




'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowercase						:   Union[str, Any]      						=							{
    '''configuration_flava''': [
        '''FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''FlavaConfig''',
        '''FlavaImageCodebookConfig''',
        '''FlavaImageConfig''',
        '''FlavaMultimodalConfig''',
        '''FlavaTextConfig''',
    ],
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase						:   Tuple      						=							['''FlavaFeatureExtractor''']
      lowercase						:   List[str]      						=							['''FlavaImageProcessor''']
      lowercase						:   Dict      						=							['''FlavaProcessor''']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase						:   Optional[Any]      						=							[
          '''FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''FlavaForPreTraining''',
          '''FlavaImageCodebook''',
          '''FlavaImageModel''',
          '''FlavaModel''',
          '''FlavaMultimodalModel''',
          '''FlavaPreTrainedModel''',
          '''FlavaTextModel''',
      ]

if TYPE_CHECKING:
      from .configuration_flava import (
          FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP,
          FlavaConfig,
          FlavaImageCodebookConfig,
          FlavaImageConfig,
          FlavaMultimodalConfig,
          FlavaTextConfig,
      )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_flava import FlavaFeatureExtractor
            from .image_processing_flava import FlavaImageProcessor
            from .processing_flava import FlavaProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_flava import (
                FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST,
                FlavaForPreTraining,
                FlavaImageCodebook,
                FlavaImageModel,
                FlavaModel,
                FlavaMultimodalModel,
                FlavaPreTrainedModel,
                FlavaTextModel,
            )

else:
      import sys

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







'''simple docstring'''

from __future__ import annotations







class lowerCamelCase   :

				def __init__(       self,						lowercase_ )    ->							None:
					snake_case							=					value
					snake_case							=					None
					snake_case							=					None







class lowerCamelCase   :
				snake_case_							     = 42

				def __init__(       self )    ->							None:
					snake_case							=					0

				def 					_lowerCamelCase    (       self,						lowercase_,						lowercase_ )    ->							None:
					if node is None:
						return

					if path_sum == self.target:
						self.paths += 1

					if node.left:
						self.depth_first_search(node.left,						path_sum + node.left.value )
					if node.right:
						self.depth_first_search(node.right,						path_sum + node.right.value )






				def 					_lowerCamelCase    (       self,						lowercase_,						lowercase_ = None )    ->							int:
					if node is None:
						return 0
					if target is not None:
						snake_case							=					target

					self.depth_first_search(lowercase_,						node.value )
					self.path_sum(node.left )
					self.path_sum(node.right )

					return self.paths


if __name__ == "__main__":
						import doctest

						doctest.testmod()





