"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__       =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__       =	{
    "bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/config.json",
    # QDQBERT models can be loaded from any BERT checkpoint, available at https://huggingface.co/models?filter=bert
}



class 	lowerCAmelCase_     (      lowerCAmelCase       ):



				"""simple docstring"""
				_lowerCAmelCase  :     Union[str, Any]      	=    """qdqbert"""

				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=True		,     lowerCAmelCase=1		,     lowerCAmelCase=0		,     lowerCAmelCase=2		,     **lowerCAmelCase		,     ):






										"""simple docstring"""

										super().__init__(pad_token_id=lowerCAmelCase		,     bos_token_id=lowerCAmelCase		,     eos_token_id=lowerCAmelCase		,     **lowerCAmelCase     )

										snake_case             =      vocab_size
										snake_case             =      max_position_embeddings
										snake_case             =      hidden_size
										snake_case             =      num_hidden_layers
										snake_case             =      num_attention_heads
										snake_case             =      intermediate_size
										snake_case             =      hidden_act
										snake_case             =      hidden_dropout_prob
										snake_case             =      attention_probs_dropout_prob
										snake_case             =      initializer_range
										snake_case             =      type_vocab_size
										snake_case             =      layer_norm_eps
										snake_case             =      use_cache



"""simple docstring"""
import os
from string import ascii_letters

SCREAMING_SNAKE_CASE__       =	ascii_letters + " \t\n"





def  lowerCAmelCase__     (      )       ->					dict[str, None]:





						"""simple docstring"""






						snake_case             =      os.path.split(os.path.realpath(_UpperCamelCase       )       )
						snake_case             =      {}
						with open(path[0] + '/dictionary.txt'       ) as dictionary_file:
												for word in dictionary_file.read().split('\n'       ):
																		snake_case             =      None
						return english_words


SCREAMING_SNAKE_CASE__       =	load_dictionary()





def  lowerCAmelCase__     (      _UpperCamelCase							:					str       )       ->					float:





						"""simple docstring"""






						snake_case             =      message.upper()
						snake_case             =      remove_non_letters(_UpperCamelCase       )
						snake_case             =      message.split()
						snake_case             =      len([word for word in possible_words if word in ENGLISH_WORDS]       )
						return float(_UpperCamelCase       ) / len(_UpperCamelCase       )





def  lowerCAmelCase__     (      _UpperCamelCase							:					str       )       ->					str:





						"""simple docstring"""






						return "".join(symbol for symbol in message if symbol in LETTERS_AND_SPACE       )





def  lowerCAmelCase__     (      _UpperCamelCase							:					str			,      _UpperCamelCase							:					int = 2_0			,      _UpperCamelCase							:					int = 8_5       )       ->					bool:





						"""simple docstring"""






						snake_case             =      get_english_count(_UpperCamelCase       ) * 1_0_0 >= word_percentage
						snake_case             =      len(remove_non_letters(_UpperCamelCase       )       )
						snake_case             =      (float(_UpperCamelCase       ) / len(_UpperCamelCase       )) * 1_0_0
						snake_case             =      message_letters_percentage >= letter_percentage
						return words_match and letters_match


if __name__ == "__main__":
					import doctest

					doctest.testmod()


