




import os
from string import ascii_letters

__A						:		int          =						ascii_letters + " \t\n"





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







				'''simple docstring'''


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


__A						:		Union[str, Any]          =						load_dictionary()





def      UpperCAmelCase  (						UpperCamelCase__   )     ->     float:







				'''simple docstring'''


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





def      UpperCAmelCase  (						UpperCamelCase__   )     ->     str:







				'''simple docstring'''


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





def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__ = 20						,			UpperCamelCase__ = 85   )     ->     bool:







				'''simple docstring'''


				__lowerCAmelCase					=  get_english_count(UpperCamelCase__   ) * 1_00 >= word_percentage
				__lowerCAmelCase					=  len(remove_non_letters(UpperCamelCase__   )   )
				__lowerCAmelCase					=  (float(UpperCamelCase__   ) / len(UpperCamelCase__   )) * 1_00
				__lowerCAmelCase					=  message_letters_percentage >= letter_percentage
				return words_match and letters_match


if __name__ == "__main__":
	import doctest

	doctest.testmod()













from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowerCamelCase						= {
    'configuration_bart': ['BART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BartConfig', 'BartOnnxConfig'],
    'tokenization_bart': ['BartTokenizer'],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= ['BartTokenizerFast']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= [
						    'BART_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'BartForCausalLM',
						    'BartForConditionalGeneration',
						    'BartForQuestionAnswering',
						    'BartForSequenceClassification',
						    'BartModel',
						    'BartPretrainedModel',
						    'PretrainedBartModel',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= [
						    'TFBartForConditionalGeneration',
						    'TFBartForSequenceClassification',
						    'TFBartModel',
						    'TFBartPretrainedModel',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= [
						    'FlaxBartDecoderPreTrainedModel',
						    'FlaxBartForCausalLM',
						    'FlaxBartForConditionalGeneration',
						    'FlaxBartForQuestionAnswering',
						    'FlaxBartForSequenceClassification',
						    'FlaxBartModel',
						    'FlaxBartPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
						from .tokenization_bart import BartTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_bart_fast import BartTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_bart import (
												    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BartForCausalLM,
												    BartForConditionalGeneration,
												    BartForQuestionAnswering,
												    BartForSequenceClassification,
												    BartModel,
												    BartPretrainedModel,
												    PretrainedBartModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_bart import (
												    TFBartForConditionalGeneration,
												    TFBartForSequenceClassification,
												    TFBartModel,
												    TFBartPretrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_bart import (
												    FlaxBartDecoderPreTrainedModel,
												    FlaxBartForCausalLM,
												    FlaxBartForConditionalGeneration,
												    FlaxBartForQuestionAnswering,
												    FlaxBartForSequenceClassification,
												    FlaxBartModel,
												    FlaxBartPreTrainedModel,
												)

else:
						import sys

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