




"""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


A_						=				logging.get_logger(__name__)

A_						=				{
    '''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(     __a ):







 '''simple docstring'''





 lowercase__ 					=					'''mobilenet_v1'''


 def __init__(				self:		int,      a_:		List[Any]=3,      a_:		Optional[int]=224,      a_:		Optional[int]=1.0,      a_:		Tuple=8,      a_:		List[Any]="relu6",      a_:		Optional[int]=True,      a_:		Union[str, Any]=0.999,      a_:		Tuple=0.02,      a_:		Dict=0.001,      **a_:		str,      ):




   '''simple docstring'''



   super().__init__(**__a		)

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

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







class 					lowercase(     __a ):







 '''simple docstring'''





 lowercase__ 					=					version.parse("1.11" )


 @property
 def  UpperCamelCase_   (				self:		str		):




   '''simple docstring'''



   return OrderedDict([("""pixel_values""", {0: """batch"""})]		)


 @property
 def  UpperCamelCase_   (				self:		Dict		):




   '''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  UpperCamelCase_   (				self:		Tuple		):




   '''simple docstring'''



   return 1E-4










lowerCamelCase       :       Tuple        =				{'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowerCamelCase       :       int        =				['''a''', '''b''', '''c''', '''d''', '''e''']
def 					snake_case_						(   lowerCAmelCase_				:  Optional[int]				,				lowerCAmelCase_				:  str				,				lowerCAmelCase_				:  List[Any]					):
							__lowercase					:							Dict			=   start
							# add current to visited
							visited.append(lowerCAmelCase_					)
							__lowercase					:							Dict			=   edges[current]
							for neighbor in neighbors:
														# if neighbor not in visited, visit
														if neighbor not in visited:
																					__lowercase					:							List[Any]			=   topological_sort(lowerCAmelCase_				,				lowerCAmelCase_				,				lowerCAmelCase_					)
    # if all neighbors visited add current to sort
							sort.append(lowerCAmelCase_					)
							# if all vertices haven't been visited select a new one to visit
							if len(lowerCAmelCase_					) != len(lowerCAmelCase_					):
														for vertice in vertices:
																					if vertice not in visited:
																												__lowercase					:							Tuple			=   topological_sort(lowerCAmelCase_				,				lowerCAmelCase_				,				lowerCAmelCase_					)
    # return sort
							return sort


if __name__ == "__main__":
	lowerCamelCase       :       Any        =				topological_sort('''a''', [], [])
	print(sort)