


'''simple docstring'''


def     snake_case_     (						SCREAMING_SNAKE_CASE__  ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE				: Dict  	=   word.upper()
				_SCREAMING_SNAKE_CASE				: Tuple  	=   0
				_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   {}
				_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   []

				for letter in word:
								if letter not in letter_nums:
												_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   str(SCREAMING_SNAKE_CASE__  )
												next_num += 1
								word_pattern.append(letter_nums[letter]  )
				return ".".join(SCREAMING_SNAKE_CASE__  )


if __name__ == "__main__":
				import pprint
				import time

				UpperCAmelCase_	:     Optional[int]							     =	time.time()
				with open('dictionary.txt') as in_file:
								UpperCAmelCase_	:     Tuple							     =	in_file.read().splitlines()

				UpperCAmelCase_	:     dict							     =	{}
				for word in word_list:
								UpperCAmelCase_	:     str							     =	get_word_pattern(word)
								if pattern in all_patterns:
												all_patterns[pattern].append(word)
								else:
												UpperCAmelCase_	:     Dict							     =	[word]

				with open('word_patterns.txt', 'w') as out_file:
								out_file.write(pprint.pformat(all_patterns))

				UpperCAmelCase_	:     str							     =	round(time.time() - start_time, 2)
				print(F"Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.")
				# Done!  9,581 word patterns found in 0.58 seconds.








'''simple docstring'''


from typing import TYPE_CHECKING

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


UpperCAmelCase_	:     Union[str, Any]							     =	{'configuration_pegasus': ['PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusConfig']}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_	:     Dict							     =	['PegasusTokenizer']

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_	:     Optional[int]							     =	['PegasusTokenizerFast']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_	:     Optional[int]							     =	[
				    'PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'PegasusForCausalLM',
				    'PegasusForConditionalGeneration',
				    'PegasusModel',
				    'PegasusPreTrainedModel',
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_	:     Optional[Any]							     =	[
				    'TFPegasusForConditionalGeneration',
				    'TFPegasusModel',
				    'TFPegasusPreTrainedModel',
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_	:     Any							     =	[
				    'FlaxPegasusForConditionalGeneration',
				    'FlaxPegasusModel',
				    'FlaxPegasusPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_pegasus import PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusConfig

				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_pegasus import PegasusTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_pegasus_fast import PegasusTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_pegasus import (
								    PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
								    PegasusForCausalLM,
								    PegasusForConditionalGeneration,
								    PegasusModel,
								    PegasusPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_pegasus import TFPegasusForConditionalGeneration, TFPegasusModel, TFPegasusPreTrainedModel

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_pegasus import (
								    FlaxPegasusForConditionalGeneration,
								    FlaxPegasusModel,
								    FlaxPegasusPreTrainedModel,
								)

else:
				import sys

				UpperCAmelCase_	:     List[str]							     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




