File size: 1,268 Bytes
c31821c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | import os
from typing import List
import numpy as np
import torch
from safetensors.torch import load_file
import onnx
from onnx import numpy_helper
def merge_loras(loras: List[str], scales: List[str]) -> dict:
refit_dict = {}
for lora, scale in zip(loras, scales):
lora_dict = load_file(lora)
for k, v in lora_dict.items():
if k in refit_dict:
refit_dict[k] += scale * v
else:
refit_dict[k] = scale * v
return refit_dict
def apply_loras(base_path: str, loras: List[str], scales: List[str]) -> dict:
refit_dict = merge_loras(loras, scales)
base = onnx.load(base_path)
onnx_opt_dir = os.path.dirname(base_path)
def convert_int64(arr):
if len(arr.shape) == 0:
return np.array([np.int32(arr)])
return arr
for initializer in base.graph.initializer:
if initializer.name not in refit_dict:
continue
wt = refit_dict[initializer.name]
initializer_data = numpy_helper.to_array(
initializer, base_dir=onnx_opt_dir
).astype(np.float16)
delta = torch.tensor(initializer_data).to(wt.device) + wt
refit_dict[initializer.name] = delta.contiguous()
return refit_dict
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