

'''simple docstring'''






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__      		=			logging.get_logger(__name__)

lowerCAmelCase__      		=			{
    '''google/mobilenet_v1_1.0_224''': '''https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json''',
    '''google/mobilenet_v1_0.75_192''': '''https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json''',
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}






class     lowercase_			(lowerCamelCase__   ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE					:						List[Any]           =    'mobilenet_v1'






  def __init__(   self     :  Tuple      ,lowercase__     :  Tuple=3      ,lowercase__     :  List[Any]=2_2_4      ,lowercase__     :  str=1.0      ,lowercase__     :  List[str]=8      ,lowercase__     :  Tuple="relu6"      ,lowercase__     :  Optional[Any]=True      ,lowercase__     :  int=0.9_9_9      ,lowercase__     :  Optional[int]=0.0_2      ,lowercase__     :  List[str]=0.0_0_1      ,**lowercase__     :  Union[str, Any]      ,):
   super().__init__(**lowercase__    )

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

   __lowercase													=				num_channels
   __lowercase													=				image_size
   __lowercase													=				depth_multiplier
   __lowercase													=				min_depth
   __lowercase													=				hidden_act
   __lowercase													=				tf_padding
   __lowercase													=				classifier_dropout_prob
   __lowercase													=				initializer_range
   __lowercase													=				layer_norm_eps






class     lowercase_			(lowerCamelCase__   ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE					:						Dict           =    version.parse('1.11'   )






  @property
  def       SCREAMING_SNAKE_CASE   (   self     :  Dict    ):
   return OrderedDict([('''pixel_values''', {0: '''batch'''})]    )






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






  @property
  def       SCREAMING_SNAKE_CASE   (   self     :  Optional[Any]    ):
   return 1e-4




'''simple docstring'''






import random
from typing import Any


def 	_A  (					A__   ):






 """simple docstring"""



 for _ in range(len(A__   )   ):
  __lowercase													=				random.randint(0  ,       len(A__   ) - 1   )
  __lowercase													=				random.randint(0  ,       len(A__   ) - 1   )
  __lowercase						,			__lowercase													=				data[b], data[a]
 return data


if __name__ == "__main__":
 lowerCAmelCase__      		=			[0, 1, 2, 3, 4, 5, 6, 7]
 lowerCAmelCase__      		=			['''python''', '''says''', '''hello''', '''!''']
 print('''Fisher-Yates Shuffle:''')
 print('''List''', integers, strings)
 print('''FY Shuffle''', fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))

