code: 
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  _A							    =	{
      """configuration_mobilenet_v1""": [
          """MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP""",
          """MobileNetV1Config""",
          """MobileNetV1OnnxConfig""",
      ],
  }
  
  try:
  							if not is_vision_available():
  														raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  							pass
  else:
  							_A							    =	["""MobileNetV1FeatureExtractor"""]
  							_A							    =	["""MobileNetV1ImageProcessor"""]
  
  try:
  							if not is_torch_available():
  														raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  							pass
  else:
  							_A							    =	[
  							    """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
  
  							_A							    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  from __future__ import annotations
  def 						lowerCAmelCase_       (	__a	,	__a	,	__a	,	__a )       ->			None:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE     ,							SCREAMING_SNAKE_CASE			: Any	     =m - 1, 0
  							while i >= 0 and j < n:
  														if key == mat[i][j]:
  																					print(f'Key {key} found at row- {i + 1} column- {j + 1}' )
  																					return
  														if key < mat[i][j]:
  																					i -= 1
  														else:
  																					j += 1
  							print(f'Key {key} not found' )
  def 						lowerCAmelCase_       (	)       ->			None:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: int	     =[[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
  							SCREAMING_SNAKE_CASE			: List[str]	     =int(input('''Enter the element to be searched:''' ) )
  							print(__a )
  							search_in_a_sorted_matrix(__a	,	len(__a )	,	len(mat[0] )	,	__a )
  
  
  if __name__ == "__main__":
  							import doctest
  
  							doctest.testmod()
  							main()
  
  
  
  
  
  
  