



from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_   :List[Any]        =      logging.get_logger(__name__)

a_   :Optional[int]        =      {
    """SCUT-DLVCLab/lilt-roberta-en-base""": (
        """https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"""
    ),
}




class 					snake_case__						(       __UpperCamelCase     ):






     """simple docstring"""


     _SCREAMING_SNAKE_CASE						=	"""lilt"""






     def __init__(       self  :  Dict, _snake_case  :  int=3_0_5_2_2, _snake_case  :  Tuple=7_6_8, _snake_case  :  Optional[int]=1_2, _snake_case  :  List[str]=1_2, _snake_case  :  Union[str, Any]=3_0_7_2, _snake_case  :  Tuple="gelu", _snake_case  :  Optional[int]=0.1, _snake_case  :  List[str]=0.1, _snake_case  :  Any=5_1_2, _snake_case  :  List[str]=2, _snake_case  :  str=0.0_2, _snake_case  :  List[Any]=1e-12, _snake_case  :  List[str]=0, _snake_case  :  Union[str, Any]="absolute", _snake_case  :  str=None, _snake_case  :  Optional[Any]=4, _snake_case  :  Union[str, Any]=1_0_2_4, **_snake_case  :  str, )   ->Dict:
            super().__init__(pad_token_id=_snake_case, **_snake_case					)

            snake_case__							:	Union[str, Any]   	=	vocab_size
            snake_case__							:	Dict   	=	hidden_size
            snake_case__							:	Tuple   	=	num_hidden_layers
            snake_case__							:	Optional[Any]   	=	num_attention_heads
            snake_case__							:	Tuple   	=	hidden_act
            snake_case__							:	Union[str, Any]   	=	intermediate_size
            snake_case__							:	List[Any]   	=	hidden_dropout_prob
            snake_case__							:	Union[str, Any]   	=	attention_probs_dropout_prob
            snake_case__							:	Optional[int]   	=	max_position_embeddings
            snake_case__							:	Tuple   	=	type_vocab_size
            snake_case__							:	Dict   	=	initializer_range
            snake_case__							:	Union[str, Any]   	=	layer_norm_eps
            snake_case__							:	Any   	=	position_embedding_type
            snake_case__							:	List[str]   	=	classifier_dropout
            snake_case__							:	int   	=	channel_shrink_ratio
            snake_case__							:	int   	=	max_ad_position_embeddings













# 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      (       _UpperCAmelCase=None )			->     Tuple:
    if subparsers is not None:
        lowerCamelCase__    :      Any					 =		subparsers.add_parser('test' )
    else:
        lowerCamelCase__    :      int					 =		argparse.ArgumentParser('Accelerate test command' )

    parser.add_argument(
        '--config_file'						,	default=_UpperCAmelCase						,	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=_UpperCAmelCase )
    return parser


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase )			->     Union[str, Any]:
    lowerCamelCase__    :      Tuple					 =		os.path.sep.join(__file__.split(os.path.sep )[:-2] + ['test_utils', 'scripts', 'test_script.py'] )

    if args.config_file is None:
        lowerCamelCase__    :      List[str]					 =		script_name
    else:
        lowerCamelCase__    :      List[Any]					 =		F"""--config_file={args.config_file} {script_name}"""

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


def        SCREAMING_SNAKE_CASE      (       )			->     Any:
    lowerCamelCase__    :      Any					 =		test_command_parser()
    lowerCamelCase__    :      List[Any]					 =		parser.parse_args()
    test_command(_UpperCAmelCase )


if __name__ == "__main__":
    main()





