code: 
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  __lowerCamelCase  				=					{
      """configuration_mobilenet_v1""": [
          """MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP""",
          """MobileNetV1Config""",
          """MobileNetV1OnnxConfig""",
      ],
  }
  
  try:
      if not is_vision_available():
          raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
      pass
  else:
      __lowerCamelCase  				=					["""MobileNetV1FeatureExtractor"""]
      __lowerCamelCase  				=					["""MobileNetV1ImageProcessor"""]
  
  try:
      if not is_torch_available():
          raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
      pass
  else:
      __lowerCamelCase  				=					[
          """MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """MobileNetV1ForImageClassification""",
          """MobileNetV1Model""",
          """MobileNetV1PreTrainedModel""",
          """load_tf_weights_in_mobilenet_v1""",
      ]
  
  
  if TYPE_CHECKING:
      from .configuration_mobilenet_va import (
          MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
          MobileNetVaConfig,
          MobileNetVaOnnxConfig,
      )
  
      try:
          if not is_vision_available():
              raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
          pass
      else:
          from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
          from .image_processing_mobilenet_va import MobileNetVaImageProcessor
  
      try:
          if not is_torch_available():
              raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
          pass
      else:
          from .modeling_mobilenet_va import (
              MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
              MobileNetVaForImageClassification,
              MobileNetVaModel,
              MobileNetVaPreTrainedModel,
              load_tf_weights_in_mobilenet_va,
          )
  
  
  else:
      import sys
  
      __lowerCamelCase  				=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
style_context: 
  
  
  
  def     UpperCAmelCase__ (							__snake_case						,				__snake_case						,				__snake_case						,				__snake_case						,				__snake_case							)   -> None:
    if target == 0:
      answer.append(path.copy()							)
    else:
      for index in range(__snake_case						,				len(__snake_case							)							):
        if target >= candidates[index]:
          path.append(candidates[index]							)
          backtrack(__snake_case						,				__snake_case						,				__snake_case						,				target - candidates[index]						,				__snake_case							)
          path.pop(len(__snake_case							) - 1							)
  
  
  
  
  def     UpperCAmelCase__ (							__snake_case						,				__snake_case							)   -> list:
    _A           =    []  # type: list[int]
    _A           =    []  # type: list[int]
    backtrack(__snake_case						,				__snake_case						,				__snake_case						,				__snake_case						,				0							)
    return answer
  
  
  
  
  def     UpperCAmelCase__ (							)   -> None:
    print(combination_sum([-8, 2.3, 0]						,				1							)							)
  
  
  if __name__ == "__main__":
      import doctest
  
      doctest.testmod()
      main()