


from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__			:      Any								=logging.get_logger(__name__)

lowerCAmelCase__			:      Union[str, Any]								={
    'caidas/swin2sr-classicalsr-x2-64': (
        'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
    ),
}







class 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							_UpperCAmelCase      =						"""swin2sr"""

							_UpperCAmelCase      =						{
							    """hidden_size""": """embed_dim""",
							    """num_attention_heads""": """num_heads""",
							    """num_hidden_layers""": """num_layers""",
							}






							def __init__(      self			,						lowerCAmelCase__=6_4			,						lowerCAmelCase__=1			,						lowerCAmelCase__=3			,						lowerCAmelCase__=1_8_0			,						lowerCAmelCase__=[6, 6, 6, 6, 6, 6]			,						lowerCAmelCase__=[6, 6, 6, 6, 6, 6]			,						lowerCAmelCase__=8			,						lowerCAmelCase__=2.0			,						lowerCAmelCase__=True			,						lowerCAmelCase__=0.0			,						lowerCAmelCase__=0.0			,						lowerCAmelCase__=0.1			,						lowerCAmelCase__="gelu"			,						lowerCAmelCase__=False			,						lowerCAmelCase__=0.02			,						lowerCAmelCase__=1E-5			,						lowerCAmelCase__=2			,						lowerCAmelCase__=1.0			,						lowerCAmelCase__="1conv"			,						lowerCAmelCase__="pixelshuffle"			,						**lowerCAmelCase__			,						):





										"""simple docstring"""




										super().__init__(**lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					image_size
										SCREAMING_SNAKE_CASE_		:     List[str]					=					patch_size
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					num_channels
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					embed_dim
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					depths
										SCREAMING_SNAKE_CASE_		:     Any					=					len(lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					num_heads
										SCREAMING_SNAKE_CASE_		:     Any					=					window_size
										SCREAMING_SNAKE_CASE_		:     str					=					mlp_ratio
										SCREAMING_SNAKE_CASE_		:     Any					=					qkv_bias
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					hidden_dropout_prob
										SCREAMING_SNAKE_CASE_		:     Dict					=					attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE_		:     Any					=					drop_path_rate
										SCREAMING_SNAKE_CASE_		:     str					=					hidden_act
										SCREAMING_SNAKE_CASE_		:     List[str]					=					use_absolute_embeddings
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					layer_norm_eps
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					initializer_range
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					upscale
										SCREAMING_SNAKE_CASE_		:     int					=					img_range
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					resi_connection
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					upsampler












"""simple docstring"""






__UpperCAmelCase						=			[
    [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__   :			Dict							,			lowerCAmelCase__   :			Optional[int]							,			lowerCAmelCase__   :			List[str]							,			lowerCAmelCase__   :			Tuple			)    ->			Dict:



			'''simple docstring'''
			# Return True if there is node that has not iterated.
			a__  :	int		 =			[False] * len(lowerCAmelCase__			)
			a__  :	Optional[Any]		 =			[s]
			a__  :	Optional[int]		 =			True

			while queue:
						a__  :	Any		 =			queue.pop(0			)
						for ind in range(len(graph[u]			)			):
									if visited[ind] is False and graph[u][ind] > 0:
												queue.append(lowerCAmelCase__			)
												a__  :	Any		 =			True
												a__  :	Union[str, Any]		 =			u

			return visited[t]






def      lowercase__ (					lowerCAmelCase__   :			List[str]							,			lowerCAmelCase__   :			List[Any]							,			lowerCAmelCase__   :			Optional[Any]			)    ->			Any:



			'''simple docstring'''
			a__  :	Any		 =			[-1] * (len(lowerCAmelCase__			))
			a__  :	Any		 =			0
			a__  :	List[str]		 =			[]
			a__  :	Tuple		 =			[i[:] for i in graph]  # Record original cut, copy.
			while bfs(lowerCAmelCase__							,			lowerCAmelCase__							,			lowerCAmelCase__							,			lowerCAmelCase__			):
						a__  :	Any		 =			float("Inf"			)
						a__  :	Optional[int]		 =			sink

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

						max_flow += path_flow
						a__  :	List[str]		 =			sink

						while v != source:
									a__  :	int		 =			parent[v]
									graph[u][v] -= path_flow
									graph[v][u] += path_flow
									a__  :	List[str]		 =			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))