🧪 CHIMERA Tests Suite

This directory contains comprehensive tests for the CHIMERA v3.0 architecture.

📋 Test Categories

🔬 Core Functionality Tests

• test_matmul_correctness.py - Verifies GPU matrix multiplication accuracy
• test_retina_basic.py - Tests physics engine (Cellular Automata)
• test_texture_ops.py - Validates texture operations and memory management

⚡ Performance Tests

• benchmark_speed.py - Speed benchmarks for all components
• benchmark_memory.py - Memory usage and efficiency tests
• benchmark_scalability.py - Performance scaling tests

🔧 Integration Tests

• test_end_to_end.py - Full pipeline integration tests
• test_model_conversion.py - PyTorch to OpenGL model conversion
• test_system_stress.py - Stress tests for stability

🎯 Specialized Tests

• test_attention_mechanism.py - Self-attention implementation tests
• test_holographic_memory.py - Holographic memory functionality
• test_cross_platform.py - Cross-GPU compatibility tests

🚀 Running Tests

Run All Tests

# Run complete test suite
python -m pytest tests/

# Run with coverage report
python -m pytest tests/ --cov=chimera_v3

# Run with verbose output
python -m pytest tests/ -v

Run Specific Test Categories

# Core functionality only
python -m pytest tests/ -k "test_matmul or test_retina"

# Performance tests only
python -m pytest tests/ -k "benchmark"

# Integration tests only
python -m pytest tests/ -k "integration or end_to_end"

Run Individual Tests

# Matrix multiplication correctness
python tests/test_matmul_correctness.py

# Retina engine basic functionality
python tests/test_retina_basic.py

# Speed benchmarks
python tests/benchmark_speed.py

📊 Test Results Interpretation

Expected Performance

Common Test Outputs

✅ Passing Test:

test_matmul_correctness.py::test_matmul_correctness PASSED
✅ Matrix multiplication is correct and reliable

❌ Failing Test:

test_retina_basic.py::test_retina_evolution FAILED
❌ Evolution: GPU memory allocation failed

⚠️ Performance Warning:

benchmark_speed.py::benchmark_matrix_multiplication WARNING
⚠️ Performance below expected threshold (25.3ms vs 15.0ms target)

🛠️ Troubleshooting Tests

Common Issues

1. OpenGL Context Creation Failed

# Update GPU drivers
# Check OpenGL version support
python -c "import moderngl; print(moderngl.create_standalone_context().info)"

2. GPU Memory Errors

# Reduce test sizes for memory-constrained GPUs
export MODERNGL_MAX_TEXTURE_SIZE=1024

3. Platform-Specific Issues

Windows:

# Install OpenGL runtime
# Update graphics drivers via Device Manager

Linux:

# Install OpenGL development libraries
sudo apt install libgl1-mesa-dev

macOS:

# Update to latest macOS version
softwareupdate --install -a

Debug Mode

# Run tests with debug output
export CHIMERA_DEBUG=1
python -m pytest tests/ -s

# Enable GPU debugging
export MODERNGL_DEBUG=1
python tests/test_matmul_correctness.py

📈 Performance Benchmarks

Hardware Requirements

Expected Performance (RTX 3090)

Cross-Platform Performance

🔬 Research and Development

Adding New Tests

Test Structure:

def test_new_feature():
    """Test description."""
    # Arrange
    setup_test_environment()

    # Act
    result = run_feature()

    # Assert
    assert result == expected_value

Performance Test Structure:

def benchmark_new_operation():
    """Benchmark new operation."""
    # Setup
    data = prepare_test_data()

    # Measure
    start_time = time.time()
    result = run_operation(data)
    elapsed = time.time() - start_time

    # Report
    print(f"Operation took: {elapsed * 1000:.2f}ms")

Test-Driven Development

1. Write test first for new functionality
2. Run test to confirm it fails
3. Implement feature to make test pass
4. Refactor while keeping tests passing
5. Add performance tests for optimizations

📚 Test Documentation

Test Categories Explained

Unit Tests:

• Test individual functions and methods
• Fast execution (< 100ms per test)
• High coverage (>90% of code)

Integration Tests:

• Test component interactions
• Medium execution time (100ms - 5s)
• Validate end-to-end workflows

Performance Tests:

• Measure speed and memory usage
• Longer execution (5s - 5min)
• Establish performance baselines

Stress Tests:

• Test under extreme conditions
• Long execution (1min - 30min)
• Validate stability and robustness

🎯 Best Practices

Writing Good Tests

1. Single Responsibility: Each test should test one thing
2. Clear Names: Test names should describe what they test
3. Arrange-Act-Assert: Structure tests clearly
4. Independent: Tests should not depend on each other
5. Repeatable: Tests should give same results every time

Performance Testing Guidelines

1. Warm-up: Run operation once before timing
2. Multiple Runs: Average across multiple executions
3. Resource Monitoring: Track memory and GPU usage
4. Cross-Platform: Test on different hardware
5. Baseline Comparison: Compare against known good values

🤝 Contributing Tests

We welcome test contributions!

How to Contribute

1. Identify Gap: Find untested functionality
2. Write Test: Create comprehensive test
3. Add Documentation: Document what the test validates
4. Submit PR: Include test in pull request

Test Review Process

• ✅ Functionality: Does it test what it claims?
• ✅ Coverage: Does it improve test coverage?
• ✅ Performance: Does it run efficiently?
• ✅ Documentation: Is it well documented?
• ✅ Cross-Platform: Does it work on different hardware?

📞 Support

Need help with tests?

• 📖 Check CONTRIBUTING.md for guidelines
• 💬 Ask in Discord #testing channel
• 🐛 Report issues in GitHub Issues
• 📧 Email: [email protected]

Happy testing! 🧪

Comprehensive testing ensures CHIMERA's revolutionary architecture works correctly across all platforms and use cases.