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LLM: avoid unnecessary import torch except converting process (#8297)

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binbin Deng 2023-06-08 14:24:58 +08:00 committed by GitHub
parent f9e2bda04a
commit 08bdfce2d8
1 changed files with 4 additions and 2 deletions
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6
python/llm/src/bigdl/llm/utils/convert_util.py
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@ -64,9 +64,7 @@ from pathlib import Path
from typing import (IO, TYPE_CHECKING, Any, Callable, Dict, Iterable, List,
Literal, Optional, Sequence, Tuple, TypeVar, Union)
import numpy as np
import torch
from sentencepiece import SentencePieceProcessor
from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig
from bigdl.llm.utils.common import invalidInputError
if TYPE_CHECKING:
@ -1238,6 +1236,8 @@ def bytes_to_unicode():
def _convert_gptneox_hf_to_ggml(model_path, outfile_dir, outtype):
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path,
torch_dtype=torch.float16
@ -1317,6 +1317,8 @@ def _convert_gptneox_hf_to_ggml(model_path, outfile_dir, outtype):
def _convert_bloom_hf_to_ggml(model_path, outfile_dir, outtype):
from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig
import torch
conv_map = {'word_embeddings': 'tok_embeddings',
'word_embeddings_layernorm': 'norm',
'input_layernorm': 'attention_norm',