d7ca5d935b
* Upgrade Peft version to 0.10.0 * Upgrade Peft version in ARC unit test and HF-Peft example.
85 lines
3.2 KiB
Python
85 lines
3.2 KiB
Python
#
|
|
# Copyright 2016 The BigDL Authors.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
#
|
|
|
|
import transformers
|
|
import importlib
|
|
import sys
|
|
from packaging import version
|
|
|
|
from ipex_llm.utils.common import invalidInputError
|
|
from enum import Enum
|
|
|
|
bigdl_patched = None # None or 'Train' or 'Inference'
|
|
attrs = []
|
|
|
|
|
|
def replace_attr(obj, name: str, value):
|
|
original_attr = getattr(obj, name)
|
|
setattr(obj, name, value)
|
|
attrs.append((obj, name, original_attr))
|
|
|
|
|
|
def llm_patch(train=False):
|
|
'''
|
|
llm_patch is used to make users' LLM application benefit from BigDL-LLM optimization
|
|
with only one-line code patch.
|
|
|
|
:param train: Whether to apply bigdl-llm patch for training code, default to be `False`.
|
|
'''
|
|
global bigdl_patched
|
|
if bigdl_patched:
|
|
return
|
|
|
|
# Initial version of patch for llm finetuning, inference support TBD
|
|
if train:
|
|
from ipex_llm.transformers import AutoModelForCausalLM, AutoModel
|
|
replace_attr(transformers, "AutoModelForCausalLM", AutoModelForCausalLM)
|
|
replace_attr(transformers, "LlamaForCausalLM", AutoModelForCausalLM)
|
|
replace_attr(transformers, "AutoModel", AutoModel)
|
|
from ipex_llm.transformers.utils import is_torch_bf16_gpu_available
|
|
replace_attr(transformers.utils, "is_torch_bf16_gpu_available", is_torch_bf16_gpu_available)
|
|
|
|
import_peft_check = 'peft' in sys.modules or 'peft.utils' in sys.modules or \
|
|
'peft.tuners' in sys.modules or 'peft.mapping' in sys.modules
|
|
invalidInputError(not import_peft_check,
|
|
'llm_patch() should be called at the beginning of your code.')
|
|
import peft
|
|
from ipex_llm.transformers.qlora import get_peft_model, prepare_model_for_kbit_training,\
|
|
LoraConfig, TrainingArguments
|
|
peft_version = peft.__version__
|
|
replace_attr(transformers, "TrainingArguments", TrainingArguments)
|
|
get_peft_model_original = getattr(peft, "get_peft_model")
|
|
replace_attr(peft, "get_peft_model", get_peft_model)
|
|
setattr(peft, "get_peft_model_original", get_peft_model_original)
|
|
replace_attr(peft, "prepare_model_for_kbit_training", prepare_model_for_kbit_training)
|
|
if version.parse(peft_version) <= version.parse("0.5.0"):
|
|
replace_attr(peft, "prepare_model_for_int8_training", prepare_model_for_kbit_training)
|
|
replace_attr(peft, "LoraConfig", LoraConfig)
|
|
bigdl_patched = 'Train'
|
|
|
|
|
|
def llm_unpatch():
|
|
'''
|
|
llm_unpatch is an reverse function to llm_patch.
|
|
'''
|
|
global bigdl_patched
|
|
|
|
if bigdl_patched is None:
|
|
return
|
|
|
|
for obj, name, torch_attr in attrs:
|
|
setattr(obj, name, torch_attr)
|
|
bigdl_patched = None
|