ENH: Use logging in project classes. BUG: Fixed tests.

.github/workflows/README.md

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+# GitHub Actions Workflows
+
+This directory contains GitHub Actions workflows for automated testing and CI/CD.
+
+## Workflows
+
+### `test.yml` - Main Test Suite
+
+Runs on every push and pull request to main branches. Includes:
+
+- **test-cpu**: Unit tests on CPU across Python 3.10, 3.11, and 3.12
+  - Uses PyTorch CPU version to avoid GPU dependencies
+  - Runs tests marked with `unit` and excludes GPU-requiring tests
+  - Generates coverage reports
+
+- **test-gpu**: Tests on self-hosted GPU runners (if available)
+  - Uses PyTorch with CUDA 12.6 support
+  - Runs all tests except those marked as slow
+  - Requires self-hosted runner with `[self-hosted, linux, gpu]` labels
+
+- **test-integration**: Integration tests on CPU
+  - Runs after CPU tests pass
+  - Tests marked with `integration` marker
+
+- **code-quality**: Static code analysis
+  - Black, isort, ruff, flake8 checks
+  - Does not fail the build (continue-on-error: true)
+
+### `test-slow.yml` - Long-Running Tests
+
+Runs nightly or on manual trigger. Includes:
+
+- **test-slow-gpu**: Slow tests requiring GPU
+  - Tests marked with `slow` marker
+  - Extended timeout (3600 seconds)
+  - Uses self-hosted GPU runners
+
+## Caching Strategy
+
+The workflows use multiple caching layers to speed up builds:
+
+1. **Python package cache** via `setup-python` action
+   - Caches pip packages based on `pyproject.toml` hash
+
+2. **Additional pip cache** via `actions/cache`
+   - Caches `~/.cache/pip` directory
+   - Separate keys for CPU, GPU, and integration tests
+   - Hierarchical restore keys for fallback
+
+## GPU Support
+
+### Self-Hosted Runners
+
+GPU tests require self-hosted runners with:
+- Linux OS
+- NVIDIA GPU with CUDA 12.6+ support
+- Runner labels: `[self-hosted, linux, gpu]`
+
+### Setting Up Self-Hosted GPU Runners
+
+1. **Install GitHub Actions Runner**:
+   ```bash
+   # Download and configure runner from GitHub repository Settings > Actions > Runners
+   ```
+
+2. **Install NVIDIA Drivers and CUDA**:
+   ```bash
+   # Install NVIDIA drivers
+   sudo apt-get install nvidia-driver-535
+
+   # Install CUDA toolkit 12.6
+   wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.0-1_all.deb
+   sudo dpkg -i cuda-keyring_1.0-1_all.deb
+   sudo apt-get update
+   sudo apt-get install cuda-toolkit-12-6
+   ```
+
+3. **Configure Runner Labels**:
+   - Add labels: `self-hosted`, `linux`, `gpu`
+   - Verify GPU is accessible: `nvidia-smi`
+
+4. **Start the Runner**:
+   ```bash
+   ./run.sh
+   ```
+
+### GitHub-Hosted Runners
+
+GitHub-hosted runners do **not** have GPU support. GPU tests will be skipped automatically if no self-hosted runners are available (`continue-on-error: true`).
+
+## Test Dependencies
+
+Test dependencies are installed from `pyproject.toml`:
+
+```bash
+pip install -e ".[test]"
+```
+
+This installs:
+- pytest >= 7.0.0
+- pytest-cov >= 4.0.0
+- pytest-xdist >= 3.0.0
+- pytest-timeout >= 2.0.0
+- coverage[toml] >= 7.0.0
+
+## Test Markers
+
+Tests should be marked appropriately:
+
+```python
+import pytest
+
+@pytest.mark.unit
+def test_simple_function():
+    """Fast unit test"""
+    pass
+
+@pytest.mark.integration
+def test_full_pipeline():
+    """Integration test"""
+    pass
+
+@pytest.mark.slow
+def test_long_running():
+    """Long-running test"""
+    pass
+
+@pytest.mark.requires_gpu
+def test_gpu_function():
+    """Test requiring GPU"""
+    if not torch.cuda.is_available():
+        pytest.skip("GPU not available")
+    pass
+```
+
+## Running Tests Locally
+
+### CPU Tests
+```bash
+# Install dependencies
+pip install -e ".[test]"
+
+# Run unit tests
+pytest tests/ -m "unit and not requires_gpu"
+
+# Run with coverage
+pytest tests/ -m "unit and not requires_gpu" --cov=physiomotion4d
+```
+
+### GPU Tests
+```bash
+# Install with CUDA support
+pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126
+pip install -e ".[test]"
+
+# Run all tests (including GPU)
+pytest tests/ -m "not slow"
+
+# Run slow tests
+pytest tests/ -m "slow"
+```
+
+## Coverage Reports
+
+Coverage reports are:
+1. Uploaded to Codecov (if configured)
+2. Stored as artifacts for 7 days
+3. Available as HTML reports in the `htmlcov/` directory
+
+## Troubleshooting
+
+### GPU Tests Not Running
+
+If GPU tests are not running:
+1. Verify self-hosted runner is online: Settings > Actions > Runners
+2. Check runner labels include `gpu`
+3. Verify `nvidia-smi` works on the runner
+4. Check workflow logs for runner assignment
+
+### Cache Not Working
+
+If builds are slow:
+1. Check cache hit/miss in workflow logs
+2. Verify `pyproject.toml` hasn't changed unexpectedly
+3. Try clearing caches: Settings > Actions > Caches
+
+### Test Failures
+
+For test failures:
+1. Check individual test logs in the workflow run
+2. Run tests locally to reproduce
+3. Use `pytest -v --tb=long` for detailed error traces
+4. Check if tests are marked correctly (unit/integration/slow/requires_gpu)
+