"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase__						:						Tuple		  =			{
    'configuration_blip': [
        'BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlipConfig',
        'BlipTextConfig',
        'BlipVisionConfig',
    ],
    'processing_blip': ['BlipProcessor'],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__						:						Optional[int]		  =			['BlipImageProcessor']


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__						:						List[Any]		  =			[
						    'BLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'BlipModel',
						    'BlipPreTrainedModel',
						    'BlipForConditionalGeneration',
						    'BlipForQuestionAnswering',
						    'BlipVisionModel',
						    'BlipTextModel',
						    'BlipForImageTextRetrieval',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__						:						List[Any]		  =			[
						    'TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'TFBlipModel',
						    'TFBlipPreTrainedModel',
						    'TFBlipForConditionalGeneration',
						    'TFBlipForQuestionAnswering',
						    'TFBlipVisionModel',
						    'TFBlipTextModel',
						    'TFBlipForImageTextRetrieval',
						]

if TYPE_CHECKING:
						from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
						from .processing_blip import BlipProcessor

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_blip import BlipImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_blip import (
												    BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BlipForConditionalGeneration,
												    BlipForImageTextRetrieval,
												    BlipForQuestionAnswering,
												    BlipModel,
												    BlipPreTrainedModel,
												    BlipTextModel,
												    BlipVisionModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_blip import (
												    TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFBlipForConditionalGeneration,
												    TFBlipForImageTextRetrieval,
												    TFBlipForQuestionAnswering,
												    TFBlipModel,
												    TFBlipPreTrainedModel,
												    TFBlipTextModel,
												    TFBlipVisionModel,
												)

else:
						import sys

						lowerCAmelCase__						:						Optional[Any]		  =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




"""simple docstring"""






from __future__ import annotations

import collections
import pprint
from pathlib import Path



def 						a_		(      lowerCamelCase ):
				return "".join(sorted(lowerCamelCase ) )



def 						a_		(      lowerCamelCase ):
				return word_by_signature[signature(lowerCamelCase )]


lowerCAmelCase__						:						str		  =			Path(__file__).parent.joinpath('words.txt').read_text(encoding='utf-8')
lowerCAmelCase__						:						str		  =			sorted({word.strip().lower() for word in data.splitlines()})

lowerCAmelCase__						:						Optional[Any]		  =			collections.defaultdict(list)
for word in word_list:
						word_by_signature[signature(word)].append(word)

if __name__ == "__main__":
						lowerCAmelCase__						:						int		  =			{word: anagram(word) for word in word_list if len(anagram(word)) > 1}

						with open('anagrams.txt', 'w') as file:
												file.write('all_anagrams = \n ')
												file.write(pprint.pformat(all_anagrams))



