




import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


lowercase__				:     Optional[int] 		=						['''small''', '''medium''', '''large''']

lowercase__				:     List[Any] 		=						'''lm_head.decoder.weight'''
lowercase__				:     Tuple 		=						'''lm_head.weight'''


def 						lowerCamelCase__    (		_A     ,	_A							):







	'''simple docstring'''





	snake_case_		    =     torch.load(A_							)
	snake_case_		    =     d.pop(A_							)
	os.makedirs(A_     ,	exist_ok=A_							)
	torch.save(A_     ,	os.path.join(A_     ,	A_							)							)


if __name__ == "__main__":
		lowercase__				:     List[str] 		=						argparse.ArgumentParser()
		parser.add_argument("--dialogpt_path", default=".", type=str)
		lowercase__				:     Union[str, Any] 		=						parser.parse_args()
		for MODEL in DIALOGPT_MODELS:
				lowercase__				:     Optional[int] 		=						os.path.join(args.dialogpt_path, f'''{MODEL}_ft.pkl''')
				lowercase__				:     Any 		=						f'''./DialoGPT-{MODEL}'''
				convert_dialogpt_checkpoint(
				    checkpoint_path,
				    pytorch_dump_folder_path,
				)



"""simple docstring"""





# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# 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 argparse
import os

from accelerate.test_utils import execute_subprocess_async

def   __SCREAMING_SNAKE_CASE  (      A_=None ):
	if subparsers is not None:
		lowerCAmelCase__	:						Optional[Any]  				=	subparsers.add_parser('''test''' )
	else:
		lowerCAmelCase__	:						List[str]  				=	argparse.ArgumentParser('''Accelerate test command''' )

	parser.add_argument(
	    '''--config_file'''						,     default=A_						,     help=(
	        '''The path to use to store the config file. Will default to a file named default_config.yaml in the cache '''
	        '''location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '''
	        '''such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '''
	        '''with \'huggingface\'.'''
	    )						,     )

	if subparsers is not None:
		parser.set_defaults(func=A_ )
	return parser

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	lowerCAmelCase__	:						Optional[int]  				=	os.path.sep.join(__file__.split(os.path.sep )[:-2] + ['''test_utils''', '''scripts''', '''test_script.py'''] )

	if args.config_file is None:
		lowerCAmelCase__	:						Optional[Any]  				=	script_name
	else:
		lowerCAmelCase__	:						Any  				=	f'--config_file={args.config_file} {script_name}'

	lowerCAmelCase__	:						List[Any]  				=	['''accelerate-launch'''] + test_args.split()
	lowerCAmelCase__	:						int  				=	execute_subprocess_async(A_						,     env=os.environ.copy() )
	if result.returncode == 0:
		print('''Test is a success! You are ready for your distributed training!''' )

def   __SCREAMING_SNAKE_CASE  (      ):
	lowerCAmelCase__	:						Any  				=	test_command_parser()
	lowerCAmelCase__	:						List[Any]  				=	parser.parse_args()
	test_command(A_ )


if __name__ == "__main__":
							main()




