82 lines
3.3 KiB
Python
82 lines
3.3 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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# this code is to support converting of model in load bit
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# for performance tests using load_low_bit
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import time
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import torch
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import os
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import argparse
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from ipex_llm.transformers.npu_model import AutoModelForCausalLM
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from transformers import AutoTokenizer
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from run import get_model_path
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current_dir = os.path.dirname(os.path.realpath(__file__))
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def save_npu_model_in_low_bit(repo_id,
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local_model_hub,
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low_bit,
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max_output_len, max_prompt_len, intra_pp, inter_pp, disable_transpose_value_cache):
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model_path = get_model_path(repo_id, local_model_hub)
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# Load model in 4 bit,
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# which convert the relevant layers in the model into INT4 format
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st = time.perf_counter()
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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torch_dtype=torch.float16,
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trust_remote_code=True,
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attn_implementation="eager",
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load_in_low_bit="sym_int4",
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optimize_model=True,
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max_output_len=max_output_len,
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max_prompt_len=max_prompt_len,
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intra_pp=intra_pp,
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inter_pp=inter_pp,
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transpose_value_cache=not disable_transpose_value_cache,
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)
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tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
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end = time.perf_counter()
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print(">> loading of and converting of model costs {}s".format(end - st))
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model.save_low_bit(model_path+'-npu-'+low_bit)
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tokenizer.save_pretrained(model_path+'-npu-'+low_bit)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Predict Tokens using `generate()` API for npu model"
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)
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parser.add_argument("--max-output-len", type=int, default=1024)
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parser.add_argument("--max-prompt-len", type=int, default=512)
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parser.add_argument("--disable-transpose-value-cache", action="store_true", default=False)
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parser.add_argument("--intra-pp", type=int, default=2)
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parser.add_argument("--inter-pp", type=int, default=2)
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args = parser.parse_args()
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from omegaconf import OmegaConf
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conf = OmegaConf.load(f'{current_dir}/config.yaml')
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for model in conf.repo_id:
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save_npu_model_in_low_bit(repo_id=model,
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local_model_hub=conf['local_model_hub'],
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low_bit=conf['low_bit'],
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max_output_len=args.max_output_len,
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max_prompt_len=args.max_prompt_len,
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intra_pp=args.intra_pp,
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inter_pp=args.inter_pp,
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disable_transpose_value_cache=args.disable_transpose_value_cache
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)
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