mirror of
https://github.com/kvcache-ai/ktransformers.git
synced 2025-09-05 20:19:51 +00:00
86 lines
No EOL
3.3 KiB
Python
86 lines
No EOL
3.3 KiB
Python
import struct
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import warnings
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import numpy as np
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import re
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import numpy.typing as npt
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from typing import Sequence
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import os
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from enum import IntEnum
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import torch
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import KTransformersOps
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from safetensors import safe_open
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from ktransformers.ktransformers_ext.triton.fp8gemm import fp8_gemm, act_quant, weight_dequant
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from safetensors.torch import save_file
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class SafeTensorLoader:
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tensor_file_map = {}
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tensor_type_map = {}
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file_handle_map = {}
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def __init__(self, file_path: str):
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self.__load_tensor_file_map(file_path)
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def __load_tensor_file_map(self, file_path: str):
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# 处理传入路径，确保是文件夹路径
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if not os.path.exists(file_path):
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raise FileNotFoundError(f"Path not found: {file_path}")
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if os.path.isfile(file_path):
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folder_path = os.path.dirname(file_path)
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else:
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folder_path = file_path
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found_safetensor = False
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for root, _, files in os.walk(folder_path):
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files = sorted(files)
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for file in files:
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if file.endswith(".safetensors"):
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found_safetensor = True
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file_path = os.path.join(root, file)
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if file not in self.file_handle_map:
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try:
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handle = safe_open(file_path, framework="pt")
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self.file_handle_map[file] = handle
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except Exception as e:
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print(f"Error opening Safetensor file {file_path}: {e}")
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continue
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f = self.file_handle_map.get(file)
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if f is None:
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continue
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try:
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for key in f.keys():
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self.tensor_file_map[key] = file
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except Exception as e:
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print(f"Error reading Safetensor file {file_path}: {e}")
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# if not found_safetensor:
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# raise FileNotFoundError(f"No Safetensor files found in {folder_path}")
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def load_tensor(self, key: str, device: str="cpu"):
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if key not in self.tensor_file_map:
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raise KeyError(f"Key {key} not found in Safetensor files")
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file = self.tensor_file_map[key]
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f = self.file_handle_map.get(file)
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if f is None:
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raise FileNotFoundError(f"File {file} not found in Safetensor files")
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tensor = f.get_tensor(key)
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return tensor.to(device)
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def close_all_handles(self):
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for handle in self.file_handle_map.values():
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handle.close()
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self.file_handle_map.clear()
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def load_dequantized_tensor(self, key:str, device: str="cpu"):
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if key not in self.tensor_file_map:
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raise KeyError(f"Key {key} not found in Safetensor files")
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file = self.tensor_file_map[key]
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f = self.file_handle_map.get(file)
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if f is None:
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raise FileNotFoundError(f"File {file} not found in Safetensor files")
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tensor = f.get_tensor(key).to(device)
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if key.endswith(".weight"):
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if key[:-7] + ".weight_scale_inv" in self.tensor_file_map:
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weight_scale_inv = f.get_tensor(key[:-7] + ".weight_scale_inv").to(device)
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tensor = weight_dequant(tensor, weight_scale_inv)
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return tensor.to(device) |