


'''simple docstring'''
import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


__snake_case											=					['''small''', '''medium''', '''large''']

__snake_case											=					'''lm_head.decoder.weight'''
__snake_case											=					'''lm_head.weight'''


def       a				(      __a			, __a       )  ->     Optional[int]:



					'''simple docstring'''






					UpperCamelCase__       :str							 =			torch.load(__a       )
					UpperCamelCase__       :str							 =			d.pop(__a       )
					os.makedirs(__a			, exist_ok=__a       )
					torch.save(__a			, os.path.join(__a			, __a       )       )


if __name__ == "__main__":
		__snake_case											=					argparse.ArgumentParser()
		parser.add_argument('''--dialogpt_path''', default='''.''', type=str)
		__snake_case											=					parser.parse_args()
		for MODEL in DIALOGPT_MODELS:
				__snake_case											=					os.path.join(args.dialogpt_path, F"""{MODEL}_ft.pkl""")
				__snake_case											=					F"""./DialoGPT-{MODEL}"""
				convert_dialogpt_checkpoint(
				    checkpoint_path,
				    pytorch_dump_folder_path,
				)



'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case											=					{'''configuration_vit_msn''': ['''VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMSNConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case											=					[
		    '''VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ViTMSNModel''',
		    '''ViTMSNForImageClassification''',
		    '''ViTMSNPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_vit_msn import VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMSNConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_vit_msn import (
				    VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ViTMSNForImageClassification,
				    ViTMSNModel,
				    ViTMSNPreTrainedModel,
				)

else:
		import sys

		__snake_case											=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)