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Installation

This guide covers installing HETorch and its dependencies.

Prerequisites​

Required​

  • Python: 3.9 or higher
  • PyTorch: 2.0 or higher
  • Operating System: Linux, macOS, or Windows

Optional​

  • uv: Fast Python package installer (recommended)
  • graphviz: For graph visualization (optional)

Installation Methods​

uv is a fast Python package installer and resolver.

# Install uv if you don't have it
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone the repository
git clone https://github.com/visualDust/HETorch
cd hetorch

# Install HETorch
uv pip install -e .

# Install with development dependencies
uv pip install -e ".[dev]"

Method 2: Using pip​

# Clone the repository
git clone https://github.com/visualDust/HETorch
cd hetorch

# Install HETorch
pip install -e .

# Install with development dependencies
pip install -e ".[dev]"

Method 3: From Source (Development)​

# Clone the repository
git clone https://github.com/visualDust/HETorch
cd hetorch

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install in editable mode
pip install -e ".[dev]"

Optional Dependencies​

Graphviz (For Visualization)​

The GraphVisualizationPass requires graphviz for rendering computation graphs.

Ubuntu/Debian:

sudo apt-get install graphviz

macOS:

brew install graphviz

Windows: Download from graphviz.org

Python package:

pip install graphviz

Development Tools​

For contributing to HETorch:

# Install development dependencies
pip install -e ".[dev]"

# This includes:
# - pytest: Testing framework
# - black: Code formatter
# - ruff: Linter
# - mypy: Type checker

Verifying Installation​

Basic Verification​

import hetorch
print(hetorch.__version__)

Run Tests​

# Run all tests
pytest tests/

# Run specific test file
pytest tests/test_compiler.py -v

# Run with coverage
pytest tests/ --cov=hetorch --cov-report=html

Run Examples​

# Run basic example
python examples/basic_linear.py

# Run neural network example
python examples/phase2_neural_network.py

Expected output:

Original model output: tensor([...])
Compiled model output: tensor([...])
Max difference: 0.0001

Troubleshooting​

PyTorch Not Found​

If you get ModuleNotFoundError: No module named 'torch':

# Install PyTorch
pip install torch

# Or with CUDA support
pip install torch --index-url https://download.pytorch.org/whl/cu118

Import Errors​

If you get import errors after installation:

# Reinstall in editable mode
pip install -e .

# Or force reinstall
pip install --force-reinstall -e .

Test Failures​

If tests fail:

  1. Ensure all dependencies are installed:

    pip install -e ".[dev]"

  2. Check Python version:

    python --version  # Should be 3.9+

  3. Clear cache and reinstall:

    rm -rf build/ dist/ *.egg-info
    pip install -e .

Graphviz Issues​

If GraphVisualizationPass fails:

  1. Install system graphviz (see above)
  2. Install Python package: 
    pip install graphviz
  3. Verify installation: 
    dot -V  # Should print graphviz version

Development Setup​

For contributing to HETorch:

# Clone repository
git clone https://github.com/visualDust/HETorch
cd hetorch

# Create virtual environment
python -m venv .venv
source .venv/bin/activate

# Install with development dependencies
pip install -e ".[dev]"

# Install pre-commit hooks (optional)
pre-commit install

# Run tests
pytest tests/

# Format code
black hetorch/ tests/ examples/

# Lint code
ruff check hetorch/ tests/ examples/

# Type check
mypy hetorch/

Uninstallation​

pip uninstall hetorch

Next Steps​