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‎docs/build_local.sh‎

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#!/bin/bash
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# Build TorchRL documentation locally using uv with a temporary virtual environment.
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#
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# Usage:
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# ./build_local.sh # Build docs (runs tutorials)
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# ./build_local.sh --no-run # Build docs without running tutorials (faster)
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#
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# The script creates a temporary virtual environment, installs dependencies,
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# builds the documentation, and cleans up on failure.
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set -e
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# Configuration
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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ROOT_DIR="$(dirname "$SCRIPT_DIR")"
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VENV_DIR="${ROOT_DIR}/.doc-venv"
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BUILD_DIR="${SCRIPT_DIR}/_local_build"
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PYTHON_VERSION="3.12"
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# Parse arguments
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RUN_TUTORIALS=true
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for arg in "$@"; do
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case $arg in
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--no-run)
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RUN_TUTORIALS=false
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shift
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;;
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--help|-h)
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echo "Usage: $0 [--no-run]"
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echo ""
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echo "Options:"
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echo " --no-run Skip running tutorials (faster build)"
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echo " --help, -h Show this help message"
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exit 0
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;;
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esac
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done
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# Cleanup function - always runs on exit
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cleanup() {
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local exit_code=$?
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# Restore conf.py if we modified it (do this regardless of success/failure)
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if [ -f "$SCRIPT_DIR/source/conf.py.bak" ]; then
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mv "$SCRIPT_DIR/source/conf.py.bak" "$SCRIPT_DIR/source/conf.py"
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echo "Restored conf.py from backup"
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fi
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if [ $exit_code -ne 0 ]; then
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echo ""
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echo "============================================"
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echo "Build failed with exit code $exit_code"
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echo "Cleaning up virtual environment..."
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echo "============================================"
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rm -rf "$VENV_DIR"
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echo "Virtual environment removed: $VENV_DIR"
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fi
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exit $exit_code
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}
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trap cleanup EXIT INT TERM
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echo "============================================"
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echo "TorchRL Documentation Build Script"
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echo "============================================"
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echo ""
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echo "Root directory: $ROOT_DIR"
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echo "Virtual env: $VENV_DIR"
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echo "Build output: $BUILD_DIR"
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echo "Run tutorials: $RUN_TUTORIALS"
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echo ""
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# Check for uv
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if ! command -v uv &> /dev/null; then
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echo "Error: 'uv' is not installed."
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echo "Install it with: curl -LsSf https://astral.sh/uv/install.sh | sh"
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exit 1
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fi
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# Remove existing venv if it exists
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if [ -d "$VENV_DIR" ]; then
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echo "Removing existing virtual environment..."
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rm -rf "$VENV_DIR"
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fi
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# Create virtual environment
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echo "Creating virtual environment with Python $PYTHON_VERSION..."
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uv venv "$VENV_DIR" --python "$PYTHON_VERSION"
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# Activate virtual environment
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echo "Activating virtual environment..."
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source "$VENV_DIR/bin/activate"
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# Upgrade pip and install build tools
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echo "Installing build tools..."
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uv pip install --upgrade pip setuptools ninja packaging "pybind11[global]" cmake
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# Install PyTorch (nightly for latest features)
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echo "Installing PyTorch..."
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uv pip install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cpu
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# Install tensordict from git
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echo "Installing tensordict..."
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uv pip install git+https://github.com/pytorch/tensordict.git
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# Install torchrl in editable mode
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echo "Installing torchrl..."
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cd "$ROOT_DIR"
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uv pip install -e . --no-build-isolation
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# Install documentation requirements
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echo "Installing documentation requirements..."
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# First install pytorch_sphinx_theme separately (editable git not supported by uv -r)
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uv pip install git+https://github.com/pytorch/pytorch_sphinx_theme.git
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# Install remaining requirements (skip the editable line)
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grep -v "pytorch_sphinx_theme" "$SCRIPT_DIR/requirements.txt" | uv pip install -r -
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# Verify installation
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echo "Verifying torchrl installation..."
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python -c "import torchrl; print(f'TorchRL version: {torchrl.__version__}')"
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# Set up environment for building
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export MAX_IDLE_COUNT=180
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export BATCHED_PIPE_TIMEOUT=180
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export TORCHRL_CONSOLE_STREAM=stdout
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# Clear old MuJoCo environment variables that might interfere with MuJoCo 3.x
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unset MUJOCO_PATH
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unset MUJOCO_PY_MUJOCO_PATH
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unset LD_LIBRARY_PATH # Reset to avoid old MuJoCo libs
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# Set plot_gallery based on mode
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# Create backup of conf.py for cleanup to restore
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cp "$SCRIPT_DIR/source/conf.py" "$SCRIPT_DIR/source/conf.py.bak"
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if [ "$RUN_TUTORIALS" = true ]; then
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echo ""
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echo "Note: Tutorials WILL be executed"
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# Enable plot_gallery (replace both True and "False" variants)
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sed -i '' 's/"plot_gallery": "False"/"plot_gallery": True/' "$SCRIPT_DIR/source/conf.py"
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sed -i '' 's/"plot_gallery": False/"plot_gallery": True/' "$SCRIPT_DIR/source/conf.py"
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else
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echo ""
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echo "Note: Tutorials will NOT be executed (--no-run mode)"
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# Disable plot_gallery
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sed -i '' 's/"plot_gallery": True/"plot_gallery": "False"/' "$SCRIPT_DIR/source/conf.py"
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fi
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# Build documentation
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echo ""
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echo "============================================"
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echo "Building documentation..."
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echo "============================================"
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cd "$SCRIPT_DIR"
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sphinx-build ./source "$BUILD_DIR" -v -j auto
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echo ""
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echo "============================================"
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echo "Documentation built successfully!"
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echo "============================================"
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echo ""
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echo "Output: $BUILD_DIR"
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echo ""
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echo "To view the documentation, run:"
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echo " python -m http.server 8000 -d $BUILD_DIR"
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echo " # Then open http://localhost:8000 in your browser"
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echo ""
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echo "To clean up the virtual environment, run:"
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echo " rm -rf $VENV_DIR"

‎docs/requirements.txt‎

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sphinx_design
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torchvision
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dm_control
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mujoco<3.3.6
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dm_control>=1.0.0
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mujoco>=3.0.0,<3.3.6
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gymnasium[classic_control,atari]
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pygame
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tqdm
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ipython
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imageio[ffmpeg,pyav]
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memory_profiler
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pyrender
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pytest
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vmas
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onnxscript
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hydra-core>=1.1
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omegaconf
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hydra-submitit-launcher
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transformers
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accelerate
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sentencepiece

‎docs/source/conf.py‎

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intersphinx_mapping = {
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"torch": ("https://pytorch.org/docs/stable/", None),
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"tensordict": ("https://pytorch.github.io/tensordict/", None),
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"tensordict": ("https://docs.pytorch.org/tensordict/stable/", None),
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# "torchrl": ("https://pytorch.org/rl/", None),
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"torchaudio": ("https://pytorch.org/audio/stable/", None),
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"torchtext": ("https://pytorch.org/text/stable/", None),
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"download_all_examples": True,
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"abort_on_example_error": True,
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# "show_memory": True,
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"plot_gallery": True,
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"plot_gallery": "False",
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"capture_repr": ("_repr_html_", "__repr__"), # capture representations
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"write_computation_times": True,
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# "compress_images": ("images", "thumbnails"),

‎docs/source/reference/config.rst‎

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:toctree: generated/
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:template: rl_template_class.rst
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DataCollectorConfig
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SyncDataCollectorConfig
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AsyncDataCollectorConfig
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MultiSyncDataCollectorConfig
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MultiaSyncDataCollectorConfig
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CollectorConfig
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AsyncCollectorConfig
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MultiSyncCollectorConfig
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MultiAsyncCollectorConfig
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Replay Buffer and Storage Configurations
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

‎docs/source/reference/cudnn_persistent_rnn.rst‎

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:orphan:
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.. note::
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In some circumstances when using the CUDNN backend with CuDNN 7.2.1, the backward
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can be up to 5x slower when called with a batch_first input. This is expected to be fixed

‎docs/source/reference/cudnn_rnn_determinism.rst‎

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:orphan:
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.. note::
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If the following conditions are not met, the backward pass will use a slower but more
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memory efficient implementation:

‎docs/source/reference/data_datasets.rst‎

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.. currentmodule:: torchrl.data
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.. _TED-format:
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Datasets
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========
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TorchRL provides dataset utilities for offline RL and data management.
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TorchRL Episode Data (TED) Format
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---------------------------------
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The TED format is TorchRL's standard data layout for offline RL datasets. It structures
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trajectories as nested tensors where each element contains the full trajectory data,
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making it efficient for sequence-based sampling and training.
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.. autosummary::
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:toctree: generated/
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:template: rl_template.rst

‎docs/source/reference/llms_collectors.rst‎

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:orphan:
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.. currentmodule:: torchrl.collectors.llm
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LLM Collectors

‎docs/source/reference/llms_data.rst‎

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:orphan:
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.. currentmodule:: torchrl.data.llm
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Data Structures

‎docs/source/reference/llms_envs.rst‎

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.. currentmodule:: torchrl.envs.llm
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LLM Environments

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