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67
examples/model-conversion/scripts/utils/inspect-org-model.py
Executable file
67
examples/model-conversion/scripts/utils/inspect-org-model.py
Executable file
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#!/usr/bin/env python3
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import argparse
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import os
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import json
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from safetensors import safe_open
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from collections import defaultdict
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parser = argparse.ArgumentParser(description='Process model with specified path')
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parser.add_argument('--model-path', '-m', help='Path to the model')
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args = parser.parse_args()
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model_path = os.environ.get('MODEL_PATH', args.model_path)
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if model_path is None:
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parser.error("Model path must be specified either via --model-path argument or MODEL_PATH environment variable")
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# Check if there's an index file (multi-file model)
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index_path = os.path.join(model_path, "model.safetensors.index.json")
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single_file_path = os.path.join(model_path, "model.safetensors")
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if os.path.exists(index_path):
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# Multi-file model
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print("Multi-file model detected")
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with open(index_path, 'r') as f:
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index_data = json.load(f)
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# Get the weight map (tensor_name -> file_name)
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weight_map = index_data.get("weight_map", {})
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# Group tensors by file for efficient processing
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file_tensors = defaultdict(list)
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for tensor_name, file_name in weight_map.items():
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file_tensors[file_name].append(tensor_name)
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print("Tensors in model:")
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# Process each shard file
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for file_name, tensor_names in file_tensors.items():
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file_path = os.path.join(model_path, file_name)
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print(f"\n--- From {file_name} ---")
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with safe_open(file_path, framework="pt") as f:
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for tensor_name in sorted(tensor_names):
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tensor = f.get_tensor(tensor_name)
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print(f"- {tensor_name} : shape = {tensor.shape}, dtype = {tensor.dtype}")
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elif os.path.exists(single_file_path):
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# Single file model (original behavior)
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print("Single-file model detected")
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with safe_open(single_file_path, framework="pt") as f:
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keys = f.keys()
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print("Tensors in model:")
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for key in sorted(keys):
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tensor = f.get_tensor(key)
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print(f"- {key} : shape = {tensor.shape}, dtype = {tensor.dtype}")
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else:
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print(f"Error: Neither 'model.safetensors.index.json' nor 'model.safetensors' found in {model_path}")
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print("Available files:")
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if os.path.exists(model_path):
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for item in sorted(os.listdir(model_path)):
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print(f" {item}")
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else:
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print(f" Directory {model_path} does not exist")
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exit(1)
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