {blobURL && ( -
    - - -
    - )} - -
    - - -
    -
    -
    -
    - {segments && - segments.map( - (segment: Segment) => { - return ( -
    -
    - {segment.start} - {" -> "} - {segment.stop} -
    -
    - {segment.text} -
    -
    - ); - } - )} -
    -
    -
    - - - ); -} diff --git a/examples/ratchet-whisper/tailwind.config.js b/examples/ratchet-whisper/tailwind.config.js deleted file mode 100644 index f03d9221..00000000 --- a/examples/ratchet-whisper/tailwind.config.js +++ /dev/null @@ -1,10 +0,0 @@ -/** @type {import('tailwindcss').Config} */ -module.exports = { - content: [ - "./src/**/*.{js,ts,jsx,tsx,mdx}", - ], - theme: { - extend: {}, - }, - plugins: [], -} diff --git a/examples/ratchet-whisper/tsconfig.json b/examples/ratchet-whisper/tsconfig.json deleted file mode 100644 index 7b285893..00000000 --- a/examples/ratchet-whisper/tsconfig.json +++ /dev/null @@ -1,26 +0,0 @@ -{ - "compilerOptions": { - "lib": ["dom", "dom.iterable", "esnext"], - "allowJs": true, - "skipLibCheck": true, - "strict": true, - "noEmit": true, - "esModuleInterop": true, - "module": "esnext", - "moduleResolution": "bundler", - "resolveJsonModule": true, - "isolatedModules": true, - "jsx": "preserve", - "incremental": true, - "plugins": [ - { - "name": "next" - } - ], - "paths": { - "@/*": ["./src/*"] - } - }, - "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"], - "exclude": ["node_modules"] -} diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml index 687c2abf..e62ae23b 100644 --- a/pnpm-lock.yaml +++ b/pnpm-lock.yaml @@ -137,58 +137,6 @@ importers: specifier: ^3.4.1 version: 3.4.1(vite@6.1.0) - examples/ratchet-whisper: - dependencies: - '@ffmpeg/ffmpeg': - specifier: 0.12.6 - version: 0.12.6 - '@ffmpeg/util': - specifier: ^0.12.1 - version: 0.12.1 - '@ratchet-ml/ratchet-web': - specifier: link:../../target/pkg/ratchet-web - version: link:../../target/pkg/ratchet-web - fix-webm-duration: - specifier: ^1.0.5 - version: 1.0.5 - next: - specifier: 14.1.0 - version: 14.1.0(react-dom@18.2.0)(react@18.2.0) - react: - specifier: ^18.2.0 - version: 18.2.0 - react-dom: - specifier: ^18.2.0 - version: 18.2.0(react@18.2.0) - react-hot-toast: - specifier: ^2.4.1 - version: 2.4.1(csstype@3.1.3)(react-dom@18.2.0)(react@18.2.0) - react-responsive-modal: - specifier: ^6.4.2 - version: 6.4.2(react-dom@18.2.0)(react@18.2.0) - devDependencies: - '@types/node': - specifier: ^20.11.24 - version: 20.11.24 - '@types/react': - specifier: ^18.2.61 - version: 18.2.61 - '@types/react-dom': - specifier: ^18.2.19 - version: 18.2.19 - autoprefixer: - specifier: ^10.4.18 - version: 10.4.18(postcss@8.4.35) - postcss: - specifier: ^8.4.35 - version: 8.4.35 - tailwindcss: - specifier: ^3.4.1 - version: 3.4.1 - typescript: - specifier: ^5.3.3 - version: 5.3.3 - packages: /@alloc/quick-lru@5.2.0: diff --git a/pnpm-workspace.yaml b/pnpm-workspace.yaml index aceecd09..8d71655d 100644 --- a/pnpm-workspace.yaml +++ b/pnpm-workspace.yaml @@ -1,3 +1,2 @@ packages: - - "examples/ratchet-whisper" - "examples/ratchet-phi" diff --git a/requirements.txt b/requirements.txt index aa835c00..ef00ccb9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,5 +3,4 @@ numpy==1.24.3 torch==2.3.0 requests==2.26.0 mlx==0.9.1; sys_platform == 'darwin' -git+https://github.com/FL33TW00D/whisper.git@feature/reference#egg=openai-whisper gguf==0.6.0 From 3612130f52bc729a267cbc0b4384a608aae4ffde Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:30:05 -0700 Subject: [PATCH 116/146] Update pnpm-lock.yaml --- pnpm-lock.yaml | 2288 ++---------------------------------------------- 1 file changed, 63 insertions(+), 2225 deletions(-) diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml index e62ae23b..d3f58d4b 100644 --- a/pnpm-lock.yaml +++ b/pnpm-lock.yaml @@ -4,6 +4,9 @@ settings: autoInstallPeers: true excludeLinksFromLockfile: false +onlyBuiltDependencies: + - esbuild + importers: .: @@ -67,76 +70,6 @@ importers: specifier: ^5.3.3 version: 5.3.3 - examples/ratchet-train-toy: - dependencies: - chart.js: - specifier: ^4.4.7 - version: 4.4.7 - mathjs: - specifier: ^14.2.1 - version: 14.2.1 - devDependencies: - '@eslint/compat': - specifier: ^1.2.5 - version: 1.2.6(eslint@9.20.1) - '@eslint/js': - specifier: ^9.18.0 - version: 9.20.0 - '@sveltejs/adapter-static': - specifier: ^3.0.8 - version: 3.0.8(@sveltejs/kit@2.17.2) - '@sveltejs/kit': - specifier: ^2.16.0 - version: 2.17.2(@sveltejs/vite-plugin-svelte@5.0.3)(svelte@5.20.1)(vite@6.1.0) - '@sveltejs/vite-plugin-svelte': - specifier: ^5.0.0 - version: 5.0.3(svelte@5.20.1)(vite@6.1.0) - '@tailwindcss/vite': - specifier: ^4.0.0 - version: 4.0.6(vite@6.1.0) - eslint: - specifier: ^9.18.0 - version: 9.20.1 - eslint-config-prettier: - specifier: ^10.0.1 - version: 10.0.1(eslint@9.20.1) - eslint-plugin-svelte: - specifier: ^2.46.1 - version: 2.46.1(eslint@9.20.1)(svelte@5.20.1) - globals: - specifier: ^15.14.0 - version: 15.15.0 - prettier: - specifier: ^3.4.2 - version: 3.5.1 - prettier-plugin-svelte: - specifier: ^3.3.3 - version: 3.3.3(prettier@3.5.1)(svelte@5.20.1) - svelte: - specifier: ^5.0.0 - version: 5.20.1 - svelte-check: - specifier: ^4.0.0 - version: 4.1.4(svelte@5.20.1)(typescript@5.3.3) - tailwindcss: - specifier: ^4.0.0 - version: 4.0.6 - typescript: - specifier: ^5.0.0 - version: 5.3.3 - typescript-eslint: - specifier: ^8.20.0 - version: 8.24.1(eslint@9.20.1)(typescript@5.3.3) - vite: - specifier: ^6.1.0 - version: 6.1.0 - vite-plugin-top-level-await: - specifier: ^1.4.4 - version: 1.5.0(vite@6.1.0) - vite-plugin-wasm: - specifier: ^3.4.1 - version: 3.4.1(vite@6.1.0) - packages: /@alloc/quick-lru@5.2.0: @@ -144,21 +77,6 @@ packages: engines: {node: '>=10'} dev: true - /@ampproject/remapping@2.3.0: - resolution: {integrity: sha512-30iZtAPgz+LTIYoeivqYo853f02jBYSd5uGnGpkFV0M3xOt9aN73erkgYAmZU43x4VfqcnLxW9Kpg3R5LC4YYw==} - engines: {node: '>=6.0.0'} - dependencies: - '@jridgewell/gen-mapping': 0.3.5 - 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Do not use it. 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'>=20'} From c762ca366e8b6cd11bd0d8ca91db9a38b3c9aa5b Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:32:01 -0700 Subject: [PATCH 117/146] config.toml formatting --- .cargo/config.toml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.cargo/config.toml b/.cargo/config.toml index a14c7a91..1ecf5a7b 100644 --- a/.cargo/config.toml +++ b/.cargo/config.toml @@ -1,5 +1,5 @@ # Needed for WASM unstable features [build] -rustflags = [ "--cfg=web_sys_unstable_apis" ] -rustdocflags = [ "--cfg=web_sys_unstable_apis" ] +rustflags = ["--cfg=web_sys_unstable_apis"] +rustdocflags = ["--cfg=web_sys_unstable_apis"] target = "wasm32-unknown-unknown" From 9c4204f800466afc04a2f2e87c6a27535a15a14b Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:34:43 -0700 Subject: [PATCH 118/146] Remove debug I don't like --- crates/ratchet-nn/src/kv_cache.rs | 1 - 1 file changed, 1 deletion(-) diff --git a/crates/ratchet-nn/src/kv_cache.rs b/crates/ratchet-nn/src/kv_cache.rs index 5d8a24fc..4d1456e1 100644 --- a/crates/ratchet-nn/src/kv_cache.rs +++ b/crates/ratchet-nn/src/kv_cache.rs @@ -104,7 +104,6 @@ impl KVCache { Ok(mask.clone()) } else { log::debug!("Creating mask for {:?}", t); - log::debug!("masks: {:?}", self.masks); let ones = Tensor::ones::(&shape![t, t], &self.device); let mask = ones.tril(None)?; self.masks.insert(t, mask.clone()); From e141eb7027401182885adafff6e762fd226cb759 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:39:04 -0700 Subject: [PATCH 119/146] Add simple caching sanity check --- crates/ratchet-core/tests/caching.rs | 43 ++++++++++++++++++++++++++++ 1 file changed, 43 insertions(+) create mode 100644 crates/ratchet-core/tests/caching.rs diff --git a/crates/ratchet-core/tests/caching.rs b/crates/ratchet-core/tests/caching.rs new file mode 100644 index 00000000..c31decc4 --- /dev/null +++ b/crates/ratchet-core/tests/caching.rs @@ -0,0 +1,43 @@ +// TODO(vinhowe): Remove or motivate this test +#[test] +fn test_simple_caching() -> anyhow::Result<()> { + let _ = env_logger::builder().is_test(true).try_init(); + + let device = Device::request_device(DeviceRequest::GPU).unwrap(); + let t1 = Tensor::from_data(vec![1f32], shape![1], Device::CPU) + .to(&device)? + .square()?; + println!("t1: {:?}", t1.to(&Device::CPU)?.to_vec::()?); + + assert_eq!(t1.to(&Device::CPU)?.to_vec::()?, vec![1f32]); + + let t2 = Tensor::from_data(vec![2f32], shape![1], Device::CPU) + .to(&device)? + .square()?; + println!("t2: {:?}", t2.to(&Device::CPU)?.to_vec::()?); + + assert_eq!(t2.to(&Device::CPU)?.to_vec::()?, vec![4f32]); + + let t3 = Tensor::from_data(vec![3f32], shape![1], Device::CPU) + .to(&device)? + .square()?; + println!("t3: {:?}", t3.to(&Device::CPU)?.to_vec::()?); + + assert_eq!(t3.to(&Device::CPU)?.to_vec::()?, vec![9f32]); + + let t4 = Tensor::from_data(vec![4f32], shape![1], Device::CPU) + .to(&device)? + .square()?; + println!("t4: {:?}", t4.to(&Device::CPU)?.to_vec::()?); + + assert_eq!(t4.to(&Device::CPU)?.to_vec::()?, vec![16f32]); + + let t5 = Tensor::from_data(vec![5f32], shape![1], Device::CPU) + .to(&device)? + .square()?; + println!("t5: {:?}", t5.to(&Device::CPU)?.to_vec::()?); + + assert_eq!(t5.to(&Device::CPU)?.to_vec::()?, vec![25f32]); + + Ok(()) +} From 6ddc9c516563ae6d22a38056a4ba3aa005dacc88 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:40:35 -0700 Subject: [PATCH 120/146] Comment this assertion for now; might be important --- .../src/gpu/buffer_allocator/allocator.rs | 38 +++++++++---------- 1 file changed, 19 insertions(+), 19 deletions(-) diff --git a/crates/ratchet-core/src/gpu/buffer_allocator/allocator.rs b/crates/ratchet-core/src/gpu/buffer_allocator/allocator.rs index 907c6ea2..aafc74c7 100644 --- a/crates/ratchet-core/src/gpu/buffer_allocator/allocator.rs +++ b/crates/ratchet-core/src/gpu/buffer_allocator/allocator.rs @@ -409,25 +409,25 @@ impl BufferAllocator { assignments.insert(output.id(), output_buffer); } - #[cfg(debug_assertions)] - { - let mut output_allocations = BTreeMap::new(); - for t in execution_order.iter() { - if let Some(allocation) = assignments.get(&t.id()) { - if output_tensors.contains_key(&t.id()) { - output_allocations.insert(allocation.global_id(), t.id()); - } else if let Some(output_id) = output_allocations.get(&allocation.global_id()) - { - panic!( - "Allocation {:?} used by output tensor {:?} was reused by tensor {:?}", - allocation.global_id(), - output_id, - t.id() - ); - } - } - } - } + // #[cfg(debug_assertions)] + // { + // let mut output_allocations = BTreeMap::new(); + // for t in execution_order.iter() { + // if let Some(allocation) = assignments.get(&t.id()) { + // if output_tensors.contains_key(&t.id()) { + // output_allocations.insert(allocation.global_id(), t.id()); + // } else if let Some(output_id) = output_allocations.get(&allocation.global_id()) + // { + // panic!( + // "Allocation {:?} used by output tensor {:?} was reused by tensor {:?}", + // allocation.global_id(), + // output_id, + // t.id() + // ); + // } + // } + // } + // } log::debug!( "Total bytes allocated: {}kb", From 7ede0c0d389c5715dfe19add2b93378820e2f2a8 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:44:22 -0700 Subject: [PATCH 121/146] Ignore samply profiles --- .gitignore | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.gitignore b/.gitignore index 3ffe4ce7..eb6fee90 100644 --- a/.gitignore +++ b/.gitignore @@ -30,3 +30,6 @@ venv/ # proptest regression tests proptest-regressions/ + +# samply profile +profile.json From a6cd2327d1543203835728ca3dcbfe29fcafbeee Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:51:11 -0700 Subject: [PATCH 122/146] Ignore webdriver configs --- .gitignore | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.gitignore b/.gitignore index eb6fee90..ed4b9df2 100644 --- a/.gitignore +++ b/.gitignore @@ -33,3 +33,6 @@ proptest-regressions/ # samply profile profile.json + +# webdriver configs +webdriver.json From 8da3a84311b02467e5fd502bf294a512e841f8b9 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:52:59 -0700 Subject: [PATCH 123/146] Check in impl of async/future buffer syncing --- crates/ratchet-core/src/executable.rs | 60 +++++++++++++++++++++++++++ 1 file changed, 60 insertions(+) diff --git a/crates/ratchet-core/src/executable.rs b/crates/ratchet-core/src/executable.rs index 8f1fbae3..61a0f549 100644 --- a/crates/ratchet-core/src/executable.rs +++ b/crates/ratchet-core/src/executable.rs @@ -257,6 +257,66 @@ impl Executable { None }; + // let cpu_bufs = if let Some(debug_list) = &self.debug_list { + // let cpu_bufs = Arc::new(RwLock::new(HashMap::with_capacity_and_hasher( + // debug_list.len(), + // Default::default(), + // ))); + + // #[cfg(target_arch = "wasm32")] + // let mut buf_futures = vec![]; + + // // Dump all of our debug results + // for step in debug_steps.iter() { + // let d = device.clone(); + // let dt = debug_list + // .get(&step.tensor_id.expect("Tensor id is not set")) + // .expect("Tensor not found in debug list") + // .dt(); + // let tensor_id = step.tensor_id.expect("Tensor id is not set"); + // let debug_buffer = step.debug_buffer.clone().expect("Debug buffer is not set"); + // let alignment = dt.size_of(); + + // #[maybe_async] + // async fn buffer_fn( + // d: WgpuDevice, + // debug_buffer: Arc, + // alignment: usize, + // ) -> CPUBuffer { + // wgpu_buffer_to_cpu_buffer(debug_buffer.as_ref(), alignment, None, &d).await + // } + + // #[cfg(target_arch = "wasm32")] + // { + // let cpu_bufs = cpu_bufs.clone(); + // let future = async move { + // let cpu_buf = buffer_fn(d, debug_buffer, alignment).await; + // cpu_bufs.write().insert(tensor_id, cpu_buf); + // }; + // buf_futures.push(future); + // } + + // #[cfg(not(target_arch = "wasm32"))] + // { + // let cpu_buf = buffer_fn(d, debug_buffer, alignment); + // cpu_bufs.write().insert(tensor_id, cpu_buf); + // } + // } + + // #[cfg(target_arch = "wasm32")] + // { + // futures::future::join_all(buf_futures).await; + // } + + // log::debug!("Created {} debug cpu buffers", cpu_bufs.read().len()); + + // Some(Arc::try_unwrap(cpu_bufs).unwrap().into_inner()) + // } else { + // None + // }; + + // log::error!("GPU bufs: {:?}", gpu_bufs.as_ref().map(|m| m.len())); + Ok(( index, ExecutionResult { From d2cda0eaf46f3cd4c9a2ef51cd7886e59ccd0d72 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:53:11 -0700 Subject: [PATCH 124/146] Revert "Check in impl of async/future buffer syncing" This reverts commit 8da3a84311b02467e5fd502bf294a512e841f8b9. --- crates/ratchet-core/src/executable.rs | 60 --------------------------- 1 file changed, 60 deletions(-) diff --git a/crates/ratchet-core/src/executable.rs b/crates/ratchet-core/src/executable.rs index 61a0f549..8f1fbae3 100644 --- a/crates/ratchet-core/src/executable.rs +++ b/crates/ratchet-core/src/executable.rs @@ -257,66 +257,6 @@ impl Executable { None }; - // let cpu_bufs = if let Some(debug_list) = &self.debug_list { - // let cpu_bufs = Arc::new(RwLock::new(HashMap::with_capacity_and_hasher( - // debug_list.len(), - // Default::default(), - // ))); - - // #[cfg(target_arch = "wasm32")] - // let mut buf_futures = vec![]; - - // // Dump all of our debug results - // for step in debug_steps.iter() { - // let d = device.clone(); - // let dt = debug_list - // .get(&step.tensor_id.expect("Tensor id is not set")) - // .expect("Tensor not found in debug list") - // .dt(); - // let tensor_id = step.tensor_id.expect("Tensor id is not set"); - // let debug_buffer = step.debug_buffer.clone().expect("Debug buffer is not set"); - // let alignment = dt.size_of(); - - // #[maybe_async] - // async fn buffer_fn( - // d: WgpuDevice, - // debug_buffer: Arc, - // alignment: usize, - // ) -> CPUBuffer { - // wgpu_buffer_to_cpu_buffer(debug_buffer.as_ref(), alignment, None, &d).await - // } - - // #[cfg(target_arch = "wasm32")] - // { - // let cpu_bufs = cpu_bufs.clone(); - // let future = async move { - // let cpu_buf = buffer_fn(d, debug_buffer, alignment).await; - // cpu_bufs.write().insert(tensor_id, cpu_buf); - // }; - // buf_futures.push(future); - // } - - // #[cfg(not(target_arch = "wasm32"))] - // { - // let cpu_buf = buffer_fn(d, debug_buffer, alignment); - // cpu_bufs.write().insert(tensor_id, cpu_buf); - // } - // } - - // #[cfg(target_arch = "wasm32")] - // { - // futures::future::join_all(buf_futures).await; - // } - - // log::debug!("Created {} debug cpu buffers", cpu_bufs.read().len()); - - // Some(Arc::try_unwrap(cpu_bufs).unwrap().into_inner()) - // } else { - // None - // }; - - // log::error!("GPU bufs: {:?}", gpu_bufs.as_ref().map(|m| m.len())); - Ok(( index, ExecutionResult { From dc93a42e3b6c53dfccf2158b6bc87909cb30a566 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:56:56 -0700 Subject: [PATCH 125/146] Remove moondream impl --- crates/ratchet-models/src/lib.rs | 1 - .../ratchet-models/src/moondream/generate.rs | 207 - crates/ratchet-models/src/moondream/mlp.rs | 18 - crates/ratchet-models/src/moondream/mod.rs | 8 - crates/ratchet-models/src/moondream/model.rs | 284 - .../src/moondream/text_model.rs | 192 - .../src/moondream/vision_encoder.rs | 173 - crates/ratchet-models/src/registry.rs | 3 - crates/ratchet-web/src/model.rs | 34 - examples/ratchet-moondream/.gitignore | 23 - examples/ratchet-moondream/README.md | 30 - examples/ratchet-moondream/package-lock.json | 18080 ---------------- examples/ratchet-moondream/package.json | 43 - examples/ratchet-moondream/public/index.html | 27 - .../ratchet-moondream/public/manifest.json | 25 - examples/ratchet-moondream/public/robots.txt | 3 - examples/ratchet-moondream/src/App.css | 38 - examples/ratchet-moondream/src/App.js | 242 - examples/ratchet-moondream/src/index.css | 13 - examples/ratchet-moondream/src/index.js | 11 - 20 files changed, 19455 deletions(-) delete mode 100644 crates/ratchet-models/src/moondream/generate.rs delete mode 100644 crates/ratchet-models/src/moondream/mlp.rs delete mode 100644 crates/ratchet-models/src/moondream/mod.rs delete mode 100644 crates/ratchet-models/src/moondream/model.rs delete mode 100644 crates/ratchet-models/src/moondream/text_model.rs delete mode 100644 crates/ratchet-models/src/moondream/vision_encoder.rs delete mode 100644 examples/ratchet-moondream/.gitignore delete mode 100644 examples/ratchet-moondream/README.md delete mode 100644 examples/ratchet-moondream/package-lock.json delete mode 100644 examples/ratchet-moondream/package.json delete mode 100644 examples/ratchet-moondream/public/index.html delete mode 100644 examples/ratchet-moondream/public/manifest.json delete mode 100644 examples/ratchet-moondream/public/robots.txt delete mode 100644 examples/ratchet-moondream/src/App.css delete mode 100644 examples/ratchet-moondream/src/App.js delete mode 100644 examples/ratchet-moondream/src/index.css delete mode 100644 examples/ratchet-moondream/src/index.js diff --git a/crates/ratchet-models/src/lib.rs b/crates/ratchet-models/src/lib.rs index 956d80ff..f9ed2527 100644 --- a/crates/ratchet-models/src/lib.rs +++ b/crates/ratchet-models/src/lib.rs @@ -1,6 +1,5 @@ #![allow(clippy::upper_case_acronyms)] pub mod gpt2; -// pub mod moondream; // pub mod phi2; // pub mod phi3; pub mod registry; diff --git a/crates/ratchet-models/src/moondream/generate.rs b/crates/ratchet-models/src/moondream/generate.rs deleted file mode 100644 index 2a97b599..00000000 --- a/crates/ratchet-models/src/moondream/generate.rs +++ /dev/null @@ -1,207 +0,0 @@ -use super::model::Moondream; -use crate::TokenOutputStream; -use ndarray::Axis; -use ndarray_stats::QuantileExt; -use ratchet::shape; -use ratchet::Device; -use ratchet::Tensor; -use ratchet_nn::Module; -use tokenizers::Tokenizer; - -#[cfg(not(target_arch = "wasm32"))] -pub fn generate( - model: &mut Moondream, - image_bytes: &[u8], - question: String, - tokenizer: Tokenizer, - callback: impl Fn(String), -) -> anyhow::Result<()> { - use ratchet::rvec; - use web_time::Instant; - let device = model.text_model.device.clone(); - - let prompt = format!("\n\nQuestion: {}\n\nAnswer:", question); - log::warn!("Prompt: {}", prompt); - - let mut tos = TokenOutputStream::new(tokenizer); - - let img = image::ImageReader::new(std::io::Cursor::new(image_bytes)) - .with_guessed_format()? - .decode() - .unwrap() - .resize_to_fill(378, 378, image::imageops::FilterType::Triangle); // Adjusted to 378x378 - - let pixels: Vec<_> = img - .to_rgb8() - .to_vec() - .iter() - .map(|&x| (x as f32 / 255.0)) - .collect(); - - let img_tensor = Tensor::from_data(pixels, shape![378, 378, 3], device.clone()) - .permute(&[2, 0, 1])? - .view(shape![1, 3, 378, 378])? - .cast(device.compute_precision())?; - - let img_embed = model.vision_encoder.schedule(img_tensor)?.resolve()?; - - let bos_token = model - .text_model - .embedding - .schedule(Tensor::from_data([50256], shape![1], device.clone()))? - .view(shape![1, 1, 2048])?; - - let encoding = tos.tokenizer().encode(prompt, false).unwrap(); - - let mut tokens = encoding - .get_ids() - .iter() - .map(|&x| x as i32) - .collect::>(); - - let mut all_tokens = tokens.clone(); - - let start = Instant::now(); - let mut generated_tokens = vec![]; - while *tokens.last().unwrap() != 50256 { - let input = Tensor::from_data(tokens.clone(), shape![1, tokens.len()], device.clone()); - let mut embeds: Tensor; - if generated_tokens.is_empty() { - embeds = model.text_model.embedding.schedule(input)?; - embeds = Tensor::cat( - rvec![bos_token.clone(), img_embed.clone(), embeds.clone()], - 1, - )?; - } else { - embeds = model.text_model.embedding.schedule(input).unwrap(); - } - - let result = model - .text_model - .schedule(embeds.clone())? - .full()? - .resolve()?; - - model.text_model.cache_mut().update(embeds.shape()[1]); - - let logits = result.to(&Device::CPU).unwrap(); - let next_tokens = logits - .to_ndarray_view::() - .map_axis(Axis(2), |row| row.argmax_skipnan().unwrap()) - .iter() - .map(|&x| x as i32) - .collect::>(); - tokens = next_tokens.clone(); - generated_tokens.extend(next_tokens.clone()); - all_tokens.extend(next_tokens.clone()); - - if let Some(t) = tos.next_token(next_tokens[0] as u32)? { - callback(t); - } - } - - let elapsed = start.elapsed(); - log::warn!("Elapsed: {:?}", elapsed); - log::warn!("Tok/s {}", all_tokens.len() as f64 / elapsed.as_secs_f64()); - model.text_model.reset(); - Ok(()) -} - -#[cfg(target_arch = "wasm32")] -pub async fn generate( - model: &mut Moondream, - image_bytes: Vec, - question: String, - tokenizer: Tokenizer, - callback: impl Fn(String), -) -> anyhow::Result<()> { - use web_time::Instant; - let device = model.text_model.device.clone(); - - let img = image::io::Reader::new(std::io::Cursor::new(image_bytes)) - .with_guessed_format()? - .decode() - .unwrap() - .resize_to_fill(378, 378, image::imageops::FilterType::Triangle); // Adjusted to 378x378 - - let prompt = format!("\n\nQuestion: {}\n\nAnswer:", question); - log::warn!("Prompt: {}", prompt); - - let mut tos = TokenOutputStream::new(tokenizer); - - let pixels: Vec<_> = img - .to_rgb8() - .to_vec() - .iter() - .map(|&x| (x as f32 / 255.0)) - .collect(); - - let img_tensor = Tensor::from_data(&pixels, shape![378, 378, 3], device.clone()) - .permute(&[2, 0, 1])? - .view(shape![1, 3, 378, 378])?; - - let img_embed = model.vision_encoder.schedule(img_tensor)?.resolve()?; - - let bos_token = model - .text_model - .embedding - .schedule(Tensor::from_data([50256], shape![1], device.clone()))? - .view(shape![1, 1, 2048])?; - - let encoding = tos.tokenizer().encode(prompt, false).unwrap(); - - let mut tokens = encoding - .get_ids() - .iter() - .map(|&x| x as i32) - .collect::>(); - - let mut all_tokens = tokens.clone(); - - let start = Instant::now(); - let mut generated_tokens = vec![]; - while *tokens.last().unwrap() != 50256 { - let input = Tensor::from_data(tokens.clone(), shape![1, tokens.len()], device.clone()); - let mut embeds: Tensor; - if generated_tokens.len() == 0 { - embeds = model.text_model.embedding.schedule(input).unwrap(); - embeds = Tensor::cat( - vec![bos_token.clone(), img_embed.clone(), embeds.clone()].into(), - 1, - ) - .unwrap(); - } else { - embeds = model.text_model.embedding.schedule(input).unwrap(); - } - - let result = model - .text_model - .schedule(embeds.clone())? - .full()? - .resolve()?; - - model.text_model.cache_mut().update(embeds.shape()[1]); - - let logits = result.to(&Device::CPU).await.unwrap(); - let next_tokens = logits - .to_ndarray_view::() - .map_axis(Axis(2), |row| row.argmax_skipnan().unwrap()) - .iter() - .map(|&x| x as i32) - .collect::>(); - tokens = next_tokens.clone(); - generated_tokens.extend(next_tokens.clone()); - all_tokens.extend(next_tokens.clone()); - - if let Some(t) = tos.next_token(next_tokens[0] as u32)? { - callback(t); - } - } - - let elapsed = start.elapsed(); - log::warn!("Elapsed: {:?}", elapsed); - log::warn!("Tok/s {}", all_tokens.len() as f64 / elapsed.as_secs_f64()); - println!("Tok/s {}", all_tokens.len() as f64 / elapsed.as_secs_f64()); - model.text_model.reset(); - Ok(()) -} diff --git a/crates/ratchet-models/src/moondream/mlp.rs b/crates/ratchet-models/src/moondream/mlp.rs deleted file mode 100644 index e94c02ec..00000000 --- a/crates/ratchet-models/src/moondream/mlp.rs +++ /dev/null @@ -1,18 +0,0 @@ -use ratchet::Tensor; -use ratchet_nn::{Linear, Module}; - -#[derive(Debug, derive_new::new)] -pub struct MLP { - pub fc1: Linear, - pub fc2: Linear, -} - -impl Module for MLP { - type Input = Tensor; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - let input_dt = input.dt(); - self.fc2 - .schedule(self.fc1.schedule(input)?.full()?.gelu()?.cast(input_dt)?) - } -} diff --git a/crates/ratchet-models/src/moondream/mod.rs b/crates/ratchet-models/src/moondream/mod.rs deleted file mode 100644 index 02d58c48..00000000 --- a/crates/ratchet-models/src/moondream/mod.rs +++ /dev/null @@ -1,8 +0,0 @@ -mod generate; -mod mlp; -pub mod model; -mod text_model; -mod vision_encoder; - -pub use generate::generate; -pub use model::Moondream; diff --git a/crates/ratchet-models/src/moondream/model.rs b/crates/ratchet-models/src/moondream/model.rs deleted file mode 100644 index 37ccfa26..00000000 --- a/crates/ratchet-models/src/moondream/model.rs +++ /dev/null @@ -1,284 +0,0 @@ -use std::io::{BufRead, Seek}; - -use anyhow::Ok; -use half::f16; -use ratchet::{shape, DType, Device, Tensor}; -use ratchet_loader::gguf::gguf::Header; -use ratchet_nn::{Embedding, KVCache, LayerNorm, Linear, RotaryEmbedding}; - -#[cfg(target_arch = "wasm32")] -use {crate::ratchet_from_gguf_web, crate::TensorMap}; - -use super::{ - mlp::MLP, - text_model::{DecoderLayer, SelfAttention, TextModel}, - vision_encoder::{ - Attention, LinearPatchEmbedding, VisionEncoder, VisionProjection, VisionTransformer, - VitBlock, - }, -}; - -#[derive(Debug)] -pub struct Moondream { - pub vision_encoder: VisionEncoder, - pub text_model: TextModel, -} - -impl Moondream { - pub fn load( - header: Header, - reader: &mut R, - device: &Device, - ) -> anyhow::Result { - let lt = |name: &str| header.tensor(reader, name, device).unwrap(); - Self::load_inner(&header, lt, device) - } - - #[cfg(target_arch = "wasm32")] - pub async fn from_web(header: Header, mut tensors: TensorMap) -> anyhow::Result { - let device = Device::request_device(ratchet::DeviceRequest::GPU).await?; - let mut lt = |name: &str| { - let tensor = tensors - .remove(name) - .ok_or_else(|| anyhow::anyhow!("missing tensor")); - ratchet_from_gguf_web(tensor.unwrap(), &device).unwrap() - }; - Self::load_inner(&header, lt, &device) - } - - fn load_inner(_header: &Header, mut lt: F, device: &Device) -> anyhow::Result - where - F: FnMut(&str) -> Tensor, - { - let n_layers = 24_i32; - let dim = 2048_f32; - let n_heads = 32_u32; - let n_kv_heads = 32_u32; - let rope_base = 10000.0f32; - let rope_dim = 32_u32; - let ln_eps = 1e-05; - let hdim = dim / n_heads as f32; - let softmax_scale = Tensor::from_data([1.0 / hdim.sqrt()], shape![1], device.clone()); - let cache_shape = shape![1, 32, 4096, 64]; - - let kv_cache = match device.compute_precision() { - DType::F16 => KVCache::new::(n_layers as _, cache_shape, device), - DType::F32 => KVCache::new::(n_layers as _, cache_shape, device), - _ => unimplemented!(), - }; - - let text_model = TextModel::new( - Embedding::new(lt("text_model.transformer.embd.wte.weight")), - (0..n_layers) - .map(|i| { - DecoderLayer::new( - LayerNorm::new( - lt(&format!("text_model.transformer.h.{}.ln.weight", i)), - Some(lt(&format!("text_model.transformer.h.{}.ln.bias", i))), - ln_eps, - ), - SelfAttention::new( - Linear::new( - lt(&format!("text_model.transformer.h.{}.mixer.Wqkv.weight", i)), - Some(lt(&format!( - "text_model.transformer.h.{}.mixer.Wqkv.bias", - i - ))), - ), - Linear::new( - lt(&format!( - "text_model.transformer.h.{}.mixer.out_proj.weight", - i - )), - Some(lt(&format!( - "text_model.transformer.h.{}.mixer.out_proj.bias", - i - ))), - ), - RotaryEmbedding::new(rope_dim as usize, false, rope_base, 1.0), - n_heads, - softmax_scale.clone(), - n_kv_heads, - ), - MLP::new( - Linear::new( - lt(&format!("text_model.transformer.h.{}.mlp.fc1.weight", i)), - Some(lt(&format!("text_model.transformer.h.{}.mlp.fc1.bias", i))), - ), - Linear::new( - lt(&format!("text_model.transformer.h.{}.mlp.fc2.weight", i)), - Some(lt(&format!("text_model.transformer.h.{}.mlp.fc2.bias", i))), - ), - ), - ) - }) - .collect(), - LayerNorm::new( - lt("text_model.lm_head.ln.weight"), - Some(lt("text_model.lm_head.ln.bias")), - ln_eps, - ), - Linear::new( - lt("text_model.lm_head.linear.weight"), - Some(lt("text_model.lm_head.linear.bias")), - ), - kv_cache, - device.clone(), - ); - - let projection = VisionProjection::new(MLP::new( - Linear::new( - lt("vision_encoder.projection.mlp.fc1.weight"), - Some(lt("vision_encoder.projection.mlp.fc1.bias")), - ), - Linear::new( - lt("vision_encoder.projection.mlp.fc2.weight"), - Some(lt("vision_encoder.projection.mlp.fc2.bias")), - ), - )); - - let transformer = VisionTransformer::new( - LinearPatchEmbedding::new( - Linear::new(lt("vision_encoder.encoder.model.visual.patch_embed.linear.weight"), Some(lt("vision_encoder.encoder.model.visual.patch_embed.linear.bias"))), - ), - lt("vision_encoder.encoder.model.visual.pos_embed"), - (0..27) - .map(|layer| { - let qkvw = lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.attn.qkv.weight", layer)); - let qkvb = lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.attn.qkv.bias", layer)); - - let n_heads = 16; - let dim = 1152; - let h_dim = dim / n_heads; - let scale_factor = - Tensor::from_data([1.0 / (h_dim as f32).sqrt()], shape![1], device.clone()); - - VitBlock::new( - 1152, - Attention::new( - n_heads, - dim, - Linear::new(qkvw, Some(qkvb)), - Linear::new( - lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.attn.proj.weight", layer)), - Some(lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.attn.proj.bias", layer))), - ), - scale_factor, - ), - MLP::new( - Linear::new( - lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.mlp.fc1.weight", layer)), - Some(lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.mlp.fc1.bias", layer))), - ), - Linear::new( - lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.mlp.fc2.weight", layer)), - Some(lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.mlp.fc2.bias", layer))), - ), - ), - LayerNorm::new( - lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.norm1.weight", layer)), - Some(lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.norm1.bias", layer))), - ln_eps, - ), - LayerNorm::new( - lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.norm2.weight", layer)), - Some(lt(&format!("vision_encoder.encoder.model.visual.blocks.{}.norm2.bias", layer))), - ln_eps, - ), - ) - }).collect::>(), - LayerNorm::new(lt("vision_encoder.encoder.model.visual.norm.weight"), Some(lt("vision_encoder.encoder.model.visual.norm.bias")), ln_eps), - ); - - let vision_encoder = VisionEncoder::new(projection, transformer); - Ok(Self { - vision_encoder, - text_model, - }) - } -} - -#[cfg(all(test, not(target_arch = "wasm32"), feature = "pyo3"))] -mod tests { - use std::fs; - - use anyhow::Ok; - use hf_hub::api::sync::Api; - use ratchet::{shape, test_util::run_py_prg, Device, DeviceRequest, Tensor}; - use ratchet_loader::gguf; - use ratchet_nn::Module; - use tokenizers::Tokenizer; - - use crate::moondream::{ - generate::generate, text_model::TextModel, vision_encoder::VisionEncoder, - }; - - use super::Moondream; - - fn vision_ground_truth(tensor: Tensor) -> anyhow::Result { - let prg = r#" -from transformers import AutoModelForCausalLM, AutoTokenizer -import torch - -def ground(*args): - tensor = torch.from_numpy(args[0]) - model_id = "vikhyatk/moondream2" - revision = "2024-05-20" - model = AutoModelForCausalLM.from_pretrained( - model_id, trust_remote_code=True, revision=revision - ) - return model.encode_image(tensor).numpy() -"#; - - run_py_prg(prg.to_string(), &[&tensor], &[], ratchet::DType::F32) - } - - #[test] - #[cfg_attr(feature = "ci", ignore)] - fn moondream_encoder() -> anyhow::Result<()> { - let device = Device::request_device(DeviceRequest::GPU).unwrap(); - let api = Api::new().unwrap(); - let model_repo = api.model("ratchet-community/ratchet-moondream-2".to_string()); - let model_path = model_repo.get("moondream_f32.gguf").unwrap(); - let mut reader = std::io::BufReader::new(std::fs::File::open(model_path).unwrap()); - let content = gguf::gguf::Header::read(&mut reader).unwrap(); - let model = Moondream::load(content, &mut reader, &device).unwrap(); - - let input = Tensor::randn::(shape![1, 3, 378, 378], device); - let ours = model - .vision_encoder - .schedule(input.clone())? - .resolve()? - .to(&Device::CPU)?; - let theirs = vision_ground_truth(input.to(&Device::CPU).unwrap()).unwrap(); - ours.all_close(&theirs, 1e-1, 1e-1).unwrap(); - Ok(()) - } - - #[test] - #[cfg_attr(feature = "ci", ignore)] - fn moondream_end_to_end() { - let device = Device::request_device(DeviceRequest::GPU).unwrap(); - let api = Api::new().unwrap(); - let model_repo = api.model("ratchet-community/ratchet-moondream-2".to_string()); - let model_path = model_repo.get("moondream_q8_0.gguf").unwrap(); - let mut reader = std::io::BufReader::new(std::fs::File::open(model_path).unwrap()); - let content = gguf::gguf::Header::read(&mut reader).unwrap(); - let mut model = Moondream::load(content, &mut reader, &device).unwrap(); - - let tokenizer_path = model_repo.get("tokenizer.json").unwrap(); - let tokenizer = Tokenizer::from_file(tokenizer_path).unwrap(); - - let img_path = model_repo.get("demo.jpg").unwrap(); - let img = fs::read(img_path).unwrap(); - - generate( - &mut model, - &img, - "What is happening here?".to_owned(), - tokenizer, - |token| print!("{}", token), - ) - .unwrap(); - } -} diff --git a/crates/ratchet-models/src/moondream/text_model.rs b/crates/ratchet-models/src/moondream/text_model.rs deleted file mode 100644 index 57bb4a91..00000000 --- a/crates/ratchet-models/src/moondream/text_model.rs +++ /dev/null @@ -1,192 +0,0 @@ -use ratchet::{rvec, shape, Device, Tensor}; -use ratchet_nn::{ - Embedding, KVCache, KVEntry, LayerNorm, Linear, Module, RotaryEmbedding, RotaryInput, -}; - -use super::mlp::MLP; - -#[derive(Debug, derive_new::new)] -pub struct SelfAttention { - qkv: Linear, - o: Linear, - rope: RotaryEmbedding, - n_heads: u32, - softmax_scale: Tensor, - n_kv_heads: u32, -} - -pub struct AttnInput { - pub input: Tensor, - pub mask: Option, - pub kv_cache: Option, -} - -impl Module for SelfAttention { - type Input = AttnInput; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - let AttnInput { - input, - mask, - kv_cache, - } = input; - let [batch_size, q_len, n_state]: [usize; 3] = input.shape().try_into()?; - - let hdim = n_state / self.n_heads as usize; - let kv_x_hdim = self.n_kv_heads as usize * hdim; - - let qkv = self.qkv.schedule(input)?; - let query_pos = self.n_heads as usize * hdim; - let key_pos = query_pos + kv_x_hdim; - let value_pos = key_pos + kv_x_hdim; - - let query_states = qkv - .clone() - .slice(&[0..batch_size, 0..q_len, 0..query_pos])?; - let key_states = qkv - .clone() - .slice(&[0..batch_size, 0..q_len, query_pos..key_pos])?; - let value_states = qkv - .clone() - .slice(&[0..batch_size, 0..q_len, key_pos..value_pos])?; - - let q_shape = shape![batch_size as _, q_len, self.n_heads as _, hdim]; - let kv_shape = shape![batch_size as _, q_len, self.n_kv_heads as _, hdim]; - - let query_states = query_states.view(q_shape)?.permute(&[0, 2, 1, 3])?; - let key_states = key_states.view(kv_shape.clone())?.permute(&[0, 2, 1, 3])?; - let value_states = value_states.view(kv_shape)?.permute(&[0, 2, 1, 3])?; - - let offset = kv_cache.as_ref().map(|kv| kv.entries).unwrap_or(0); - let q_dt = query_states.dt(); - let query_states = self - .rope - .schedule(RotaryInput { - input: query_states.full()?, - offset, - })? - .cast(q_dt)?; - let key_states = self - .rope - .schedule(RotaryInput { - input: key_states.full()?, - offset, - })? - .cast(q_dt)?; - - let (key_states, value_states) = if let Some(kv) = kv_cache { - let k_cache = kv.k_cache.cache(key_states, 2, offset)?; - let v_cache = kv.v_cache.cache(value_states, 2, offset)?; - (k_cache, v_cache) - } else { - (key_states, value_states) - }; - - let mut attn_weights = query_states - .full()? - .matmul(key_states.full()?, false, true)? - .mul(self.softmax_scale.clone())? - .cast(q_dt)?; - - if let Some(m) = mask { - let attn_dt = attn_weights.dt(); - attn_weights = attn_weights.add(m.cast(attn_dt)?)?; - } - - let w = attn_weights.full()?.softmax(3)?.cast(value_states.dt())?; - let wv = w - .matmul(value_states, false, false)? - .permute(&[0, 2, 1, 3])?; - let wv = wv.view(shape![batch_size as _, q_len, n_state])?; - self.o.schedule(wv) - } -} - -#[derive(Debug, derive_new::new)] -pub struct DecoderLayer { - pub ln: LayerNorm, - pub self_attn: SelfAttention, - pub mlp: MLP, -} - -#[derive(Debug)] -pub struct DecoderLayerInput { - pub x: Tensor, - pub mask: Option, - pub kv_cache: Option, -} - -impl Module for DecoderLayer { - type Input = DecoderLayerInput; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - let DecoderLayerInput { x, mask, kv_cache } = input; - let residual = x.clone(); - let xs = self.ln.schedule(x)?; - let attn_output = self.self_attn.schedule(AttnInput { - input: xs.clone(), - mask, - kv_cache, - })?; - let ff_hs = self.mlp.schedule(xs)?; - attn_output.add(ff_hs)?.add(residual) - } -} - -#[derive(Debug, derive_new::new)] -pub struct TextModel { - pub embedding: Embedding, - pub layers: Vec, - pub ln_post: LayerNorm, - pub lm_head: Linear, - pub kv_cache: KVCache, - pub device: Device, -} - -impl Module for TextModel { - type Input = Tensor; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - let mut x = input.clone(); - let [_, seq_len, n_state]: [usize; 3] = x.shape().try_into()?; - let mask = if seq_len <= 1 { - None - } else { - Some(Self::generate_mask(seq_len, x.device())?) - }; - - for (i, layer) in self.layers.iter().enumerate() { - let input = DecoderLayerInput { - x, - mask: mask.clone(), - kv_cache: Some(self.kv_cache[i].clone()), - }; - x = layer.schedule(input)?; - } - x = self.ln_post.schedule(x)?; - x = x.slice(&[0..1, seq_len - 1..seq_len, 0..n_state])?; - let logits = self.lm_head.schedule(x)?; - Ok(logits) - } -} - -impl TextModel { - pub fn generate_mask(seq_len: usize, device: &Device) -> anyhow::Result { - let mask: Vec<_> = (0..seq_len) - .flat_map(|i| (0..seq_len).map(move |j| if j > i { f32::NEG_INFINITY } else { 0f32 })) - .collect(); - - Ok(Tensor::from_data( - mask, - shape![seq_len, seq_len], - device.clone(), - )) - } - - pub fn cache_mut(&mut self) -> &mut KVCache { - &mut self.kv_cache - } - pub fn reset(&mut self) { - self.kv_cache.reset(); - } -} diff --git a/crates/ratchet-models/src/moondream/vision_encoder.rs b/crates/ratchet-models/src/moondream/vision_encoder.rs deleted file mode 100644 index 26eb9c3a..00000000 --- a/crates/ratchet-models/src/moondream/vision_encoder.rs +++ /dev/null @@ -1,173 +0,0 @@ -use ratchet::{prelude::shape, rvec, Tensor}; -use ratchet_nn::{LayerNorm, Linear, Module}; - -use super::mlp::MLP; - -#[derive(Debug, derive_new::new)] -pub struct Attention { - n_heads: usize, - dim: usize, - qkv: Linear, - proj: Linear, - scale_factor: Tensor, -} - -impl Module for Attention { - type Input = Tensor; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - let h_dim = self.dim / self.n_heads; - let [b, n, c]: [usize; 3] = input.shape().try_into()?; - // step 1 - 0, 1, 2, 3, 4 - // step 2 - 0, 2, 1, 3, 4 - // step 3 - 2, 0, 1, 3, 4 - // step 4 - 2, 0, 3, 1, 4 - - // b, n, 3, nh, hd - let mut qkv = self.qkv.schedule(input.clone())?; - // b, 3, n, nh, hd - qkv = qkv - .view(shape![b, n, 3, self.n_heads * h_dim])? - .permute(&[0, 2, 1, 3])?; - // 3, b, n, nh, hd - qkv = qkv - .view(shape![b, 3, n * self.n_heads * h_dim])? - .permute(&[1, 0, 2])?; - // 3, b, nh, n, hd - qkv = qkv - .view(shape![3 * b, n, self.n_heads, h_dim])? - .permute(&[0, 2, 1, 3])? - .view(shape![3, b * self.n_heads * n * h_dim])?; - - let q = qkv - .clone() - .slice(&[0..1, 0..(b * self.n_heads * n * h_dim)])? - .view(shape![b, self.n_heads, n, h_dim])?; - let k = qkv - .clone() - .slice(&[1..2, 0..(b * self.n_heads * n * h_dim)])? - .view(shape![b, self.n_heads, n, h_dim])?; - let v = qkv - .clone() - .slice(&[2..3, 0..(b * self.n_heads * n * h_dim)])? - .view(shape![b, self.n_heads, n, h_dim])?; - - // scaled dot-product attention - let mut attn_weights = q - .full()? - .matmul(k.permute(&[0, 1, 3, 2])?.full()?, false, false)? - .mul(self.scale_factor.clone())?; - attn_weights = attn_weights.softmax(3)?.cast(v.dt())?; - let mut x = attn_weights.matmul(v, false, false)?; - x = x.permute(&[0, 2, 1, 3])?.view(shape![b, n, c])?; - self.proj.schedule(x) - } -} - -#[derive(Debug, derive_new::new)] -pub struct VitBlock { - embed_dim: usize, - attn: Attention, - mlp: MLP, - norm1: LayerNorm, - norm2: LayerNorm, -} - -impl Module for VitBlock { - type Input = Tensor; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - let x = input - .clone() - .add(self.attn.schedule(self.norm1.schedule(input)?)?)?; - x.clone().add(self.mlp.schedule(self.norm2.schedule(x)?)?) - } -} - -#[derive(Debug, derive_new::new)] -pub struct LinearPatchEmbedding { - linear: Linear, -} - -impl Module for LinearPatchEmbedding { - type Input = Tensor; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - let [b, c, hp1, wp2]: [usize; 4] = input.shape().try_into()?; - let (p1, p2) = (14, 14); - let (h, w) = (hp1 / p1, wp2 / p2); - // step 1 - 0, 1, 2, 3, 4, 5 - // step 2 - 0, 2, 1, 3, 4, 5 - // step 3 - 0, 2, 1, 4, 3, 5 - // step 4 - 0, 2, 4, 1, 3, 5 - - // b, c, h, p1, w, p2 - let mut x = input - .view(shape![b, c, h, p1 * w * p2])? - .permute(&[0, 2, 1, 3])?; - // b, h, c, p1, w, p2 - x = x - .view(shape![b * h * c, p1, w, p2])? - .permute(&[0, 2, 1, 3])?; - // b, h, c, w, p1, p2 - x = x - .view(shape![b * h, c, w, p1 * p2])? - .permute(&[0, 2, 1, 3])?; - // b, h, w, c, p1, p2 - x = x.view(shape![b, h * w, c * p1 * p2])?; - self.linear.schedule(x) - } -} - -#[derive(Debug, derive_new::new)] -pub struct VisionTransformer { - patch_embed: LinearPatchEmbedding, - pos_embed: Tensor, - blocks: Vec, - norm: LayerNorm, -} - -impl Module for VisionTransformer { - type Input = Tensor; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - let mut x = self.patch_embed.schedule(input)?; - x = x.clone().add(self.pos_embed.clone())?; - x = self - .blocks - .iter() - .fold(x.clone(), |acc, blk| blk.schedule(acc).unwrap()); - self.norm.schedule(x) - } -} - -#[derive(Debug, derive_new::new)] -pub struct VisionProjection { - mlp: MLP, -} - -impl Module for VisionProjection { - type Input = Tensor; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - self.mlp.schedule(input) - } -} - -#[derive(Debug, derive_new::new)] -pub struct VisionEncoder { - projection: VisionProjection, - transformer: VisionTransformer, -} - -impl Module for VisionEncoder { - type Input = Tensor; - - fn schedule(&self, input: Self::Input) -> anyhow::Result { - let transformed = self.transformer.schedule(input)?; - self.projection.schedule(Tensor::cat( - rvec![transformed.clone(), transformed.clone()], - 2, - )?) - } -} diff --git a/crates/ratchet-models/src/registry.rs b/crates/ratchet-models/src/registry.rs index a493664c..2143ceef 100644 --- a/crates/ratchet-models/src/registry.rs +++ b/crates/ratchet-models/src/registry.rs @@ -32,7 +32,6 @@ pub enum PhiVariants { #[cfg_attr(target_arch = "wasm32", tsify(from_wasm_abi))] pub enum AvailableModels { Phi(PhiVariants), - Moondream, } impl AvailableModels { @@ -42,7 +41,6 @@ impl AvailableModels { PhiVariants::Phi2 => "FL33TW00D-HF/phi2", PhiVariants::Phi3 => "FL33TW00D-HF/phi3", }, - AvailableModels::Moondream => "ratchet-community/ratchet-moondream-2", }; id.to_string() } @@ -53,7 +51,6 @@ impl AvailableModels { PhiVariants::Phi2 => "phi2", PhiVariants::Phi3 => "phi3-mini-4k", }, - AvailableModels::Moondream => "moondream", }; match quantization { Quantization::Q8_0 => format!("{}_q8_0.gguf", model_stem), diff --git a/crates/ratchet-web/src/model.rs b/crates/ratchet-web/src/model.rs index e0df45da..3e4cb789 100644 --- a/crates/ratchet-web/src/model.rs +++ b/crates/ratchet-web/src/model.rs @@ -3,7 +3,6 @@ use futures::stream::TryStreamExt; use futures::StreamExt; use ratchet_hub::{Api, ApiBuilder, RepoType}; use ratchet_loader::gguf::gguf::{self, Header, TensorInfo}; -use ratchet_models::moondream::{self, Moondream}; use ratchet_models::phi2; use ratchet_models::phi2::Phi2; use ratchet_models::phi3::{self, Phi3}; @@ -16,7 +15,6 @@ use wasm_bindgen::prelude::*; pub enum WebModel { Phi2(Phi2), Phi3(Phi3), - Moondream(Moondream), } impl WebModel { @@ -54,26 +52,6 @@ impl WebModel { .unwrap(); Ok(JsValue::NULL) } - WebModel::Moondream(model) => { - let input: MoondreamInputs = serde_wasm_bindgen::from_value(input)?; - let rs_callback = |output: String| { - let _ = input.callback.call1(&JsValue::NULL, &output.into()); - }; - let model_repo = - ApiBuilder::from_hf("tgestson/ratchet-moondream2", RepoType::Model).build(); - let model_bytes = model_repo.get("tokenizer.json").await?; - let tokenizer = Tokenizer::from_bytes(model_bytes.to_vec()).unwrap(); - moondream::generate( - model, - input.image_bytes, - input.question, - tokenizer, - rs_callback, - ) - .await - .unwrap(); - Ok(JsValue::NULL) - } } } @@ -93,10 +71,6 @@ impl WebModel { Ok(WebModel::Phi3(model)) } }, - AvailableModels::Moondream => { - let model = Moondream::from_web(header, tensor_map).await?; - Ok(WebModel::Moondream(model)) - } _ => Err(anyhow::anyhow!("Unknown model type")), } } @@ -109,14 +83,6 @@ pub struct PhiInputs { pub callback: js_sys::Function, } -#[derive(serde::Serialize, serde::Deserialize)] -pub struct MoondreamInputs { - pub question: String, - pub image_bytes: Vec, - #[serde(with = "serde_wasm_bindgen::preserve")] - pub callback: js_sys::Function, -} - #[wasm_bindgen] #[derive(Debug)] pub struct Model { diff --git a/examples/ratchet-moondream/.gitignore b/examples/ratchet-moondream/.gitignore deleted file mode 100644 index 4d29575d..00000000 --- a/examples/ratchet-moondream/.gitignore +++ /dev/null @@ -1,23 +0,0 @@ -# See https://help.github.com/articles/ignoring-files/ for more about ignoring files. - -# dependencies -/node_modules -/.pnp -.pnp.js - -# testing -/coverage - -# production -/build - -# misc -.DS_Store -.env.local -.env.development.local -.env.test.local -.env.production.local - -npm-debug.log* -yarn-debug.log* -yarn-error.log* diff --git a/examples/ratchet-moondream/README.md b/examples/ratchet-moondream/README.md deleted file mode 100644 index 5e7cf25e..00000000 --- a/examples/ratchet-moondream/README.md +++ /dev/null @@ -1,30 +0,0 @@ -# Getting Started with Create React App - -This project was bootstrapped with [Create React App](https://github.com/facebook/create-react-app). - -## Available Scripts - -In the project directory, you can run: - -### `npm start` - -Runs the app in the development mode.\ -Open [http://localhost:3000](http://localhost:3000) to view it in your browser. - -The page will reload when you make changes.\ -You may also see any lint errors in the console. - -### `npm test` - -Launches the test runner in the interactive watch mode.\ -See the section about [running tests](https://facebook.github.io/create-react-app/docs/running-tests) for more information. - -### `npm run build` - -Builds the app for production to the `build` folder.\ -It correctly bundles React in production mode and optimizes the build for the best performance. - -The build is minified and the filenames include the hashes.\ -Your app is ready to be deployed! - -See the section about [deployment](https://facebook.github.io/create-react-app/docs/deployment) for more information. diff --git a/examples/ratchet-moondream/package-lock.json b/examples/ratchet-moondream/package-lock.json deleted file mode 100644 index 06febf98..00000000 --- a/examples/ratchet-moondream/package-lock.json +++ /dev/null @@ -1,18080 +0,0 @@ -{ - "name": "ratchet-moondream", - 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"name": "ratchet-moondream", - "version": "0.1.0", - "private": true, - "dependencies": { - "@emotion/react": "^11.11.4", - "@emotion/styled": "^11.11.5", - "@mui/icons-material": "^5.15.19", - "@mui/material": "^5.15.19", - "@ratchet-ml/ratchet-web": "file:../../target/pkg/ratchet-web", - "react": "^18.3.1", - "react-dom": "^18.3.1", - "react-scripts": "5.0.1", - "web-vitals": "^2.1.4" - }, - "scripts": { - "start": "react-scripts start", - "build": "react-scripts build", - "test": "react-scripts test", - "eject": "react-scripts eject" - }, - "eslintConfig": { - "extends": [ - "react-app", - "react-app/jest" - ] - }, - "browserslist": { - "production": [ - ">0.2%", - "not dead", - "not op_mini all" - ], - "development": [ - "last 1 chrome version", - "last 1 firefox version", - "last 1 safari version" - ] - }, - "devDependencies": { - "prettier": "3.3.1" - } -} diff --git a/examples/ratchet-moondream/public/index.html b/examples/ratchet-moondream/public/index.html deleted file mode 100644 index 5d1e5bc2..00000000 --- a/examples/ratchet-moondream/public/index.html +++ /dev/null @@ -1,27 +0,0 @@ - - - - - - - - Ratchet Moondream - - - -
    - - - diff --git a/examples/ratchet-moondream/public/manifest.json b/examples/ratchet-moondream/public/manifest.json deleted file mode 100644 index 080d6c77..00000000 --- a/examples/ratchet-moondream/public/manifest.json +++ /dev/null @@ -1,25 +0,0 @@ -{ - "short_name": "React App", - "name": "Create React App Sample", - "icons": [ - { - "src": "favicon.ico", - "sizes": "64x64 32x32 24x24 16x16", - "type": "image/x-icon" - }, - { - "src": "logo192.png", - "type": "image/png", - "sizes": "192x192" - }, - { - "src": "logo512.png", - "type": "image/png", - "sizes": "512x512" - } - ], - "start_url": ".", - "display": "standalone", - "theme_color": "#000000", - "background_color": "#ffffff" -} diff --git a/examples/ratchet-moondream/public/robots.txt b/examples/ratchet-moondream/public/robots.txt deleted file mode 100644 index e9e57dc4..00000000 --- a/examples/ratchet-moondream/public/robots.txt +++ /dev/null @@ -1,3 +0,0 @@ -# https://www.robotstxt.org/robotstxt.html -User-agent: * -Disallow: diff --git a/examples/ratchet-moondream/src/App.css b/examples/ratchet-moondream/src/App.css deleted file mode 100644 index 74b5e053..00000000 --- a/examples/ratchet-moondream/src/App.css +++ /dev/null @@ -1,38 +0,0 @@ -.App { - text-align: center; -} - -.App-logo { - height: 40vmin; - pointer-events: none; -} - -@media (prefers-reduced-motion: no-preference) { - .App-logo { - animation: App-logo-spin infinite 20s linear; - } -} - -.App-header { - background-color: #282c34; - min-height: 100vh; - display: flex; - flex-direction: column; - align-items: center; - justify-content: center; - font-size: calc(10px + 2vmin); - color: white; -} - -.App-link { - color: #61dafb; -} - -@keyframes App-logo-spin { - from { - transform: rotate(0deg); - } - to { - transform: rotate(360deg); - } -} diff --git a/examples/ratchet-moondream/src/App.js b/examples/ratchet-moondream/src/App.js deleted file mode 100644 index 340e48be..00000000 --- a/examples/ratchet-moondream/src/App.js +++ /dev/null @@ -1,242 +0,0 @@ -import "./App.css"; -import { Model, Quantization, default as init } from "@ratchet-ml/ratchet-web"; -import { styled } from "@mui/material/styles"; -import { useState, useEffect } from "react"; -import { - LinearProgress, - TextField, - Button, - Container, - Card, - CardMedia, - Stack, - Box, - Dialog, - DialogActions, - DialogContentText, - DialogTitle, - DialogContent, - Typography, - CardActions, - InputAdornment, - IconButton, -} from "@mui/material"; -import SendIcon from "@mui/icons-material/Send"; - -const VisuallyHiddenInput = styled("input")({ - clip: "rect(0 0 0 0)", - clipPath: "inset(50%)", - height: 1, - overflow: "hidden", - position: "absolute", - bottom: 0, - left: 0, - whiteSpace: "nowrap", - width: 1, -}); - -function App() { - const [question, setQuestion] = useState(""); - const [generatedText, setGeneratedText] = useState(""); - const [image, setImage] = useState(new Uint8Array()); - const [progress, setProgress] = useState(0); - const [isLoading, setIsLoading] = useState(true); - const [accepted, setAccepted] = useState(false); - const [isSupportedBrowser, setIsSupportedBrowser] = useState(true); - const [ratchetDBExists, setRatchetDBExists] = useState(false); - const [model, setModel] = useState(null); - const [isRunning, setIsRunning] = useState(false); - - useEffect(() => { - (async () => { - await init(); - setRatchetDBExists( - (await window.indexedDB.databases()) - .map((db) => db.name) - .includes("ratchet"), - ); - await setImage( - new Uint8Array( - await ( - await fetch( - "https://raw.githubusercontent.com/vikhyat/moondream/main/assets/demo-1.jpg", - ) - ).arrayBuffer(), - ), - ); - })(); - }, []); - - async function loadModel() { - setAccepted(true); - setProgress(2); - setModel( - await Model.load("Moondream", Quantization.Q8_0, (p) => setProgress(p)), - ); - setProgress(100); - setIsLoading(false); - } - - async function runModel() { - if (!model || isRunning) { - return; - } - - setGeneratedText(""); - - let cb = (s) => { - setGeneratedText((prevText) => { - return prevText + s; - }); - }; - - setIsRunning(true); - await model.run({ question: question, image_bytes: image, callback: cb }); - setIsRunning(false); - } - - async function handleUpload(e) { - if (e.target.files.length == 0) { - return; - } - setImage(new Uint8Array(await e.target.files[0].arrayBuffer())); - } - - async function keypress(e) { - if (e.key === "Enter") { - runModel(); - e.preventDefault(); - } - } - - async function deleteWeights() { - setAccepted(false); - setProgress(0); - setModel(null); - await window.indexedDB.deleteDatabase("ratchet"); - setIsLoading(true); - } - - return ( -
    - - - - {navigator.gpu ? "Load Model" : "Unsupported Browser"} - - - - {navigator.gpu - ? "This app requires downloading a 2.2GB model which may take a few minutes. If the model has been previously downloaded, it will be loaded from cache." - : "This app requires a browser that supports webgpu"} - - - {navigator.gpu ? ( - - - - ) : ( - <> - )} - - - - - Moondream by{" "} - Vikhyat running - on WebGpu via{" "} - Ratchet - - - - - - - - - - - - - setQuestion(e.target.value)} - onKeyDown={keypress} - InputProps={{ - endAdornment: ( - - - - - - ), - }} - /> - -
    - -
    - {isLoading && progress < 99 ? ( - - Downloading Weights... - - ) : ( - <> - )} - {isLoading && progress > 99 ? ( - - Preparing Weights... - - ) : ( - <> - )} -
    - {generatedText} -
    -     -     -
    - ); -} - -export default App; diff --git a/examples/ratchet-moondream/src/index.css b/examples/ratchet-moondream/src/index.css deleted file mode 100644 index 4a1df4db..00000000 --- a/examples/ratchet-moondream/src/index.css +++ /dev/null @@ -1,13 +0,0 @@ -body { - margin: 0; - font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", "Roboto", "Oxygen", - "Ubuntu", "Cantarell", "Fira Sans", "Droid Sans", "Helvetica Neue", - sans-serif; - -webkit-font-smoothing: antialiased; - -moz-osx-font-smoothing: grayscale; -} - -code { - font-family: source-code-pro, Menlo, Monaco, Consolas, "Courier New", - monospace; -} diff --git a/examples/ratchet-moondream/src/index.js b/examples/ratchet-moondream/src/index.js deleted file mode 100644 index df868170..00000000 --- a/examples/ratchet-moondream/src/index.js +++ /dev/null @@ -1,11 +0,0 @@ -import React from "react"; -import ReactDOM from "react-dom/client"; -import "./index.css"; -import App from "./App"; - -const root = ReactDOM.createRoot(document.getElementById("root")); -root.render( - - - , -); From 1f70c6c87c3ca701df8a4cc479170a8b4ebf4734 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:58:20 -0700 Subject: [PATCH 126/146] Update pnpm-lock.yaml --- pnpm-lock.yaml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml index d3f58d4b..563bdcbd 100644 --- a/pnpm-lock.yaml +++ b/pnpm-lock.yaml @@ -26,9 +26,9 @@ importers: '@ffmpeg/util': specifier: ^0.12.1 version: 0.12.1 - '@ratchet-ml/ratchet-web-train': - specifier: link:../../target/pkg/ratchet-web-train - version: link:../../target/pkg/ratchet-web-train + '@ratchet-ml/ratchet-web': + specifier: link:../../target/pkg/ratchet-web + version: link:../../target/pkg/ratchet-web fix-webm-duration: specifier: ^1.0.5 version: 1.0.5 From 9b448e45caf5079778c3d92ad4cc3f68a325d6eb Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 00:58:33 -0700 Subject: [PATCH 127/146] Update vite version on ratchet-train-toy --- examples/ratchet-train-toy/package.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/ratchet-train-toy/package.json b/examples/ratchet-train-toy/package.json index 375b32e4..4a2d12b2 100644 --- a/examples/ratchet-train-toy/package.json +++ b/examples/ratchet-train-toy/package.json @@ -36,7 +36,7 @@ "tailwindcss": "^4.0.0", "typescript": "^5.0.0", "typescript-eslint": "^8.20.0", - "vite": "^6.1.0", + "vite": "^6.2.0", "vite-plugin-top-level-await": "^1.4.4", "vite-plugin-wasm": "^3.4.1" } From 8d93d9af6051c1da5de6057b043f7e774d7cf441 Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 01:03:19 -0700 Subject: [PATCH 128/146] Add using cache graph --- .../ratchet-train-toy/src/routes/+page.svelte | 58 ++++++++++++++++++- examples/ratchet-train-toy/src/trainWorker.ts | 7 +++ 2 files changed, 64 insertions(+), 1 deletion(-) diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte index 5063d0c8..3336010a 100644 --- a/examples/ratchet-train-toy/src/routes/+page.svelte +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -17,11 +17,13 @@ let memoryChart: Chart; let lrChart: Chart; let accuracyChart: Chart; + let usingCacheChart: Chart; let canvas: HTMLCanvasElement; let speedCanvas: HTMLCanvasElement; let memoryCanvas: HTMLCanvasElement; let lrCanvas: HTMLCanvasElement; let accuracyCanvas: HTMLCanvasElement; + let usingCacheCanvas: HTMLCanvasElement; let attentionCanvases: HTMLCanvasElement[][] = []; let showAdvanced = false; let runCount = 0; @@ -63,7 +65,7 @@ // Track last parameter values to detect actual changes let lastParams: Record | null = null; - let lastTaskParams: Record | null = null; + let lastTaskParams: Record | null = null; // Add reactive statement to restart training when parameters change $: { @@ -380,6 +382,16 @@ pointStyle: false }); + // Add dataset to using cache chart + usingCacheChart.data.datasets.push({ + label: '', // Will be set by updateAllLabels + data: [], + borderColor: colors[runCount % colors.length], + tension: 0.1, + order: -runCount, + pointStyle: false + }); + // Add dataset to memory chart memoryChart.data.datasets.push({ label: '', // Will be set by updateAllLabels @@ -524,12 +536,15 @@ const currentLossDataset = chart.data.datasets[chart.data.datasets.length - 1]; const currentSpeedDataset = speedChart.data.datasets[speedChart.data.datasets.length - 1]; + const currentUsingCacheDataset = + usingCacheChart.data.datasets[usingCacheChart.data.datasets.length - 1]; const currentMemoryDataset = memoryChart.data.datasets[memoryChart.data.datasets.length - 1]; const currentLrDataset = lrChart.data.datasets[lrChart.data.datasets.length - 1]; currentLossDataset.data.push(loss); currentSpeedDataset.data.push(stepsPerSecond); + currentUsingCacheDataset.data.push(data.usingCache * 1); currentMemoryDataset.data.push(Number(data.usage_bytes) / (1024 * 1024)); // Convert bigint to number then to MB currentLrDataset.data.push(data.learning_rate); @@ -551,6 +566,7 @@ const labels = Array.from({ length: maxLength }, (_, i) => i.toString()); chart.data.labels = labels; speedChart.data.labels = labels; + usingCacheChart.data.labels = labels; memoryChart.data.labels = labels; lrChart.data.labels = labels; accuracyChart.data.labels = labels; @@ -615,6 +631,7 @@ chart.update(); speedChart.update(); + usingCacheChart.update(); memoryChart.update(); lrChart.update(); accuracyChart.update(); @@ -698,6 +715,42 @@ } }); + // Initialize using cache chart + usingCacheChart = new Chart(usingCacheCanvas, { + type: 'line', + data: { + labels: [], + datasets: [] + }, + options: { + responsive: true, + animation: false, + aspectRatio: 4, + scales: { + y: { + beginAtZero: true + } + }, + plugins: { + legend: { + display: false + }, + title: { + display: true, + text: 'Using Cache', + font: { + weight: 'bold' + } + } + }, + datasets: { + line: { + order: -1 + } + } + } + }); + // Initialize memory chart memoryChart = new Chart(memoryCanvas, { type: 'line', @@ -975,6 +1028,9 @@
    +
    + +
    diff --git a/examples/ratchet-train-toy/src/trainWorker.ts b/examples/ratchet-train-toy/src/trainWorker.ts index 76ed8d13..2b4453b3 100644 --- a/examples/ratchet-train-toy/src/trainWorker.ts +++ b/examples/ratchet-train-toy/src/trainWorker.ts @@ -21,6 +21,9 @@ export interface TrainerConfig { seed?: number; layernorm_position: string; label_smoothing: number; + caching_enabled: boolean; + inplace_support: boolean; + debug_selection: string; optimizer: { optimizer_type: string; lr: number; @@ -94,6 +97,9 @@ async function trainingLoop( // Train on the batch const result = await trainer.train_on_batch(input, target); + + const logOutput = await trainer.take_step_log(); + const usingCache = logOutput?.cached ?? false; const logits = result.get('logits') as Map; const loss = result.get('loss') as Map; const attn_masks = result.get('attn_masks') as Map; @@ -171,6 +177,7 @@ async function trainingLoop( if (sessionId === currentSession) { self.postMessage({ type: 'step', + usingCache, input: input.map((x) => x.map((t) => tokenizer.ids[t])), target: target.map((t) => t.map((t) => tokenizer.ids[t])), accuracy: winCount === null ? null : winCount / EVAL_TRIAL_COUNT, From 24b4657a32bd0878aae1329ba2bcd0f9c631c3be Mon Sep 17 00:00:00 2001 From: Vin Howe <24789592+vinhowe@users.noreply.github.com> Date: Sun, 9 Mar 2025 01:07:43 -0700 Subject: [PATCH 129/146] Move trainWorker and tasks to $lib --- .../ratchet-train-toy/src/lib/trainWorker.ts | 227 ++++++++++++++++++ .../ratchet-train-toy/src/routes/+page.svelte | 4 +- 2 files changed, 229 insertions(+), 2 deletions(-) create mode 100644 examples/ratchet-train-toy/src/lib/trainWorker.ts diff --git a/examples/ratchet-train-toy/src/lib/trainWorker.ts b/examples/ratchet-train-toy/src/lib/trainWorker.ts new file mode 100644 index 00000000..d0ec1f29 --- /dev/null +++ b/examples/ratchet-train-toy/src/lib/trainWorker.ts @@ -0,0 +1,227 @@ +import { Trainer } from '@ratchet-ml/ratchet-web-train'; +import { type TaskConfigMap, tasks, type TaskSpec, type SimpleTokenizer } from '$lib/tasks'; + +let trainer: Trainer; +let sessionCounter = 0; +let currentSession = 0; +const trainingSessions: Record = {}; + +export interface TrainerConfig { + vocab_size: number; + n_embd: number; + n_layer: number; + n_head: number; + block_size: number; + batch_size: number; + dataset: keyof typeof tasks; + task_parameters: TaskConfigMap[keyof TaskConfigMap]; + activation: string; + attention_only: boolean; + position_encoding: string; + seed?: number; + layernorm_position: string; + label_smoothing: number; + caching_enabled: boolean; + inplace_support: boolean; + debug_selection: string; + optimizer: { + optimizer_type: string; + lr: number; + beta1: number; + beta2: number; + eps: number; + weight_decay: number; + momentum: number; + scheduler_type: string; + scheduler_factor: number; + scheduler_steps: number; + scheduler_eta_min: number; + }; +} + +function markStopTraining() { + Object.keys(trainingSessions).forEach((key) => { + trainingSessions[Number(key)] = false; + }); +} + +async function initializeTrainer(config: TrainerConfig) { + // Stop all existing training sessions + markStopTraining(); + + const task = tasks[config.dataset] as TaskSpec; + const tokenizer = task.createTokenizer(config.task_parameters); + + // Get the appropriate task generator + if (!task) { + console.error(`Unknown dataset type: ${config.dataset}`); + return; + } + + trainer = await new Trainer({ + ...config, + // Add 1 to the vocab size to account for the end-of-sequence token + vocab_size: tokenizer.lastToken + }); + self.postMessage({ type: 'modelReady' }); + currentSession = sessionCounter++; + trainingSessions[currentSession] = true; + trainingLoop(currentSession, config, task, tokenizer); +} + +async function trainingLoop( + sessionId: number, + config: TrainerConfig, + task: TaskSpec, + tokenizer: SimpleTokenizer +) { + if (!trainer) { + console.error('Trainer not initialized'); + return; + } + + let step = 0; + while (trainingSessions[sessionId]) { + // Skip if this isn't the current session anymore + if (sessionId !== currentSession) { + break; + } + + try { + // Combine batch size with task-specific parameters before invoking the generator + const taskConfig = { + batchSize: config.batch_size, + ...config.task_parameters + }; + const [input, target] = task.trainBatch(taskConfig); + + // Train on the batch + const result = await trainer.train_on_batch(input, target); + + const logOutput = await trainer.take_step_log(); + const usingCache = logOutput?.cached ?? false; + const logits = result.get('logits') as Map; + const loss = result.get('loss') as Map; + const attn_masks = result.get('attn_masks') as Map; + const usage_bytes = trainer.usage_bytes(); + + let winCount = null; + const EVAL_TRIAL_COUNT = 5; + + const { example: evalExample, metric: evalMetric } = task.eval(config.task_parameters); + + // After every 10 steps, evaluate the model + if (step % 10 === 0) { + const [streamingSequence, streamingTarget] = evalExample(); + let streamingExampleCompletion: number[] | null = null; + const streamingExampleLogits: number[] = []; + let streamingExampleMetric: boolean | null = null; + + // For the first eval, we'll stream it to the frontend + await trainer.generate( + streamingSequence, + /* max_tokens= */ streamingTarget.length + 1, + (tokens: number[], logitsObj: { shape: number[]; data: number[] }) => { + // For the first call (prompt), just store logits + if (streamingExampleCompletion === null) { + streamingExampleCompletion = []; + streamingExampleLogits.push(...logitsObj.data); + return; + } + + // For each subsequent token, append it and evaluate + streamingExampleCompletion.push(...tokens); + streamingExampleLogits.push(...logitsObj.data); + + // Run the metric on the current completion + const evalResult = evalMetric( + streamingExampleCompletion, + streamingTarget, + streamingSequence + ); + + streamingExampleMetric = evalResult.every((result) => result); + + // Send the streaming eval result to the frontend + if (sessionId === currentSession) { + self.postMessage({ + type: 'evalStreaming', + sequence: streamingSequence.map((t) => tokenizer.ids[t]), + completion: streamingExampleCompletion.map((t) => tokenizer.ids[t]), + target: streamingTarget.map((t) => tokenizer.ids[t]), + evalResult, + logits: { + data: streamingExampleLogits, + shape: logitsObj.shape + } + }); + } + } + ); + + winCount = streamingExampleMetric === true ? 1 : 0; + + // We'll do best of 5 evals, so we'll do the rest non-streaming + for (let i = 0; i < EVAL_TRIAL_COUNT - 1; i++) { + const [sequence, target] = evalExample(); + const result = await trainer.generate(sequence, target.length + 1); + const tokens = result.get('tokens') as number[]; + const evalResult = evalMetric(tokens, target, sequence); + if (evalResult.every((result) => result)) { + winCount++; + } + } + } + + // Only send message if this is still the current session + if (sessionId === currentSession) { + self.postMessage({ + type: 'step', + usingCache, + input: input.map((x) => x.map((t) => tokenizer.ids[t])), + target: target.map((t) => t.map((t) => tokenizer.ids[t])), + accuracy: winCount === null ? null : winCount / EVAL_TRIAL_COUNT, + loss: { + total: loss.get('total'), + tokens: loss.get('tokens') + }, + learning_rate: result.get('learning_rate'), + usage_bytes, + attn_masks: { + data: attn_masks.get('data'), + shape: attn_masks.get('shape') + }, + logits: { + data: logits.get('data'), + shape: logits.get('shape') + } + }); + } + } catch (error: Error | unknown) { + console.error('Training error in worker:', error); + if (sessionId === currentSession) { + self.postMessage({ + type: 'error', + error: error instanceof Error ? error.message : String(error) + }); + } + break; + } + step++; + // Yield to keep the worker responsive + await new Promise((resolve) => setTimeout(resolve, 0)); + } +} + +self.onmessage = async (e: MessageEvent) => { + if (e.data.type === 'stop') { + markStopTraining(); + return; + } + // If we receive a configuration object, initialize a new trainer + if (typeof e.data === 'object') { + await initializeTrainer(e.data); + } +}; + +self.postMessage({ type: 'ready' }); diff --git a/examples/ratchet-train-toy/src/routes/+page.svelte b/examples/ratchet-train-toy/src/routes/+page.svelte index 3336010a..6a17dc20 100644 --- a/examples/ratchet-train-toy/src/routes/+page.svelte +++ b/examples/ratchet-train-toy/src/routes/+page.svelte @@ -1,12 +1,12 @@