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fix: update test dependency chains to correct module numbering

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- Update MODULE_DEPENDENCIES dict to match current 01-20 structure
- Fix dependency chain comments in test_progressive_integration.py files
- Update CHECKPOINTS in test_checkpoint_integration.py
- Update module_mappings in package_manager_integration.py
- Update module_order in module_complete_orchestrator.py

The old test files referenced incorrect module numbers (06_spatial instead
of 09_convolutions) from an outdated module structure.

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This commit is contained in:
Vijay Janapa Reddi
2025-12-14 13:21:59 -05:00
parent 0c3c75678e
commit ff810c02f1
13 changed files with 163 additions and 121 deletions
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45
tinytorch/tests/integration/test_module_dependencies.py
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@@ -5,24 +5,33 @@ Tests how each module interfaces with modules that came before it
"""
# Module dependency graph for TinyTorch
# Current module structure:
# 01_tensor, 02_activations, 03_layers, 04_losses, 05_autograd,
# 06_optimizers, 07_training, 08_dataloader, 09_convolutions,
# 10_tokenization, 11_embeddings, 12_attention, 13_transformers,
# 14_profiling, 15_quantization, 16_compression, 17_memoization,
# 18_acceleration, 19_benchmarking, 20_capstone
MODULE_DEPENDENCIES = {
"01_setup": [], # No dependencies
"02_tensor": ["01_setup"], # Depends on setup
"03_activations": ["02_tensor"], # Needs Tensor
"04_layers": ["02_tensor"], # Needs Tensor
"05_dense": ["02_tensor", "04_layers"], # Needs Tensor and Layer base
"06_spatial": ["02_tensor", "04_layers"], # Needs Tensor and Layer base
"07_attention": ["02_tensor", "04_layers", "05_dense"], # Needs Tensor, Layer, Dense
"08_dataloader": ["02_tensor"], # Needs Tensor
"09_normalization": ["02_tensor", "04_layers"], # Needs Tensor and Layer
"10_autograd": ["02_tensor"], # Core dependency on Tensor
"11_optimizers": ["02_tensor", "10_autograd"], # Needs Tensor and autograd
"12_training": ["02_tensor", "10_autograd", "11_optimizers"], # Training loop deps
"13_regularization": ["02_tensor", "04_layers"], # Regularization techniques
"14_kernels": ["02_tensor"], # Low-level tensor ops
"15_benchmarking": ["02_tensor"], # Performance testing
"16_mlops": ["02_tensor", "12_training"], # Production deployment
"17_tinygpt": ["02_tensor", "04_layers", "05_dense", "07_attention", "09_normalization"] # Full stack
"01_tensor": [], # No dependencies - foundation
"02_activations": ["01_tensor"], # Needs Tensor
"03_layers": ["01_tensor"], # Needs Tensor
"04_losses": ["01_tensor"], # Needs Tensor
"05_autograd": ["01_tensor"], # Core dependency on Tensor
"06_optimizers": ["01_tensor", "05_autograd"], # Needs Tensor and autograd
"07_training": ["01_tensor", "05_autograd", "06_optimizers"], # Training loop deps
"08_dataloader": ["01_tensor"], # Needs Tensor
"09_convolutions": ["01_tensor", "03_layers"], # Needs Tensor and Layer base
"10_tokenization": ["01_tensor"], # Needs Tensor
"11_embeddings": ["01_tensor"], # Needs Tensor
"12_attention": ["01_tensor", "03_layers"], # Needs Tensor, Layer
"13_transformers": ["01_tensor", "03_layers", "12_attention"], # Full attention stack
"14_profiling": ["01_tensor"], # Performance analysis
"15_quantization": ["01_tensor"], # Optimization techniques
"16_compression": ["01_tensor"], # Optimization techniques
"17_memoization": ["01_tensor"], # Optimization techniques
"18_acceleration": ["01_tensor"], # Optimization techniques
"19_benchmarking": ["01_tensor"], # Performance testing
"20_capstone": ["01_tensor", "09_convolutions", "13_transformers"] # Full stack
}
def get_module_integration_tests(module_name: str):
@@ -57,7 +66,7 @@ def get_module_integration_tests(module_name: str):
tests.append(("test_dense_with_activations", test_dense_with_activations))
tests.append(("test_multi_layer_network", test_multi_layer_network))
elif module_name == "06_spatial":
elif module_name == "09_convolutions":
tests.append(("test_conv2d_with_tensor", test_conv2d_with_tensor))
tests.append(("test_pooling_integration", test_pooling_integration))