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https://github.com/deepseek-ai/DeepSeek-V3.git
synced 2025-02-22 21:58:58 -05:00
55 lines
2.1 KiB
Python
55 lines
2.1 KiB
Python
import os
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import json
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from argparse import ArgumentParser
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from glob import glob
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from tqdm import tqdm
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import torch
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from safetensors.torch import load_file, save_file
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from kernel import weight_dequant
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def main(fp8_path, bf16_path):
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torch.set_default_dtype(torch.bfloat16)
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os.makedirs(bf16_path, exist_ok=True)
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model_index_file = os.path.join(fp8_path, "model.safetensors.index.json")
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with open(model_index_file, "r") as f:
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model_index = json.load(f)
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weight_map = model_index["weight_map"]
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fp8_weight_names = []
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safetensor_files = list(glob(os.path.join(fp8_path, "*.safetensors")))
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for safetensor_file in tqdm(safetensor_files):
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file_name = os.path.basename(safetensor_file)
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state_dict = load_file(safetensor_file, device="cuda")
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new_state_dict = {}
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for weight_name, weight in state_dict.items():
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if weight_name.endswith("_scale_inv"):
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continue
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elif weight.element_size() == 1:
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scale_inv_name = f"{weight_name}_scale_inv"
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assert scale_inv_name in state_dict
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fp8_weight_names.append(weight_name)
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scale_inv = state_dict[scale_inv_name]
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new_state_dict[weight_name] = weight_dequant(weight, scale_inv)
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else:
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new_state_dict[weight_name] = weight
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new_safetensor_file = os.path.join(bf16_path, file_name)
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save_file(new_state_dict, new_safetensor_file)
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new_model_index_file = os.path.join(bf16_path, "model.safetensors.index.json")
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for weight_name in fp8_weight_names:
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scale_inv_name = f"{weight_name}_scale_inv"
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assert scale_inv_name in weight_map
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weight_map.pop(scale_inv_name)
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with open(new_model_index_file, "w") as f:
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json.dump({"metadata": {}, "weight_map": weight_map}, f, indent=2)
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if __name__ == "__main__":
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parser = ArgumentParser()
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parser.add_argument("--input-fp8-hf-path", type=str, required=True)
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parser.add_argument("--output-bf16-hf-path", type=str, required=True)
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args = parser.parse_args()
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main(args.input_fp8_hf_path, args.output_bf16_hf_path)
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