




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


__SCREAMING_SNAKE_CASE 						=logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE 						={
    """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  __magic_name__						(  __UpperCAmelCase):
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							List[str]	      =					"mobilenet_v2"


				def __init__(							self:   Tuple		,					_lowerCamelCase:   List[str]=3		,					_lowerCamelCase:   Union[str, Any]=2_24		,					_lowerCamelCase:   Optional[Any]=1.0		,					_lowerCamelCase:   Dict=8		,					_lowerCamelCase:   int=8		,					_lowerCamelCase:   Any=6		,					_lowerCamelCase:   Tuple=32		,					_lowerCamelCase:   Union[str, Any]=True		,					_lowerCamelCase:   Dict=True		,					_lowerCamelCase:   Any="relu6"		,					_lowerCamelCase:   Any=True		,					_lowerCamelCase:   Dict=0.8		,					_lowerCamelCase:   str=0.02		,					_lowerCamelCase:   Dict=0.0_01		,					_lowerCamelCase:   Any=2_55		,					**_lowerCamelCase:   Dict		,					):
											super().__init__(**_lowerCamelCase		)

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

											SCREAMING_SNAKE_CASE_   	=    num_channels
											SCREAMING_SNAKE_CASE_   	=    image_size
											SCREAMING_SNAKE_CASE_   	=    depth_multiplier
											SCREAMING_SNAKE_CASE_   	=    depth_divisible_by
											SCREAMING_SNAKE_CASE_   	=    min_depth
											SCREAMING_SNAKE_CASE_   	=    expand_ratio
											SCREAMING_SNAKE_CASE_   	=    output_stride
											SCREAMING_SNAKE_CASE_   	=    first_layer_is_expansion
											SCREAMING_SNAKE_CASE_   	=    finegrained_output
											SCREAMING_SNAKE_CASE_   	=    hidden_act
											SCREAMING_SNAKE_CASE_   	=    tf_padding
											SCREAMING_SNAKE_CASE_   	=    classifier_dropout_prob
											SCREAMING_SNAKE_CASE_   	=    initializer_range
											SCREAMING_SNAKE_CASE_   	=    layer_norm_eps
											SCREAMING_SNAKE_CASE_   	=    semantic_loss_ignore_index






class  __magic_name__						(  __UpperCAmelCase):
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							Dict	      =					version.parse("1.11")


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


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





				@property
				def     _A							(							self:   Tuple		):
											return 1E-4








def 			a   (_lowerCAmelCase     ):
							if number > 0:
														raise ValueError('''input must be a negative integer'''     )
							SCREAMING_SNAKE_CASE_   	=    len(bin(_lowerCAmelCase     )[3:]     )
							SCREAMING_SNAKE_CASE_   	=    bin(abs(_lowerCAmelCase     ) - (1 << binary_number_length)     )[3:]
							SCREAMING_SNAKE_CASE_   	=    (
							    (
							        '''1'''
							        + '''0''' * (binary_number_length - len(_lowerCAmelCase     ))
							        + twos_complement_number
							    )
							    if number < 0
							    else '''0'''
							)
							return "0b" + twos_complement_number


if __name__ == "__main__":
			import doctest

			doctest.testmod()


