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			89 lines
		
	
	
		
			2.8 KiB
		
	
	
	
		
			Python
		
	
	
		
			Executable File
		
	
	
	
	
			
		
		
	
	
			89 lines
		
	
	
		
			2.8 KiB
		
	
	
	
		
			Python
		
	
	
		
			Executable File
		
	
	
	
	
| #!/usr/bin/env python3
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| 
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| import numpy as np
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| import sys
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| import os
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| from pathlib import Path
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| 
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| def quick_logits_check(pytorch_file, llamacpp_file):
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|     """Lightweight sanity check before NMSE"""
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| 
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|     try:
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|         pytorch_logits = np.fromfile(pytorch_file, dtype=np.float32)
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|         llamacpp_logits = np.fromfile(llamacpp_file, dtype=np.float32)
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|     except Exception as e:
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|         print(f"❌ NOK: Failed to load files - {e}")
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|         return False
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| 
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|     # Check shapes match
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|     if pytorch_logits.shape != llamacpp_logits.shape:
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|         print(f"❌ NOK: Shape mismatch - PyTorch: {pytorch_logits.shape}, llama.cpp: {llamacpp_logits.shape}")
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|         return False
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| 
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|     # Calculate key metrics
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|     diff = pytorch_logits - llamacpp_logits
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|     abs_diff = np.abs(diff)
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|     max_diff = np.max(abs_diff)
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| 
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|     # Get top 10 predictions from both models
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|     pytorch_top10 = np.argsort(pytorch_logits)[-10:][::-1]
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|     llamacpp_top10 = np.argsort(llamacpp_logits)[-10:][::-1]
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|     print(f"Top 10 PyTorch logits: {pytorch_logits[pytorch_top10]}")
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|     print(f"Top 10 llama.cpp logits: {llamacpp_logits[llamacpp_top10]}")
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|     print(f"Max absolute difference: {max_diff:.4f}")
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| 
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|     if max_diff > 1.0:
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|         print(f"❌ NOK: Large differences detected - max diff: {max_diff:.4f}")
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|         return False
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| 
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|     return True
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| 
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| def main():
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|     model_path = os.getenv('MODEL_PATH')
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|     if not model_path:
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|         print("Error: MODEL_PATH environment variable not set")
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|         sys.exit(1)
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| 
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|     if not os.path.exists(model_path):
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|         print(f"Error: Model file not found: {model_path}")
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|         sys.exit(1)
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| 
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|     model_name = os.path.basename(model_path)
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|     data_dir = Path("data")
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| 
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|     pytorch_file = data_dir / f"pytorch-{model_name}.bin"
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|     llamacpp_file = data_dir / f"llamacpp-{model_name}.bin"
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| 
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|     if not pytorch_file.exists():
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|         print(f"Error: PyTorch logits file not found: {pytorch_file}")
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|         print("Please run scripts/run-org-model.sh first to generate this file.")
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|         sys.exit(1)
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| 
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|     if not llamacpp_file.exists():
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|         print(f"Error: llama.cpp logits file not found: {llamacpp_file}")
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|         print("Please run scripts/run-converted-model.sh first to generate this file.")
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|         sys.exit(1)
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| 
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|     print("Checked all required files were found. Proceeding...\n")
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| 
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| 
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|     print("🔍 GGML Model Validation for model ", model_name)
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|     print("=" * 40)
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|     print(f"PyTorch logits  : {pytorch_file}")
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|     print(f"llama.cpp logits: {llamacpp_file}")
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|     print()
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| 
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|     success = quick_logits_check(pytorch_file, llamacpp_file)
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| 
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|     # Exit with appropriate code
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|     if success:
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|         print("✅ OK: Lightweight model check successful!")
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|         print("       Ok to proceed with NMSE check...")
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|         sys.exit(0)
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|     else:
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|         print(f"❌ NOK: Top 10 predictions don't match - generation will differ")
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|         sys.exit(1)
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| 
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| if __name__ == "__main__":
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|     main()
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