
"""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


UpperCamelCase     :    Optional[Any]       =			logging.get_logger(__name__)

UpperCamelCase     :    Optional[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 __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						"mobilenet_v1"





     def __init__(     self     ,					__UpperCAmelCase=3     ,					__UpperCAmelCase=224     ,					__UpperCAmelCase=1.0     ,					__UpperCAmelCase=8     ,					__UpperCAmelCase="relu6"     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=0.9_9_9     ,					__UpperCAmelCase=0.0_2     ,					__UpperCAmelCase=0.0_0_1     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      super().__init__(**__UpperCAmelCase				)

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

      __UpperCamelCase      =	num_channels
      __UpperCamelCase      =	image_size
      __UpperCamelCase      =	depth_multiplier
      __UpperCamelCase      =	min_depth
      __UpperCamelCase      =	hidden_act
      __UpperCamelCase      =	tf_padding
      __UpperCamelCase      =	classifier_dropout_prob
      __UpperCamelCase      =	initializer_range
      __UpperCamelCase      =	layer_norm_eps


class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						version.parse("1.11"      )





     @property
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




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





     @property
     def 						UpperCAmelCase (     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 						UpperCAmelCase (     self				):

      '''simple docstring'''




      return 1E-4





"""simple docstring"""

UpperCamelCase     :    Union[str, Any]       =			[
    [0, 1_6, 1_3, 0, 0, 0],
    [0, 0, 1_0, 1_2, 0, 0],
    [0, 4, 0, 0, 1_4, 0],
    [0, 0, 9, 0, 0, 2_0],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]






def 							A						(    snake_case				:Dict    , snake_case				:Tuple    , snake_case				:str    , snake_case				:Optional[int]		)				->     Union[str, Any]:
 # Return True if there is node that has not iterated.
 __UpperCamelCase      =	[False] * len(snake_case		)
 __UpperCamelCase      =	[s]
 __UpperCamelCase      =	True

 while queue:
  __UpperCamelCase      =	queue.pop(0		)
  for ind in range(len(graph[u]		)		):
   if visited[ind] is False and graph[u][ind] > 0:
    queue.append(snake_case		)
    __UpperCamelCase      =	True
    __UpperCamelCase      =	u

 return visited[t]






def 							A						(    snake_case				:int    , snake_case				:Any    , snake_case				:Union[str, Any]		)				->     Optional[int]:
 __UpperCamelCase      =	[-1] * (len(snake_case		))
 __UpperCamelCase      =	0
 __UpperCamelCase      =	[]
 __UpperCamelCase      =	[i[:] for i in graph]  # Record original cut, copy.
 while bfs(snake_case    , snake_case    , snake_case    , snake_case		):
  __UpperCamelCase      =	float('Inf'		)
  __UpperCamelCase      =	sink

  while s != source:
   # Find the minimum value in select path
   __UpperCamelCase      =	min(snake_case    , graph[parent[s]][s]		)
   __UpperCamelCase      =	parent[s]

  max_flow += path_flow
  __UpperCamelCase      =	sink

  while v != source:
   __UpperCamelCase      =	parent[v]
   graph[u][v] -= path_flow
   graph[v][u] += path_flow
   __UpperCamelCase      =	parent[v]

 for i in range(len(snake_case		)		):
  for j in range(len(graph[0]		)		):
   if graph[i][j] == 0 and temp[i][j] > 0:
    res.append((i, j)		)

 return res


if __name__ == "__main__":
      print(mincut(test_graph, source=0, sink=5))



