


"""simple docstring"""







lowerCAmelCase__				    =       [
    [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  a__      (    SCREAMING_SNAKE_CASE   :   Optional[Any]    ,				SCREAMING_SNAKE_CASE   :   List[Any]    ,				SCREAMING_SNAKE_CASE   :   Union[str, Any]    ,				SCREAMING_SNAKE_CASE   :   Tuple    ):


		'''simple docstring'''







		lowerCAmelCase					:					Optional[int]								=							[False] * len(SCREAMING_SNAKE_CASE    )
		lowerCAmelCase					:					str								=							[s]
		lowerCAmelCase					:					Optional[int]								=							True

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

		return visited[t]
def  a__      (    SCREAMING_SNAKE_CASE   :   List[Any]    ,				SCREAMING_SNAKE_CASE   :   List[str]    ,				SCREAMING_SNAKE_CASE   :   List[str]    ):


		'''simple docstring'''







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

				while s != source:
						# Find the minimum value in select path
						lowerCAmelCase					:					int								=							min(SCREAMING_SNAKE_CASE    ,				graph[parent[s]][s]    )
						lowerCAmelCase					:					Union[str, Any]								=							parent[s]

				max_flow += path_flow
				lowerCAmelCase					:					int								=							sink

				while v != source:
						lowerCAmelCase					:					str								=							parent[v]
						graph[u][v] -= path_flow
						graph[v][u] += path_flow
						lowerCAmelCase					:					List[Any]								=							parent[v]

		for i in range(len(SCREAMING_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))









"""simple docstring"""







from ...configuration_utils import PretrainedConfig


lowerCAmelCase__				    =       {
    '''google/tapas-base-finetuned-sqa''': (
        '''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
    ),
    '''google/tapas-base-finetuned-wtq''': (
        '''https://huggingface.co/google/tapas-base-finetuned-wtq/resolve/main/config.json'''
    ),
    '''google/tapas-base-finetuned-wikisql-supervised''': (
        '''https://huggingface.co/google/tapas-base-finetuned-wikisql-supervised/resolve/main/config.json'''
    ),
    '''google/tapas-base-finetuned-tabfact''': (
        '''https://huggingface.co/google/tapas-base-finetuned-tabfact/resolve/main/config.json'''
    ),
}


class 				SCREAMING_SNAKE_CASE__    (		lowercase    ):
       """simple docstring"""


       a  :    Any       ="tapas"

       def __init__(						self		,					snake_case__=30_522		,					snake_case__=768		,					snake_case__=12		,					snake_case__=12		,					snake_case__=3_072		,					snake_case__="gelu"		,					snake_case__=0.1		,					snake_case__=0.1		,					snake_case__=1_024		,					snake_case__=[3, 256, 256, 2, 256, 256, 10]		,					snake_case__=0.02		,					snake_case__=1e-12		,					snake_case__=0		,					snake_case__=10.0		,					snake_case__=0		,					snake_case__=1.0		,					snake_case__=None		,					snake_case__=1.0		,					snake_case__=False		,					snake_case__=None		,					snake_case__=1.0		,					snake_case__=1.0		,					snake_case__=False		,					snake_case__=False		,					snake_case__="ratio"		,					snake_case__=None		,					snake_case__=None		,					snake_case__=64		,					snake_case__=32		,					snake_case__=False		,					snake_case__=True		,					snake_case__=False		,					snake_case__=False		,					snake_case__=True		,					snake_case__=False		,					snake_case__=None		,					snake_case__=None		,					**snake_case__		,					):






         """simple docstring"""





         super().__init__(pad_token_id=snake_case__		,					**snake_case__						)

         # BERT hyperparameters (with updated max_position_embeddings and type_vocab_sizes)
         lowerCAmelCase					:					List[Any]								=							vocab_size
         lowerCAmelCase					:					List[str]								=							hidden_size
         lowerCAmelCase					:					Optional[Any]								=							num_hidden_layers
         lowerCAmelCase					:					List[str]								=							num_attention_heads
         lowerCAmelCase					:					Optional[Any]								=							hidden_act
         lowerCAmelCase					:					List[Any]								=							intermediate_size
         lowerCAmelCase					:					Optional[Any]								=							hidden_dropout_prob
         lowerCAmelCase					:					str								=							attention_probs_dropout_prob
         lowerCAmelCase					:					Any								=							max_position_embeddings
         lowerCAmelCase					:					Dict								=							type_vocab_sizes
         lowerCAmelCase					:					Union[str, Any]								=							initializer_range
         lowerCAmelCase					:					str								=							layer_norm_eps

         # Fine-tuning task hyperparameters
         lowerCAmelCase					:					Dict								=							positive_label_weight
         lowerCAmelCase					:					Union[str, Any]								=							num_aggregation_labels
         lowerCAmelCase					:					Optional[Any]								=							aggregation_loss_weight
         lowerCAmelCase					:					List[Any]								=							use_answer_as_supervision
         lowerCAmelCase					:					Dict								=							answer_loss_importance
         lowerCAmelCase					:					List[Any]								=							use_normalized_answer_loss
         lowerCAmelCase					:					List[str]								=							huber_loss_delta
         lowerCAmelCase					:					Optional[int]								=							temperature
         lowerCAmelCase					:					Optional[int]								=							aggregation_temperature
         lowerCAmelCase					:					Any								=							use_gumbel_for_cells
         lowerCAmelCase					:					Union[str, Any]								=							use_gumbel_for_aggregation
         lowerCAmelCase					:					Union[str, Any]								=							average_approximation_function
         lowerCAmelCase					:					int								=							cell_selection_preference
         lowerCAmelCase					:					Dict								=							answer_loss_cutoff
         lowerCAmelCase					:					Optional[int]								=							max_num_rows
         lowerCAmelCase					:					Union[str, Any]								=							max_num_columns
         lowerCAmelCase					:					Any								=							average_logits_per_cell
         lowerCAmelCase					:					List[Any]								=							select_one_column
         lowerCAmelCase					:					Tuple								=							allow_empty_column_selection
         lowerCAmelCase					:					str								=							init_cell_selection_weights_to_zero
         lowerCAmelCase					:					List[Any]								=							reset_position_index_per_cell
         lowerCAmelCase					:					Optional[Any]								=							disable_per_token_loss

         # Aggregation hyperparameters
         lowerCAmelCase					:					List[str]								=							aggregation_labels
         lowerCAmelCase					:					List[str]								=							no_aggregation_label_index

         if isinstance(self.aggregation_labels		,					snake_case__						):
           lowerCAmelCase					:					Union[str, Any]								=							{int(snake_case__						): v for k, v in aggregation_labels.items()}





