

from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCAmelCase     :   Any						     =  logging.get_logger(__name__)

lowerCAmelCase     :   Tuple						     =  {
    'google/mobilenet_v2_1.4_224': 'https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json',
    'google/mobilenet_v2_1.0_224': 'https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json',
    'google/mobilenet_v2_0.75_160': 'https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json',
    'google/mobilenet_v2_0.35_96': 'https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json',
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}
class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      Dict       =  '''mobilenet_v2'''

  def __init__(				self ,					_SCREAMING_SNAKE_CASE=3 ,					_SCREAMING_SNAKE_CASE=224 ,					_SCREAMING_SNAKE_CASE=1.0 ,					_SCREAMING_SNAKE_CASE=8 ,					_SCREAMING_SNAKE_CASE=8 ,					_SCREAMING_SNAKE_CASE=6 ,					_SCREAMING_SNAKE_CASE=32 ,					_SCREAMING_SNAKE_CASE=True ,					_SCREAMING_SNAKE_CASE=True ,					_SCREAMING_SNAKE_CASE="relu6" ,					_SCREAMING_SNAKE_CASE=True ,					_SCREAMING_SNAKE_CASE=0.8 ,					_SCREAMING_SNAKE_CASE=0.02 ,					_SCREAMING_SNAKE_CASE=0.001 ,					_SCREAMING_SNAKE_CASE=255 ,					**_SCREAMING_SNAKE_CASE ,					):





        """simple docstring"""







        super().__init__(**_SCREAMING_SNAKE_CASE					)

        if depth_multiplier <= 0:
              raise ValueError('depth_multiplier must be greater than zero.'					)

        SCREAMING_SNAKE_CASE_				:  Tuple           =     num_channels
        SCREAMING_SNAKE_CASE_				:  int           =     image_size
        SCREAMING_SNAKE_CASE_				:  Tuple           =     depth_multiplier
        SCREAMING_SNAKE_CASE_				:  str           =     depth_divisible_by
        SCREAMING_SNAKE_CASE_				:  str           =     min_depth
        SCREAMING_SNAKE_CASE_				:  str           =     expand_ratio
        SCREAMING_SNAKE_CASE_				:  Dict           =     output_stride
        SCREAMING_SNAKE_CASE_				:  int           =     first_layer_is_expansion
        SCREAMING_SNAKE_CASE_				:  List[Any]           =     finegrained_output
        SCREAMING_SNAKE_CASE_				:  str           =     hidden_act
        SCREAMING_SNAKE_CASE_				:  List[str]           =     tf_padding
        SCREAMING_SNAKE_CASE_				:  str           =     classifier_dropout_prob
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     initializer_range
        SCREAMING_SNAKE_CASE_				:  Tuple           =     layer_norm_eps
        SCREAMING_SNAKE_CASE_				:  int           =     semantic_loss_ignore_index

class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      Any       =  version.parse('''1.11''')

  @property
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        return OrderedDict([('pixel_values', {0: 'batch'})]					)

  @property
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        if self.task == "image-classification":
              return OrderedDict([('logits', {0: 'batch'})]					)
        else:
              return OrderedDict([('last_hidden_state', {0: 'batch'}), ('pooler_output', {0: 'batch'})]					)



  @property
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        return 1e-4









def    A_  (							a  ):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  List[Any]           =     0
      while num > 0:
            digit_sum += num % 1_0
            num //= 1_0
      return digit_sum

def    A_  (							a = 1_0_0  ):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  List[str]           =     1
      SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     2

      for i in range(2					,   max_n + 1  ):
            SCREAMING_SNAKE_CASE_				:  List[str]           =     pre_numerator
            SCREAMING_SNAKE_CASE_				:  str           =     2 * i // 3 if i % 3 == 0 else 1
            SCREAMING_SNAKE_CASE_				:  Tuple           =     cur_numerator
            SCREAMING_SNAKE_CASE_				:  Tuple           =     e_cont * pre_numerator + temp

      return sum_digits(a  )


if __name__ == "__main__":
    print(F'{solution() = }')






