'''simple docstring'''




_a   :	int 							=   [
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       List[str]:





       """simple docstring"""


       __UpperCAmelCase  :				Any       				=		[False] * len(_lowerCamelCase						)
       __UpperCAmelCase  :				str       				=		[s]
       __UpperCAmelCase  :				List[str]       				=		True

       while queue:
              __UpperCAmelCase  :				Any       				=		queue.pop(0						)
              for ind in range(len(graph[u]						)						):
                     if visited[ind] is False and graph[u][ind] > 0:
                            queue.append(_lowerCamelCase						)
                            __UpperCAmelCase  :				List[str]       				=		True
                            __UpperCAmelCase  :				int       				=		u

       return visited[t]

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       Optional[int]:





       """simple docstring"""


       __UpperCAmelCase  :				str       				=		[-1] * (len(_lowerCamelCase						))
       __UpperCAmelCase  :				Tuple       				=		0
       __UpperCAmelCase  :				Union[str, Any]       				=		[]
       __UpperCAmelCase  :				str       				=		[i[:] for i in graph]  # Record original cut, copy.
       while bfs(_lowerCamelCase							,    _lowerCamelCase							,    _lowerCamelCase							,    _lowerCamelCase						):
              __UpperCAmelCase  :				Optional[Any]       				=		float("Inf"						)
              __UpperCAmelCase  :				Optional[Any]       				=		sink

              while s != source:
                     # Find the minimum value in select path
                     __UpperCAmelCase  :				Optional[int]       				=		min(_lowerCamelCase							,    graph[parent[s]][s]						)
                     __UpperCAmelCase  :				Optional[Any]       				=		parent[s]

              max_flow += path_flow
              __UpperCAmelCase  :				Dict       				=		sink

              while v != source:
                     __UpperCAmelCase  :				Union[str, Any]       				=		parent[v]
                     graph[u][v] -= path_flow
                     graph[v][u] += path_flow
                     __UpperCAmelCase  :				Optional[Any]       				=		parent[v]

       for i in range(len(_lowerCamelCase						)						):
              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))







'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_a   :	List[str] 							=   logging.get_logger(__name__)

_a   :	Any 							=   {
    "kssteven/ibert-roberta-base": "https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json",
    "kssteven/ibert-roberta-large": "https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json",
    "kssteven/ibert-roberta-large-mnli": (
        "https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json"
    ),
}






class 		__A       (__magic_name__   ):
       snake_case       :Union[str, Any]				    =					"ibert"






       def __init__(      self				,     UpperCamelCase_=3_05_22				,     UpperCamelCase_=7_68				,     UpperCamelCase_=12				,     UpperCamelCase_=12				,     UpperCamelCase_=30_72				,     UpperCamelCase_="gelu"				,     UpperCamelCase_=0.1				,     UpperCamelCase_=0.1				,     UpperCamelCase_=5_12				,     UpperCamelCase_=2				,     UpperCamelCase_=0.0_2				,     UpperCamelCase_=1E-12				,     UpperCamelCase_=1				,     UpperCamelCase_=0				,     UpperCamelCase_=2				,     UpperCamelCase_="absolute"				,     UpperCamelCase_=False				,     UpperCamelCase_="none"				,     **UpperCamelCase_				,     ):
              super().__init__(pad_token_id=UpperCamelCase_				,     bos_token_id=UpperCamelCase_				,     eos_token_id=UpperCamelCase_				,     **UpperCamelCase_      )

              __UpperCAmelCase  :				List[Any]       				=		vocab_size
              __UpperCAmelCase  :				Optional[Any]       				=		hidden_size
              __UpperCAmelCase  :				List[Any]       				=		num_hidden_layers
              __UpperCAmelCase  :				Any       				=		num_attention_heads
              __UpperCAmelCase  :				List[str]       				=		hidden_act
              __UpperCAmelCase  :				List[str]       				=		intermediate_size
              __UpperCAmelCase  :				Optional[int]       				=		hidden_dropout_prob
              __UpperCAmelCase  :				Union[str, Any]       				=		attention_probs_dropout_prob
              __UpperCAmelCase  :				str       				=		max_position_embeddings
              __UpperCAmelCase  :				List[str]       				=		type_vocab_size
              __UpperCAmelCase  :				Dict       				=		initializer_range
              __UpperCAmelCase  :				Optional[int]       				=		layer_norm_eps
              __UpperCAmelCase  :				Any       				=		position_embedding_type
              __UpperCAmelCase  :				Tuple       				=		quant_mode
              __UpperCAmelCase  :				Union[str, Any]       				=		force_dequant






class 		__A       (__magic_name__   ):






       @property
       def 			_snake_case						(      self      ):
              if self.task == "multiple-choice":
                     __UpperCAmelCase  :				Optional[int]       				=		{0: "batch", 1: "choice", 2: "sequence"}
              else:
                     __UpperCAmelCase  :				Optional[int]       				=		{0: "batch", 1: "sequence"}
              return OrderedDict(
                  [
                      ("input_ids", dynamic_axis),
                      ("attention_mask", dynamic_axis),
                  ]      )






