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- # coding=utf-8
- # Copyright 2024 Microsoft Corporation and the LlamaFactory team.
- #
- # This code is inspired by the Microsoft's DeepSpeed library.
- # https://www.deepspeed.ai/tutorials/flops-profiler/
- #
- # 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 fire
- import torch
- from deepspeed.accelerator import get_accelerator # type: ignore
- from deepspeed.profiling.flops_profiler import get_model_profile # type: ignore
- from llamafactory.chat import ChatModel
- def calculate_flops(
- model_name_or_path: str,
- batch_size: int = 1,
- seq_length: int = 512,
- flash_attn: str = "auto",
- ):
- r"""
- Calculates the flops of pre-trained models.
- Usage: python cal_flops.py --model_name_or_path path_to_model --batch_size 1 --seq_length 512
- """
- with get_accelerator().device(0):
- chat_model = ChatModel(dict(model_name_or_path=model_name_or_path, template="empty", flash_attn=flash_attn))
- fake_input = torch.ones((batch_size, seq_length), dtype=torch.long, device=chat_model.engine.model.device)
- input_dict = {"input_ids": fake_input, "labels": fake_input.clone()}
- flops, macs, params = get_model_profile(
- chat_model.engine.model, kwargs=input_dict, print_profile=True, detailed=True
- )
- print("FLOPs:", flops)
- print("MACs:", macs)
- print("Params:", params)
- if __name__ == "__main__":
- fire.Fire(calculate_flops)
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