Add data loader to read special weights for fp8; Add special weight process script

ktransformers/util/custom_loader.py

@@ -0,0 +1,86 @@
+import struct
+import warnings
+import numpy as np
+import re
+import numpy.typing as npt
+from typing import Sequence
+import os
+from enum import IntEnum
+import torch
+import KTransformersOps
+from safetensors import safe_open
+from ktransformers.ktransformers_ext.triton.fp8gemm import fp8_gemm, act_quant, weight_dequant
+from safetensors.torch import save_file
+
+class SafeTensorLoader:
+    tensor_file_map = {}
+    tensor_type_map = {}
+    file_handle_map = {}
+    
+    def __init__(self, file_path: str):
+        self.__load_tensor_file_map(file_path)
+
+    def __load_tensor_file_map(self, file_path: str):
+        # 处理传入路径，确保是文件夹路径
+        if not os.path.exists(file_path):
+            raise FileNotFoundError(f"Path not found: {file_path}")
+        if os.path.isfile(file_path):
+            folder_path = os.path.dirname(file_path)
+        else:
+            folder_path = file_path
+
+        found_safetensor = False
+        for root, _, files in os.walk(folder_path):
+            files = sorted(files)
+            for file in files:
+                if file.endswith(".safetensors"):
+                    found_safetensor = True
+                    file_path = os.path.join(root, file)
+                    if file not in self.file_handle_map:
+                        try:
+                            handle = safe_open(file_path, framework="pt")
+                            self.file_handle_map[file] = handle
+                        except Exception as e:
+                            print(f"Error opening Safetensor file {file_path}: {e}")
+                            continue
+
+                    f = self.file_handle_map.get(file)
+                    if f is None:
+                        continue
+                    try:
+                        for key in f.keys():
+                            self.tensor_file_map[key] = file
+                    except Exception as e:
+                        print(f"Error reading Safetensor file {file_path}: {e}")
+
+        # if not found_safetensor:
+        #     raise FileNotFoundError(f"No Safetensor files found in {folder_path}")
+
+    def load_tensor(self, key: str, device: str="cpu"):
+        if key not in self.tensor_file_map:
+            raise KeyError(f"Key {key} not found in Safetensor files")
+        file = self.tensor_file_map[key]
+        f = self.file_handle_map.get(file)
+        if f is None:
+            raise FileNotFoundError(f"File {file} not found in Safetensor files")
+        tensor = f.get_tensor(key)
+        return tensor.to(device)
+
+    def close_all_handles(self):
+        for handle in self.file_handle_map.values():
+            handle.close()
+        self.file_handle_map.clear()
+
+    def load_dequantized_tensor(self, key:str, device: str="cpu"):
+        if key not in self.tensor_file_map:
+            raise KeyError(f"Key {key} not found in Safetensor files")
+        file = self.tensor_file_map[key]
+        f = self.file_handle_map.get(file)
+        if f is None:
+            raise FileNotFoundError(f"File {file} not found in Safetensor files")
+        tensor = f.get_tensor(key).to(device)
+        if key.endswith(".weight"):
+            if key[:-7] + ".weight_scale_inv" in self.tensor_file_map:
+                weight_scale_inv = f.get_tensor(key[:-7] + ".weight_scale_inv").to(device)
+                tensor = weight_dequant(tensor, weight_scale_inv)
+        return tensor.to(device)