Minor improvements and new features

.github/workflows/build_test_wheel.yml

@@ -38,42 +38,88 @@ jobs:
 
     steps:
     - uses: actions/checkout@v4
-    - name: Set up Python 3.11
-      uses: actions/setup-python@v3
+    - name: Cache conda packages
+      id: conda-cache
+      uses: actions/cache@v4
       with:
-        python-version: '3.11'
-    - name: Add conda to system path
-      run: |
-        # $CONDA is an environment variable pointing to the root of the miniconda directory
-        echo $CONDA/bin >> $GITHUB_PATH
+        path: /home/runner/miniconda3/pkgs
+        key: ${{ runner.os }}-conda-${{ hashFiles('environment-ci.yml') }}
+        restore-keys: |
+          ${{ runner.os }}-conda-
+    - name: Set up conda
+      uses: conda-incubator/setup-miniconda@v3
+      with:
+        miniforge-variant: Miniforge3
+        miniforge-version: latest
+        environment-file: environment-ci.yml
+        activate-environment: autoforge
+        installation-dir: /home/runner/miniconda3
+        auto-activate-base: false
+        pkgs-dirs: /home/runner/miniconda3/pkgs
+        use-mamba: true
+        use-only-tar-bz2: true
     - name: Install dependencies
       run: |
-        #conda env update --file environment.yml --name base
-        pip install .
+        "${CONDA}/bin/conda" run -n autoforge python -m pip install .
   verify-lint:
     runs-on: ubuntu-latest
     needs: build-package
     steps:
     - uses: actions/checkout@v4
+    - name: Cache conda packages
+      id: conda-cache
+      uses: actions/cache@v4
+      with:
+        path: /home/runner/miniconda3/pkgs
+        key: ${{ runner.os }}-conda-${{ hashFiles('environment-ci.yml') }}
+        restore-keys: |
+          ${{ runner.os }}-conda-
+    - name: Set up conda
+      uses: conda-incubator/setup-miniconda@v3
+      with:
+        miniforge-variant: Miniforge3
+        miniforge-version: latest
+        environment-file: environment-ci.yml
+        activate-environment: autoforge
+        installation-dir: /home/runner/miniconda3
+        auto-activate-base: false
+        pkgs-dirs: /home/runner/miniconda3/pkgs
+        use-mamba: true
+        use-only-tar-bz2: true
     - name: Lint with flake8
       run: |
-        conda install flake8
-        conda init
-        conda activate base
+        "${CONDA}/bin/conda" run -n autoforge python -m pip install flake8
         # stop the build if there are Python syntax errors or undefined names
-        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        "${CONDA}/bin/conda" run -n autoforge flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
         # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+        "${CONDA}/bin/conda" run -n autoforge flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
   test-package:
     runs-on: ubuntu-latest
     needs: build-package
     steps:
     - uses: actions/checkout@v4
+    - name: Cache conda packages
+      id: conda-cache
+      uses: actions/cache@v4
+      with:
+        path: /home/runner/miniconda3/pkgs
+        key: ${{ runner.os }}-conda-${{ hashFiles('environment-ci.yml') }}
+        restore-keys: |
+          ${{ runner.os }}-conda-
+    - name: Set up conda
+      uses: conda-incubator/setup-miniconda@v3
+      with:
+        miniforge-variant: Miniforge3
+        miniforge-version: latest
+        environment-file: environment-ci.yml
+        activate-environment: autoforge
+        installation-dir: /home/runner/miniconda3
+        auto-activate-base: false
+        pkgs-dirs: /home/runner/miniconda3/pkgs
+        use-mamba: true
+        use-only-tar-bz2: true
     - name: Test with pytest
       run: |
-        conda install pytest
-        conda init
-        conda activate base
-        pytest # TODO add specifications of test
+        "${CONDA}/bin/conda" run -n autoforge python -m pytest # TODO add specifications of test
 
 

.gitignore

@@ -170,3 +170,6 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+.vscode/browse.vc.db
+.vscode/browse.vc.db-shm
+.vscode/browse.vc.db-wal

.vscode/c_cpp_properties.json

@@ -0,0 +1,20 @@
+{
+  "configurations": [
+    {
+      "browse": {
+        "databaseFilename": "${workspaceFolder}/.vscode/browse.vc.db",
+        "limitSymbolsToIncludedHeaders": false
+      },
+      "includePath": [
+        "/opt/ros/jazzy/include/**",
+        "/usr/include/**"
+      ],
+      "name": "ros2",
+      "intelliSenseMode": "gcc-x64",
+      "compilerPath": "/usr/bin/gcc",
+      "cStandard": "gnu11",
+      "cppStandard": "c++17"
+    }
+  ],
+  "version": 4
+}

TODO

@@ -44,6 +44,7 @@
   - [ ] Review and unit test selection criteria implementation
   - [ ] Extend augs-trainer integration to allow "discard" option in validation module
   - [x] Implement tailoring of RandomAffine to make it border crossing aware
+  - [ ] Migrate documentation from Read The Docs to something more controllable and less restrictive
 
 - [ ] v0.3.X
   - [x] Implement custom adaptive pooling layers for ONNx static export

environment-ci.yml

@@ -0,0 +1,9 @@
+name: autoforge
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python=3.11
+  - pip
+  - setuptools
+  - wheel

environment.yml

@@ -197,7 +197,6 @@ dependencies:
       - pyasn1-modules==0.4.1
       - pybind11==2.13.6
       - pycparser==2.22
-      - pycuda==2025.1
       - pydantic==2.10.6
       - pydantic-core==2.27.2
       - pygments==2.19.1

pyTorchAutoForge.code-workspace

@@ -46,5 +46,13 @@
 			"path": "../ml-based-centroiding"
 		}
 	],
-	"settings": {}
+	"settings": {
+		"ROS2.distro": "jazzy",
+		"python.autoComplete.extraPaths": [
+			"/opt/ros/jazzy/lib/python3.12/site-packages"
+		],
+		"python.analysis.extraPaths": [
+			"/opt/ros/jazzy/lib/python3.12/site-packages"
+		]
+	}
 }

pyTorchAutoForge/api/tensorrt/TRTengineExporter.py

@@ -2,7 +2,6 @@
 import torch 
 import numpy as np
 import sys, os, shutil
-import pycuda as cuda
 import subprocess
 from enum import Enum
 from pyTorchAutoForge.api.onnx import ModelHandlerONNx
@@ -167,4 +166,4 @@ def build_engine_from_onnx(self, input_onnx_model: str | None = None, output_eng
             print("Engine built successfully and saved to:", output_engine_path)
 
         else:
-            raise ValueError("Invalid TRTengineExporterMode value. Please select TRTEXEC or PYTHON.")
+            raise ValueError("Invalid TRTengineExporterMode value. Please select TRTEXEC or PYTHON.")

pyTorchAutoForge/datasets/LabelsClasses.py

@@ -30,6 +30,8 @@ class PTAF_Datakey(enum.Enum):
     PHASE_ANGLE = 9  # Phase angle of the scene
     CENTRE_OF_FIGURE = 10  # Centre of figure of the object
     APPARENT_SIZE = 11  # Apparent size of the object in pixels
+    SUN_DIRECTION_ANGLE_FROM_X = 12  # Angle of the sun direction from the x-axis in radians
+
 
     def get_lbl_vector_size(self):
         # Define sizes for data keys
@@ -49,7 +51,8 @@ def get_lbl_vector_size(self):
             PTAF_Datakey.REFERENCE_SIZE: 1,
             PTAF_Datakey.PHASE_ANGLE: 1,
             PTAF_Datakey.CENTRE_OF_FIGURE: 2,  # x, y coordinates of the centre of figure
-            PTAF_Datakey.APPARENT_SIZE: 1  # Apparent size in pixels
+            PTAF_Datakey.APPARENT_SIZE: 1,  # Apparent size in pixels
+            PTAF_Datakey.SUN_DIRECTION_ANGLE_FROM_X: 1  # Angle of the sun direction from the x-axis in radians
         }
 
         return sizes.get(self, None)
@@ -235,7 +238,7 @@ class AuxiliaryLabels(BaseLabelsContainer):
         default=-1.0, metadata={'yaml': 'dPhaseAngleInDeg'})
 
     light_direction_rad_angle_from_x: float = field(
-        default=0.0, metadata={'yaml': 'dLightDirectionRadAngleFromX'})
+        default=-1.0, metadata={'yaml': 'dLightDirectionRadAngleFromX'})
 
     object_shape_matrix_cam_frame: list[list[float]] = field(
         default_factory=list, metadata={'yaml': 'dObjectShapeMatrix_CamFrame'})
@@ -311,6 +314,9 @@ def __getattr__(self, item: str) -> Any:
 
         elif item == PTAF_Datakey.APPARENT_SIZE:
             return float(self.geometric.obj_apparent_size_in_pix)
+
+        elif item == PTAF_Datakey.SUN_DIRECTION_ANGLE_FROM_X:
+            return float(self.auxiliary.light_direction_rad_angle_from_x)
 
         else:
             # Raise AttributeError to maintain standard behavior

pyTorchAutoForge/model_building/backbones/base_backbones.py

@@ -25,6 +25,7 @@ class FeatureExtractorConfig(BaseConfigClass):
     # Dimension of the final linear layer (if you want to add a linear layer)
     output_size: int | None = None
     remove_classifier: bool = True
+    remove_gap_layer: bool = False
     device: torch.device | str | None = None
     input_channels: int = 3 # Placeholder value
 

pyTorchAutoForge/model_building/backbones/efficient_net.py

@@ -5,6 +5,7 @@
 
 import torch
 import torch.nn.functional as F
+import warnings
 from pyTorchAutoForge.model_building.backbones.spatial_features_operators import SpatialKptFeatureSoftmaxLocator
 from pyTorchAutoForge.model_building.poolingBlocks import CustomAdaptiveMaxPool2d
 
@@ -22,7 +23,13 @@ def __init__(self, cfg: EfficientNetConfig):
 
         # Extract the “features” part all children except the final classifier/sequential
         modules = list(model.children())[:-1]
+
         if cfg.output_type == 'last':
+
+            if hasattr(cfg, 'remove_gap_layer'):
+                # Remove the final global average pooling layer (AdaptiveAvgPool2d) if specified in config
+                modules = modules[0] if isinstance(modules[-1], nn.AdaptiveAvgPool2d) and cfg.remove_gap_layer else modules
+
             # Wrap as a single ModuleList so that forward is simple
             self.feature_extractor = nn.ModuleList([nn.Sequential(*modules)])
 
@@ -35,8 +42,10 @@ def __init__(self, cfg: EfficientNetConfig):
             self.feature_extractor = nn.ModuleList(
                 list(feature_extractor_modules.children()))
 
-            # Add last layer (global adaptive pooling) from modules
-            self.feature_extractor.append(modules[1])
+            # Add last layer (global adaptive pooling) from modules if not removed
+            if hasattr(cfg, 'remove_gap_layer'):
+                if isinstance(modules[-1], nn.AdaptiveAvgPool2d) and not(cfg.remove_gap_layer):
+                    self.feature_extractor.append(modules[-1])
 
             # Build average pooling layer
             self.feature_spill_preprocessor = nn.ModuleDict()

pyproject.toml

@@ -56,7 +56,6 @@ classifiers=[
 [project.optional-dependencies]
 cuda_all = [
     "pynvml; platform_machine == 'x86_64'", 
-    "pycuda; platform_machine == 'x86_64'", 
 ]
 
 [tool.setuptools.packages.find]