| |
| import os |
| from dataclasses import dataclass |
| from typing import Optional |
|
|
| from swift.utils import HfConfigFactory, get_logger, to_abspath |
| from .megatron_args import MegatronArguments |
| from .megatron_base_args import MegatronBaseArguments |
|
|
| logger = get_logger() |
|
|
|
|
| @dataclass |
| class MegatronExportArguments(MegatronBaseArguments): |
| to_mcore: bool = False |
| to_hf: bool = False |
| test_convert_precision: bool = False |
| test_convert_dtype: str = 'float32' |
| exist_ok: bool = False |
| merge_lora: Optional[bool] = None |
|
|
| def _init_output_dir(self): |
| if self.output_dir is None: |
| ckpt_dir = self.ckpt_dir or f'./{self.model_suffix}' |
| ckpt_dir, ckpt_name = os.path.split(ckpt_dir) |
| if self.to_mcore: |
| suffix = 'mcore' |
| elif self.to_hf: |
| suffix = 'hf' |
| self.output_dir = os.path.join(ckpt_dir, f'{ckpt_name}-{suffix}') |
|
|
| self.output_dir = to_abspath(self.output_dir) |
| if not self.exist_ok and os.path.exists(self.output_dir): |
| raise FileExistsError(f'args.output_dir: `{self.output_dir}` already exists.') |
| logger.info(f'args.output_dir: `{self.output_dir}`') |
|
|
| def _init_megatron_args(self): |
| self._init_output_dir() |
| self.test_convert_dtype = HfConfigFactory.to_torch_dtype(self.test_convert_dtype) |
| extra_config = MegatronArguments.load_args_config(self.ckpt_dir) |
| extra_config['mcore_adapter'] = self.mcore_adapter |
| if self.mcore_model: |
| extra_config['mcore_model'] = self.mcore_model |
| for k, v in extra_config.items(): |
| setattr(self, k, v) |
| if self.to_hf or self.to_mcore: |
| self._init_convert() |
| if self.model_info.is_moe_model is not None and self.tensor_model_parallel_size > 1: |
| self.sequence_parallel = True |
| logger.info('Settting args.sequence_parallel: True') |
| if self.merge_lora is None: |
| self.merge_lora = self.to_hf |
| super()._init_megatron_args() |
|
|
| def _init_convert(self): |
| convert_kwargs = { |
| 'no_save_optim': True, |
| 'no_save_rng': True, |
| 'no_load_optim': True, |
| 'no_load_rng': True, |
| 'finetune': True, |
| 'attention_backend': 'unfused', |
| 'padding_free': False, |
| } |
| for k, v in convert_kwargs.items(): |
| setattr(self, k, v) |
| if self.model_info.is_moe_model: |
| self.moe_grouped_gemm = True |
|
|
