


from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE						:List[Any]			=  {
    '''configuration_mobilenet_v2''': [
        '''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileNetV2Config''',
        '''MobileNetV2OnnxConfig''',
    ],
}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE						:List[Any]			=  ['''MobileNetV2FeatureExtractor''']
   SCREAMING_SNAKE_CASE						:str			=  ['''MobileNetV2ImageProcessor''']


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE						:Dict			=  [
       '''MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''MobileNetV2ForImageClassification''',
       '''MobileNetV2ForSemanticSegmentation''',
       '''MobileNetV2Model''',
       '''MobileNetV2PreTrainedModel''',
       '''load_tf_weights_in_mobilenet_v2''',
   ]


if TYPE_CHECKING:
   from .configuration_mobilenet_va import (
       MOBILENET_V2_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_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
          MobileNetVaForImageClassification,
          MobileNetVaForSemanticSegmentation,
          MobileNetVaModel,
          MobileNetVaPreTrainedModel,
          load_tf_weights_in_mobilenet_va,
      )


else:
   import sys

   SCREAMING_SNAKE_CASE						:Dict			=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








from __future__ import annotations



def       _lowerCAmelCase    (				lowerCAmelCase_				:int		,    lowerCAmelCase_				:int				)->list[str]:
   '''simple docstring'''






   if partitions <= 0:
      raise ValueError("partitions must be a positive number!"				)
   if partitions > number_of_bytes:
      raise ValueError("partitions can not > number_of_bytes!"				)
   snake_case_            =       number_of_bytes // partitions
   snake_case_            =       []
   for i in range(lowerCAmelCase_				):
      snake_case_            =       i * bytes_per_partition + 1
      snake_case_            =       (
          number_of_bytes if i == partitions - 1 else (i + 1) * bytes_per_partition
      )
      allocation_list.append(F'''{start_bytes}-{end_bytes}'''				)
   return allocation_list


if __name__ == "__main__":
   import doctest

   doctest.testmod()




