


from collections.abc import Iterable
from typing import Generic, TypeVar

_snake_case	:						Dict         =							TypeVar("_T")

class 							a						(Generic[_T] ):




							"""simple docstring"""


							def __init__(				self			:    int       ,      lowerCamelCase			:    Iterable[_T] | None = None							)      ->       None:
														__snake_case						:     list[_T]									=  list(iterable or []							)
														__snake_case						:     list[_T]									=  []

							def __len__(				self			:    Optional[int]							)      ->       int:
														return len(self._stacka							) + len(self._stacka							)

							def __repr__(				self			:    Tuple							)      ->       str:
														return F'Queue({tuple(self._stacka[::-1] + self._stacka							)})'

							def        __snake_case   (				self			:    Tuple       ,      lowerCamelCase			:    _T							)      ->       None:
														self._stacka.append(lowerCamelCase							)






							def        __snake_case   (				self			:    str							)      ->       _T:
														__snake_case						:     List[str]									=  self._stacka.pop
														__snake_case						:     int									=  self._stacka.append

														if not self._stacka:
																					while self._stacka:
																												stacka_append(stacka_pop()							)

														if not self._stacka:
																					raise IndexError("Queue is empty"							)
														return self._stacka.pop()


if __name__ == "__main__":
			from doctest import testmod

			testmod()








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


__UpperCamelCase:	Optional[int] = logging.get_logger(__name__)

__UpperCamelCase:	Optional[int] = {
    """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       __lowerCAmelCase					(       _UpperCamelCase      ):


	'''simple docstring'''





	_A													=				"mobilenet_v1"

	def __init__(						self:						Dict,					lowerCamelCase_:						Any=3,					lowerCamelCase_:						Dict=224,					lowerCamelCase_:						int=1.0,					lowerCamelCase_:						List[Any]=8,					lowerCamelCase_:						int="relu6",					lowerCamelCase_:						Optional[int]=True,					lowerCamelCase_:						Any=0.9_9_9,					lowerCamelCase_:						List[str]=0.0_2,					lowerCamelCase_:						Optional[int]=0.0_0_1,					**lowerCamelCase_:						Tuple,					):
			super().__init__(**lowerCamelCase_			)

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

			lowercase__					:      Optional[int]      =		num_channels
			lowercase__					:      List[Any]      =		image_size
			lowercase__					:      str      =		depth_multiplier
			lowercase__					:      Optional[Any]      =		min_depth
			lowercase__					:      int      =		hidden_act
			lowercase__					:      Dict      =		tf_padding
			lowercase__					:      Optional[Any]      =		classifier_dropout_prob
			lowercase__					:      int      =		initializer_range
			lowercase__					:      Any      =		layer_norm_eps


class       __lowerCAmelCase					(       _UpperCamelCase      ):


	'''simple docstring'''





	_A													=				version.parse("1.11"      )

	@property
	def    snake_case__(						self:						Optional[int]			):
			return OrderedDict([('pixel_values', {0: 'batch'})]			)

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





	@property
	def    snake_case__(						self:						List[Any]			):
			return 1E-4


