






'''simple docstring'''

import logging

from transformers.configuration_utils import PretrainedConfig


UpperCamelCase      					=logging.getLogger(__name__)




class      A     (   __lowercase    ):






 """simple docstring"""





 __a      :    int			  =    '''masked_bert'''
 def __init__(				self      ,  __lowerCAmelCase=3_05_22      ,  __lowerCAmelCase=7_68      ,  __lowerCAmelCase=12      ,  __lowerCAmelCase=12      ,  __lowerCAmelCase=30_72      ,  __lowerCAmelCase="gelu"      ,  __lowerCAmelCase=0.1      ,  __lowerCAmelCase=0.1      ,  __lowerCAmelCase=5_12      ,  __lowerCAmelCase=2      ,  __lowerCAmelCase=0.02      ,  __lowerCAmelCase=1E-12      ,  __lowerCAmelCase=0      ,  __lowerCAmelCase="topK"      ,  __lowerCAmelCase="constant"      ,  __lowerCAmelCase=0.0      ,  **__lowerCAmelCase      ,  ):
       super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_      ,  **SCREAMING_SNAKE_CASE_			)

       UpperCamelCase_					: Optional[int]            =				vocab_size
       UpperCamelCase_					: Optional[Any]            =				hidden_size
       UpperCamelCase_					: int            =				num_hidden_layers
       UpperCamelCase_					: List[Any]            =				num_attention_heads
       UpperCamelCase_					: Optional[Any]            =				hidden_act
       UpperCamelCase_					: Dict            =				intermediate_size
       UpperCamelCase_					: List[Any]            =				hidden_dropout_prob
       UpperCamelCase_					: List[Any]            =				attention_probs_dropout_prob
       UpperCamelCase_					: List[str]            =				max_position_embeddings
       UpperCamelCase_					: List[Any]            =				type_vocab_size
       UpperCamelCase_					: Optional[int]            =				initializer_range
       UpperCamelCase_					: List[str]            =				layer_norm_eps
       UpperCamelCase_					: Optional[Any]            =				pruning_method
       UpperCamelCase_					: List[str]            =				mask_init
       UpperCamelCase_					: str            =				mask_scale








"""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 							_lowerCamelCase			(			__a=None     ):
		if subparsers is not None:
				SCREAMING_SNAKE_CASE_    			=			subparsers.add_parser('''test'''     )
		else:
				SCREAMING_SNAKE_CASE_    			=			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 							_lowerCamelCase			(			__a     ):
		SCREAMING_SNAKE_CASE_    			=			os.path.sep.join(__file__.split(os.path.sep     )[:-2] + ['''test_utils''', '''scripts''', '''test_script.py''']     )

		if args.config_file is None:
				SCREAMING_SNAKE_CASE_    			=			script_name
		else:
				SCREAMING_SNAKE_CASE_    			=			F'--config_file={args.config_file} {script_name}'

		SCREAMING_SNAKE_CASE_    			=			['''accelerate-launch'''] + test_args.split()
		SCREAMING_SNAKE_CASE_    			=			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 							_lowerCamelCase			(			):
		SCREAMING_SNAKE_CASE_    			=			test_command_parser()
		SCREAMING_SNAKE_CASE_    			=			parser.parse_args()
		test_command(__a     )


if __name__ == "__main__":
						main()