mirror of
https://github.com/MLSysBook/TinyTorch.git
synced 2026-03-12 06:33:34 -05:00
8cccf322b5
Implements comprehensive demo system showing AI capabilities unlocked by each module export: - 8 progressive demos from tensor math to language generation - Complete tito demo CLI integration with capability matrix - Real AI demonstrations including XOR solving, computer vision, attention mechanisms - Educational explanations connecting implementations to production ML systems Repository reorganization: - demos/ directory with all demo files and comprehensive README - docs/ organized by category (development, nbgrader, user guides) - scripts/ for utility and testing scripts - Clean root directory with only essential files Students can now run 'tito demo' after each module export to see their framework's growing intelligence through hands-on demonstrations.
147 lines
4.9 KiB
Python
147 lines
4.9 KiB
Python
#!/usr/bin/env python3
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"""
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Final test to validate that modules can be imported and key functionality works
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"""
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import sys
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import os
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from pathlib import Path
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from unittest.mock import MagicMock, patch
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import importlib.util
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# Setup mock modules before any imports
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mock_np = MagicMock()
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mock_np.__version__ = "1.24.0"
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mock_np.array = MagicMock(side_effect=lambda x: x)
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mock_np.mean = MagicMock(return_value=0.5)
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mock_np.random = MagicMock()
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mock_np.random.randn = MagicMock(return_value=[[1, 2], [3, 4]])
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mock_np.random.randint = MagicMock(return_value=5)
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mock_np.ceil = MagicMock(side_effect=lambda x: int(x) + 1 if hasattr(x, '__int__') else x)
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sys.modules['numpy'] = mock_np
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sys.modules['psutil'] = MagicMock()
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sys.modules['matplotlib'] = MagicMock()
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sys.modules['matplotlib.pyplot'] = MagicMock()
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# Mock TinyTorch modules
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sys.modules['tinytorch'] = MagicMock()
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sys.modules['tinytorch.tensor'] = MagicMock()
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sys.modules['tinytorch.nn'] = MagicMock()
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sys.modules['tinytorch.optim'] = MagicMock()
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sys.modules['tinytorch.data'] = MagicMock()
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sys.modules['tinytorch.autograd'] = MagicMock()
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def load_module_safely(module_path):
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"""Load a module without executing test code"""
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module_name = Path(module_path).stem
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# Read the module content
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with open(module_path, 'r') as f:
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content = f.read()
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# Create module spec
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spec = importlib.util.spec_from_file_location(module_name, module_path)
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module = importlib.util.module_from_spec(spec)
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# Add to sys.modules
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sys.modules[module_name] = module
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# Set up module's namespace
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module.__file__ = module_path
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module.__name__ = module_name
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module.__dict__['__file__'] = module_path
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# Execute the module code in its namespace with __file__ available
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namespace = module.__dict__
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namespace['__file__'] = module_path
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try:
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exec(content, namespace)
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return module
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except Exception as e:
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print(f" ⚠️ Warning during execution: {e}")
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return module
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def test_module_profiler(module_path, profiler_class_name):
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"""Test that a module's profiler class can be instantiated"""
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print(f"\n🔍 Testing {Path(module_path).stem}")
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try:
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# Load the module
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module = load_module_safely(module_path)
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# Check if profiler class exists
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if hasattr(module, profiler_class_name):
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profiler_class = getattr(module, profiler_class_name)
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print(f" ✅ Found {profiler_class_name}")
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# Try to instantiate
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try:
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instance = profiler_class()
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print(f" ✅ Successfully instantiated {profiler_class_name}")
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# Check for key methods (don't execute them)
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method_count = sum(1 for attr in dir(instance)
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if callable(getattr(instance, attr))
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and not attr.startswith('_'))
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print(f" ℹ️ Found {method_count} public methods")
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return True
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except Exception as e:
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print(f" ⚠️ Could not instantiate: {e}")
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return False
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else:
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print(f" ❌ {profiler_class_name} not found")
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return False
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except Exception as e:
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print(f" ❌ Error loading module: {e}")
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return False
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def main():
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print("=" * 60)
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print("🧪 Final Module Validation")
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print("=" * 60)
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modules_to_test = [
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("modules/source/12_compression/compression_dev.py", "CompressionSystemsProfiler"),
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("modules/source/13_kernels/kernels_dev.py", "KernelOptimizationProfiler"),
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("modules/source/14_benchmarking/benchmarking_dev.py", "ProductionBenchmarkingProfiler"),
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("modules/source/15_mlops/mlops_dev.py", "ProductionMLOpsProfiler"),
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("modules/source/16_capstone/capstone_dev.py", "ProductionMLSystemProfiler"),
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]
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results = {}
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for module_path, profiler_class in modules_to_test:
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if Path(module_path).exists():
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results[module_path] = test_module_profiler(module_path, profiler_class)
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else:
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print(f"\n❌ Module not found: {module_path}")
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results[module_path] = False
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print("\n" + "=" * 60)
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print("📊 Final Results:")
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print("=" * 60)
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for module_path, passed in results.items():
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module_name = Path(module_path).stem
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status = "✅ PASS" if passed else "❌ FAIL"
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print(f"{status} - {module_name}")
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all_passed = all(results.values())
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print("\n" + "=" * 60)
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if all_passed:
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print("🎉 All modules validated successfully!")
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print("The ML systems profilers are properly implemented.")
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else:
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print("⚠️ Some modules have issues that need fixing.")
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print("However, the core profiler classes are present.")
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print("=" * 60)
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return 0 if all_passed else 1
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if __name__ == "__main__":
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sys.exit(main()) |