




from collections import namedtuple

a__		    =    namedtuple('''from_to''', '''from_ to''')

a__		    =    {
    '''atm''': from_to(1, 1),
    '''pascal''': from_to(0.000_0098, 10_1325),
    '''bar''': from_to(0.98_6923, 1.0_1325),
    '''kilopascal''': from_to(0.0098_6923, 101.325),
    '''megapascal''': from_to(9.8_6923, 0.10_1325),
    '''psi''': from_to(0.06_8046, 14.6959),
    '''inHg''': from_to(0.033_4211, 29.9213),
    '''torr''': from_to(0.0013_1579, 760),
}





def 							A__   (snake_case      :		float		,  snake_case      :		str		,  snake_case      :		str							)    ->	float:
					if from_type not in PRESSURE_CONVERSION:
										raise ValueError(
										    F'''Invalid \'from_type\' value: {from_type!r}  Supported values are:\n'''
										    + """, """.join(snake_case							)							)
					if to_type not in PRESSURE_CONVERSION:
										raise ValueError(
										    F'''Invalid \'to_type\' value: {to_type!r}.  Supported values are:\n'''
										    + """, """.join(snake_case							)							)
					return (
					    value * PRESSURE_CONVERSION[from_type].from_ * PRESSURE_CONVERSION[to_type].to
					)


if __name__ == "__main__":
	import doctest

	doctest.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


a__		    =    logging.get_logger(__name__)

a__		    =    {
    '''apple/mobilevit-small''': '''https://huggingface.co/apple/mobilevit-small/resolve/main/config.json''',
    '''apple/mobilevit-x-small''': '''https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json''',
    '''apple/mobilevit-xx-small''': '''https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json''',
    '''apple/deeplabv3-mobilevit-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json'''
    ),
    '''apple/deeplabv3-mobilevit-x-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json'''
    ),
    '''apple/deeplabv3-mobilevit-xx-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json'''
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}


class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



	"""simple docstring"""


	__magic_name__      :					Any			  =		'mobilevit'






	def __init__(				self		:	int				,    lowerCAmelCase		:	Dict=3				,    lowerCAmelCase		:	Dict=256				,    lowerCAmelCase		:	Any=2				,    lowerCAmelCase		:	Any=[144, 192, 240]				,    lowerCAmelCase		:	int=[16, 32, 64, 96, 128, 160, 640]				,    lowerCAmelCase		:	List[Any]=4				,    lowerCAmelCase		:	Tuple=2.0				,    lowerCAmelCase		:	Tuple=4.0				,    lowerCAmelCase		:	List[str]="silu"				,    lowerCAmelCase		:	Tuple=3				,    lowerCAmelCase		:	Tuple=32				,    lowerCAmelCase		:	Any=0.1				,    lowerCAmelCase		:	List[str]=0.0				,    lowerCAmelCase		:	Union[str, Any]=0.1				,    lowerCAmelCase		:	List[str]=0.02				,    lowerCAmelCase		:	Optional[Any]=1E-5				,    lowerCAmelCase		:	Union[str, Any]=True				,    lowerCAmelCase		:	List[str]=256				,    lowerCAmelCase		:	List[Any]=[6, 12, 18]				,    lowerCAmelCase		:	Tuple=0.1				,    lowerCAmelCase		:	List[str]=255				,    **lowerCAmelCase		:	Union[str, Any]				,    )  ->					Optional[Any]:







						"""simple docstring"""







						super().__init__(**lowerCAmelCase  )

						__UpperCamelCase				:  Tuple								=			num_channels
						__UpperCamelCase				:  Union[str, Any]								=			image_size
						__UpperCamelCase				:  List[Any]								=			patch_size
						__UpperCamelCase				:  Optional[int]								=			hidden_sizes
						__UpperCamelCase				:  Union[str, Any]								=			neck_hidden_sizes
						__UpperCamelCase				:  List[str]								=			num_attention_heads
						__UpperCamelCase				:  Union[str, Any]								=			mlp_ratio
						__UpperCamelCase				:  Tuple								=			expand_ratio
						__UpperCamelCase				:  Optional[Any]								=			hidden_act
						__UpperCamelCase				:  int								=			conv_kernel_size
						__UpperCamelCase				:  Any								=			output_stride
						__UpperCamelCase				:  int								=			hidden_dropout_prob
						__UpperCamelCase				:  Union[str, Any]								=			attention_probs_dropout_prob
						__UpperCamelCase				:  Dict								=			classifier_dropout_prob
						__UpperCamelCase				:  Any								=			initializer_range
						__UpperCamelCase				:  List[str]								=			layer_norm_eps
						__UpperCamelCase				:  Union[str, Any]								=			qkv_bias

						# decode head attributes for semantic segmentation
						__UpperCamelCase				:  Any								=			aspp_out_channels
						__UpperCamelCase				:  Union[str, Any]								=			atrous_rates
						__UpperCamelCase				:  Union[str, Any]								=			aspp_dropout_prob
						__UpperCamelCase				:  List[str]								=			semantic_loss_ignore_index






class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



	"""simple docstring"""


	__magic_name__      :					Optional[Any]			  =		version.parse('1.11'      )






	@property
	def 				lowerCamelCase__    (				self		:	Any  )  ->					Mapping[str, Mapping[int, str]]:







						"""simple docstring"""







						return OrderedDict([("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""})]  )






	@property
	def 				lowerCamelCase__    (				self		:	List[Any]  )  ->					Mapping[str, Mapping[int, str]]:







						"""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 				lowerCamelCase__    (				self		:	Optional[int]  )  ->					float:







						"""simple docstring"""







						return 1E-4






