9df70d95eb
* Rename bigdl/llm to ipex_llm * rm python/llm/src/bigdl * from bigdl.llm to from ipex_llm
79 lines
2.8 KiB
Python
79 lines
2.8 KiB
Python
#
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# Copyright 2016 The BigDL Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import transformers
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import importlib
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import sys
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from ipex_llm.utils.common import invalidInputError
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from enum import Enum
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bigdl_patched = None # None or 'Train' or 'Inference'
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attrs = []
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def replace_attr(obj, name: str, value):
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original_attr = getattr(obj, name)
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setattr(obj, name, value)
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attrs.append((obj, name, original_attr))
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def llm_patch(train=False):
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'''
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llm_patch is used to make users' LLM application benefit from BigDL-LLM optimization
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with only one-line code patch.
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:param train: Whether to apply bigdl-llm patch for training code, default to be `False`.
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'''
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global bigdl_patched
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if bigdl_patched:
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return
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# Initial version of patch for llm finetuning, inference support TBD
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if train:
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from ipex_llm.transformers import AutoModelForCausalLM, AutoModel
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replace_attr(transformers, "AutoModelForCausalLM", AutoModelForCausalLM)
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replace_attr(transformers, "LlamaForCausalLM", AutoModelForCausalLM)
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replace_attr(transformers, "AutoModel", AutoModel)
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import_peft_check = 'peft' in sys.modules or 'peft.utils' in sys.modules or \
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'peft.tuners' in sys.modules or 'peft.mapping' in sys.modules
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invalidInputError(not import_peft_check,
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'llm_patch() should be called at the beginning of your code.')
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import peft
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from ipex_llm.transformers.qlora import get_peft_model, prepare_model_for_kbit_training,\
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LoraConfig, TrainingArguments
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replace_attr(transformers, "TrainingArguments", TrainingArguments)
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get_peft_model_original = getattr(peft, "get_peft_model")
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replace_attr(peft, "get_peft_model", get_peft_model)
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setattr(peft, "get_peft_model_original", get_peft_model_original)
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replace_attr(peft, "prepare_model_for_kbit_training", prepare_model_for_kbit_training)
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replace_attr(peft, "prepare_model_for_int8_training", prepare_model_for_kbit_training)
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replace_attr(peft, "LoraConfig", LoraConfig)
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bigdl_patched = 'Train'
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def llm_unpatch():
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'''
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llm_unpatch is an reverse function to llm_patch.
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'''
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global bigdl_patched
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if bigdl_patched is None:
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return
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for obj, name, torch_attr in attrs:
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setattr(obj, name, torch_attr)
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bigdl_patched = None
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