Files
TinyTorch/tests
Vijay Janapa Reddi 79db89930a Complete comprehensive testing for API simplification
Added full test suite following TinyTorch testing conventions:

 UNIT TESTS (test_api_simplification.py):
- 23 comprehensive tests covering all API components
- Tests Parameter function, Module base class, Linear/Conv2d layers
- Tests functional interface (F.relu, F.flatten, F.max_pool2d)
- Tests optimizer integration and backward compatibility
- Tests complete model workflows (MLP, CNN)

 INTEGRATION TESTS (test_api_simplification_integration.py):
- Cross-component integration testing
- Complete workflow validation (model → optimizer → training setup)
- PyTorch compatibility verification
- Nested module parameter collection testing

 EXAMPLE FIXES:
- Fixed optimizer parameter names (lr → learning_rate)
- Examples demonstrate real-world usage patterns
- Show dramatic code simplification vs old API

🎯 TEST RESULTS:
- Unit Tests: 23/23 PASS 
- Integration Tests: 8/8 PASS 
- API simplification validated with comprehensive coverage

The testing validates that the API simplification maintains educational
value while providing clean PyTorch-compatible interfaces.
2025-09-23 08:24:50 -04:00
..
2025-09-17 19:29:16 -04:00
2025-07-15 10:03:05 -04:00

🧪 TinyTorch Integration Tests

⚠️ CRITICAL DIRECTORY - DO NOT DELETE

This directory contains 17 integration test files that verify cross-module functionality across the entire TinyTorch system. These tests represent significant development effort and are essential for:

  • Module integration validation
  • Cross-component compatibility
  • Real-world ML pipeline testing
  • System-level regression detection

📁 Test Structure

  • test_*_integration.py - Cross-module integration tests
  • test_utils.py - Shared testing utilities
  • test_integration_report.md - Test documentation

🧪 Integration Test Coverage

Foundation Integration

  • test_tensor_activations_integration.py - Tensor + Activations
  • test_layers_networks_integration.py - Layers + Dense Networks
  • test_tensor_autograd_integration.py - Tensor + Autograd

Architecture Integration

  • test_tensor_attention_integration.py - NEW: Tensor + Attention mechanisms
  • test_attention_pipeline_integration.py - NEW: Complete transformer-like pipelines
  • test_tensor_cnn_integration.py - Tensor + Spatial/CNN
  • test_cnn_networks_integration.py - Spatial + Dense Networks
  • test_cnn_pipeline_integration.py - Complete CNN pipelines

Training & Data Integration

  • test_dataloader_tensor_integration.py - DataLoader + Tensor
  • test_training_integration.py - Complete training workflows
  • test_ml_pipeline_integration.py - End-to-end ML pipelines

Inference Serving Integration

  • test_compression_integration.py - Model compression
  • test_kernels_integration.py - Custom operations
  • test_benchmarking_integration.py - Performance measurement
  • test_mlops_integration.py - Deployment and serving

🔧 Usage

# Run all integration tests
pytest tests/ -v

# Run specific module integration
pytest tests/test_tensor_attention_integration.py -v
pytest tests/test_attention_pipeline_integration.py -v

# Run attention-related tests
pytest tests/ -k "attention" -v

🚨 Recovery Instructions

If accidentally deleted:

git checkout HEAD -- tests/
git status  # Verify recovery

📊 Test Coverage

These integration tests complement the inline tests in each module's *_dev.py files, providing comprehensive system validation with focus on:

  • Real component integration (not mocks)
  • Cross-module compatibility
  • Realistic ML workflows (classification, seq2seq, transformers)
  • Performance and scalability