Files
TinyTorch/tests/integration/test_integration_04_layers.py
Vijay Janapa Reddi e0998417ca Implement Package Manager integration testing system
Features:
- Module-level integration tests for immediate validation
- Two-tier validation: integration tests + checkpoint tests
- Quick package validation after every module completion
- Comprehensive integration test suite for all modules
- Package Manager coordination and test running

Two-Tier System:
1. Integration Test (Package Manager) - "Module works in package"
   - Quick validation (< 1 second)
   - Import validation and basic functionality
   - No conflicts with other modules

2. Checkpoint Test (existing) - "Complete capability unlocked"
   - Comprehensive validation (2-10 seconds)
   - End-to-end workflows and multi-module capabilities
   - Major milestone achievements

CLI Workflow:
- tito module complete 02_tensor
- → Export + Integration test + Checkpoint test
- → Two-tier results with different messaging
- → Immediate feedback + capability celebrations

Integration:
- 15 module integration tests covering complete course
- Package health validation and dependency checking
- Clean separation from checkpoint capability testing
- Professional Package Manager workflow
2025-09-16 21:32:08 -04:00

184 lines
6.4 KiB
Python

"""
Integration test for Module 04: Layers
Validates that the layers module integrates correctly with the TinyTorch package.
This is a quick validation test, not a comprehensive capability test.
"""
import sys
import importlib
import warnings
import numpy as np
def test_layers_module_integration():
"""Test that layers module integrates correctly with package."""
# Suppress warnings for cleaner test output
warnings.filterwarnings("ignore")
results = {
"module_name": "04_layers",
"integration_type": "layers_validation",
"tests": [],
"success": True,
"errors": []
}
try:
# Test 1: Layers module imports from package
try:
from tinytorch.core.layers import Linear, Module
results["tests"].append({
"name": "layers_import",
"status": "✅ PASS",
"description": "Layer classes import from package"
})
except ImportError as e:
results["tests"].append({
"name": "layers_import",
"status": "❌ FAIL",
"description": f"Layers import failed: {e}"
})
results["success"] = False
results["errors"].append(f"Layers import error: {e}")
return results
# Test 2: Basic layer instantiation
try:
linear = Linear(4, 2) # input_size=4, output_size=2
results["tests"].append({
"name": "layer_creation",
"status": "✅ PASS",
"description": "Linear layer can be instantiated"
})
except Exception as e:
results["tests"].append({
"name": "layer_creation",
"status": "❌ FAIL",
"description": f"Layer creation failed: {e}"
})
results["success"] = False
results["errors"].append(f"Layer creation error: {e}")
return results
# Test 3: Layer has required properties
try:
assert hasattr(linear, 'weight'), "Linear layer should have weight"
assert hasattr(linear, 'bias'), "Linear layer should have bias"
results["tests"].append({
"name": "layer_properties",
"status": "✅ PASS",
"description": "Layer has required weight and bias properties"
})
except Exception as e:
results["tests"].append({
"name": "layer_properties",
"status": "❌ FAIL",
"description": f"Layer properties test failed: {e}"
})
results["success"] = False
results["errors"].append(f"Layer properties error: {e}")
# Test 4: Integration with previous modules
try:
from tinytorch.core.tensor import Tensor
from tinytorch.core.activations import ReLU
# Test forward pass
data = np.random.randn(1, 4)
tensor = Tensor(data)
# Forward through linear layer
output = linear.forward(tensor)
assert hasattr(output, 'data'), "Layer should return tensor-like object"
results["tests"].append({
"name": "module_integration",
"status": "✅ PASS",
"description": "Layers work with Tensor and Activations"
})
except ImportError as e:
results["tests"].append({
"name": "module_integration",
"status": "⏸️ SKIP",
"description": f"Previous modules not available: {e}"
})
except Exception as e:
results["tests"].append({
"name": "module_integration",
"status": "❌ FAIL",
"description": f"Module integration failed: {e}"
})
results["success"] = False
results["errors"].append(f"Module integration error: {e}")
# Test 5: Required methods exist
try:
required_methods = ['forward', 'parameters']
missing_methods = []
for method in required_methods:
if not hasattr(linear, method):
missing_methods.append(method)
if not missing_methods:
results["tests"].append({
"name": "required_methods",
"status": "✅ PASS",
"description": "Layer has all required methods"
})
else:
results["tests"].append({
"name": "required_methods",
"status": "❌ FAIL",
"description": f"Missing methods: {missing_methods}"
})
results["success"] = False
results["errors"].append(f"Missing methods: {missing_methods}")
except Exception as e:
results["tests"].append({
"name": "required_methods",
"status": "❌ FAIL",
"description": f"Method check failed: {e}"
})
results["success"] = False
results["errors"].append(f"Method check error: {e}")
except Exception as e:
results["success"] = False
results["errors"].append(f"Unexpected error in layers integration test: {e}")
results["tests"].append({
"name": "unexpected_error",
"status": "❌ FAIL",
"description": f"Unexpected error: {e}"
})
return results
def run_integration_test():
"""Run the integration test and return results."""
return test_layers_module_integration()
if __name__ == "__main__":
# Run test when script is executed directly
result = run_integration_test()
print(f"=== Integration Test: {result['module_name']} ===")
print(f"Type: {result['integration_type']}")
print(f"Overall Success: {result['success']}")
print("\nTest Results:")
for test in result["tests"]:
print(f" {test['status']} {test['name']}: {test['description']}")
if result["errors"]:
print(f"\nErrors:")
for error in result["errors"]:
print(f" - {error}")
# Exit with appropriate code
sys.exit(0 if result["success"] else 1)