
def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   list:
       for i in range(len(SCREAMING_SNAKE_CASE__    ) - 1 ,     0 ,     -1    ):
              lowercase							:					List[Any]	     =				False

              for j in range(SCREAMING_SNAKE_CASE__ ,     0 ,     -1    ):
                     if unsorted[j] < unsorted[j - 1]:
                            lowercase     ,      lowercase							:					Union[str, Any]	     =				unsorted[j - 1], unsorted[j]
                            lowercase							:					Dict	     =				True

              for j in range(SCREAMING_SNAKE_CASE__    ):
                     if unsorted[j] > unsorted[j + 1]:
                            lowercase     ,      lowercase							:					Any	     =				unsorted[j + 1], unsorted[j]
                            lowercase							:					Any	     =				True

              if not swapped:
                     break
       return unsorted


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  lowercase  : Any						   =							input("""Enter numbers separated by a comma:\n""").strip()
  lowercase  : Any						   =							[int(item) for item in user_input.split(""",""")]
  print(F'''{cocktail_shaker_sort(unsorted) = }''')


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


lowercase  : List[Any]						   =							logging.get_logger(__name__)

lowercase  : List[Any]						   =							{
    """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 __snake_case		(				lowerCAmelCase					):
    _a		:						Dict=    "mobilenet_v1"
    def __init__(  self		,snake_case=3		,snake_case=224		,snake_case=1.0		,snake_case=8		,snake_case="relu6"		,snake_case=True		,snake_case=0.999		,snake_case=0.02		,snake_case=0.001		,**snake_case		,):



           '''simple docstring'''







           super().__init__(**snake_case				)

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

           lowercase							:					int	     =				num_channels
           lowercase							:					Union[str, Any]	     =				image_size
           lowercase							:					int	     =				depth_multiplier
           lowercase							:					Tuple	     =				min_depth
           lowercase							:					Dict	     =				hidden_act
           lowercase							:					Dict	     =				tf_padding
           lowercase							:					Dict	     =				classifier_dropout_prob
           lowercase							:					int	     =				initializer_range
           lowercase							:					List[str]	     =				layer_norm_eps






class __snake_case		(				lowerCAmelCase					):
    _a		:						int=    version.parse("1.11"					)
    @property
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           return OrderedDict([("""pixel_values""", {0: """batch"""})]				)
    @property
    def 				_SCREAMING_SNAKE_CASE	(  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 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           return 1e-4
