

"""simple docstring"""





from typing import TYPE_CHECKING

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


__UpperCamelCase  :      Dict							      =		{
    '''configuration_clip''': [
        '''CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''CLIPConfig''',
        '''CLIPOnnxConfig''',
        '''CLIPTextConfig''',
        '''CLIPVisionConfig''',
    ],
    '''processing_clip''': ['''CLIPProcessor'''],
    '''tokenization_clip''': ['''CLIPTokenizer'''],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase  :      int							      =		['''CLIPTokenizerFast''']

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase  :      Optional[int]							      =		['''CLIPFeatureExtractor''']
							__UpperCamelCase  :      Optional[Any]							      =		['''CLIPImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase  :      Tuple							      =		[
							    '''CLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''CLIPModel''',
							    '''CLIPPreTrainedModel''',
							    '''CLIPTextModel''',
							    '''CLIPTextModelWithProjection''',
							    '''CLIPVisionModel''',
							    '''CLIPVisionModelWithProjection''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase  :      Optional[int]							      =		[
							    '''TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFCLIPModel''',
							    '''TFCLIPPreTrainedModel''',
							    '''TFCLIPTextModel''',
							    '''TFCLIPVisionModel''',
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase  :      Optional[Any]							      =		[
							    '''FlaxCLIPModel''',
							    '''FlaxCLIPPreTrainedModel''',
							    '''FlaxCLIPTextModel''',
							    '''FlaxCLIPTextPreTrainedModel''',
							    '''FlaxCLIPVisionModel''',
							    '''FlaxCLIPVisionPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_clip import (
							    CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    CLIPConfig,
							    CLIPOnnxConfig,
							    CLIPTextConfig,
							    CLIPVisionConfig,
							)
							from .processing_clip import CLIPProcessor
							from .tokenization_clip import CLIPTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_clip_fast import CLIPTokenizerFast

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_clip import CLIPFeatureExtractor
														from .image_processing_clip import CLIPImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_clip import (
														    CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    CLIPModel,
														    CLIPPreTrainedModel,
														    CLIPTextModel,
														    CLIPTextModelWithProjection,
														    CLIPVisionModel,
														    CLIPVisionModelWithProjection,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_clip import (
														    TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFCLIPModel,
														    TFCLIPPreTrainedModel,
														    TFCLIPTextModel,
														    TFCLIPVisionModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_clip import (
														    FlaxCLIPModel,
														    FlaxCLIPPreTrainedModel,
														    FlaxCLIPTextModel,
														    FlaxCLIPTextPreTrainedModel,
														    FlaxCLIPVisionModel,
														    FlaxCLIPVisionPreTrainedModel,
														)


else:
							import sys

							__UpperCamelCase  :      Tuple							      =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







from __future__ import annotations

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    dict	,     SCREAMING_SNAKE_CASE_		:    str			):



     '''simple docstring'''





     lowercase__      , lowercase__    :   List[str]      =       set(SCREAMING_SNAKE_CASE_			), [start]

     while stack:
          lowercase__    :   Union[str, Any]      =       stack.pop()
          explored.add(SCREAMING_SNAKE_CASE_			)
          # Differences from BFS:
          # 1) pop last element instead of first one
          # 2) add adjacent elements to stack without exploring them
          for adj in reversed(graph[v]			):
               if adj not in explored:
                    stack.append(SCREAMING_SNAKE_CASE_			)
     return explored


snake_case_			  = {
    '''A''': ['''B''', '''C''', '''D'''],
    '''B''': ['''A''', '''D''', '''E'''],
    '''C''': ['''A''', '''F'''],
    '''D''': ['''B''', '''D'''],
    '''E''': ['''B''', '''F'''],
    '''F''': ['''C''', '''E''', '''G'''],
    '''G''': ['''F'''],
}

if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(depth_first_search(G, '''A'''))

