
'''simple docstring'''


import enum
import inspect
from typing import Iterable, List, Optional, Tuple, Union

class 		__lowercase			(					enum.Enum      ):
			lowerCamelCase     :						int		 =     'timm'
			lowerCamelCase     :						int		 =     'transformers'




def lowercase_		(				_lowercase     ,    _lowercase     ,    _lowercase			)       ->							List[Any]:
					'''simple docstring'''

					if stage_names is None:
										raise ValueError('''Stage_names must be set for transformers backbones'''			)

					if out_features is not None:
										if not isinstance(_A     ,    (list,)			):
															raise ValueError(F"""out_features must be a list {type(_A			)}"""			)
										if any(feat not in stage_names for feat in out_features			):
															raise ValueError(F"""out_features must be a subset of stage_names: {stage_names} got {out_features}"""			)

					if out_indices is not None:
										if not isinstance(_A     ,    (list, tuple)			):
															raise ValueError(F"""out_indices must be a list or tuple, got {type(_A			)}"""			)
										if any(idx >= len(_A			) for idx in out_indices			):
															raise ValueError('''out_indices must be valid indices for stage_names {stage_names}, got {out_indices}'''			)

					if out_features is not None and out_indices is not None:
										if len(_A			) != len(_A			):
															raise ValueError('''out_features and out_indices should have the same length if both are set'''			)
										if out_features != [stage_names[idx] for idx in out_indices]:
															raise ValueError('''out_features and out_indices should correspond to the same stages if both are set'''			)




def lowercase_		(				_lowercase     ,    _lowercase     ,    _lowercase     ,    )       ->							Any:
					'''simple docstring'''

					if out_indices is None and out_features is None:
										lowerCamelCase_   : List[Any]       =						[len(_A			) - 1]
										lowerCamelCase_   : Any       =						[stage_names[-1]]
					elif out_indices is None and out_features is not None:
										lowerCamelCase_   : Tuple       =						[stage_names.index(_A			) for layer in out_features]
					elif out_features is None and out_indices is not None:
										lowerCamelCase_   : str       =						[stage_names[idx] for idx in out_indices]
					return out_features, out_indices




def lowercase_		(				_lowercase     ,    _lowercase     ,    _lowercase     ,    )       ->							Optional[int]:
					'''simple docstring'''

					verify_out_features_out_indices(out_features=_A     ,    out_indices=_A     ,    stage_names=_A			)
					lowerCamelCase_, lowerCamelCase_   : Optional[int]       =						_align_output_features_output_indices(
					    out_features=_A     ,    out_indices=_A     ,    stage_names=_A			)
					# Verify that the aligned out_features and out_indices are valid
					verify_out_features_out_indices(out_features=_A     ,    out_indices=_A     ,    stage_names=_A			)
					return output_features, output_indices

class 		__lowercase			:
			lowerCamelCase     :						Optional[BackboneType]		 =     None

			def     UpperCAmelCase__	(self     ,				A ):






								if getattr(self     ,				'''_backbone'''     ,				lowercase_ ) is None:
													raise ValueError('''self._backbone must be set before calling _init_timm_backbone''' )

								# These will diagree with the defaults for the transformers models e.g. for resnet50
								# the transformer model has out_features = ['stem', 'stage1', 'stage2', 'stage3', 'stage4']
								# the timm model has out_features = ['act', 'layer1', 'layer2', 'layer3', 'layer4']
								lowerCamelCase_   : Dict       =						[stage['''module'''] for stage in self._backbone.feature_info.info]
								lowerCamelCase_   : List[Any]       =						[stage['''num_chs'''] for stage in self._backbone.feature_info.info]
								lowerCamelCase_   : int       =						self._backbone.feature_info.out_indices
								lowerCamelCase_   : Optional[Any]       =						self._backbone.feature_info.module_name()

								# We verify the out indices and out features are valid
								verify_out_features_out_indices(
								    out_features=lowercase_     ,				out_indices=lowercase_     ,				stage_names=self.stage_names )
								lowerCamelCase_, lowerCamelCase_   : Any       =						out_features, out_indices

			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_   : Union[str, Any]       =						getattr(lowercase_     ,				'''stage_names''' )
								lowerCamelCase_   : Optional[int]       =						getattr(lowercase_     ,				'''out_features'''     ,				lowercase_ )
								lowerCamelCase_   : Union[str, Any]       =						getattr(lowercase_     ,				'''out_indices'''     ,				lowercase_ )

								lowerCamelCase_   : List[Any]       =						stage_names
								lowerCamelCase_, lowerCamelCase_   : Optional[int]       =						get_aligned_output_features_output_indices(
								    out_features=lowercase_     ,				out_indices=lowercase_     ,				stage_names=lowercase_ )
								# Number of channels for each stage. This is set in the transformer backbone model init
								lowerCamelCase_   : List[Any]       =						None

			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_   : Optional[int]       =						config

								lowerCamelCase_   : Union[str, Any]       =						getattr(lowercase_     ,				'''use_timm_backbone'''     ,				lowercase_ )
								lowerCamelCase_   : int       =						BackboneType.TIMM if self.use_timm_backbone else BackboneType.TRANSFORMERS

								if self.backbone_type == BackboneType.TIMM:
													self._init_timm_backbone(lowercase_ )
								elif self.backbone_type == BackboneType.TRANSFORMERS:
													self._init_transformers_backbone(lowercase_ )
								else:
													raise ValueError(F"""backbone_type {self.backbone_type} not supported.""" )

			@property
			def     UpperCAmelCase__	(self ):
								return self._out_features

			@out_features.setter
			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_, lowerCamelCase_   : str       =						get_aligned_output_features_output_indices(
								    out_features=lowercase_     ,				out_indices=lowercase_     ,				stage_names=self.stage_names )

			@property
			def     UpperCAmelCase__	(self ):
								return self._out_indices

			@out_indices.setter
			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_, lowerCamelCase_   : str       =						get_aligned_output_features_output_indices(
								    out_features=lowercase_     ,				out_indices=lowercase_     ,				stage_names=self.stage_names )

			@property
			def     UpperCAmelCase__	(self ):
								return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names )}

			@property
			def     UpperCAmelCase__	(self ):
								return [self.out_feature_channels[name] for name in self.out_features]

			def     UpperCAmelCase__	(self     ,				*A     ,				**A ):
								lowerCamelCase_   : Tuple       =						dict(inspect.signature(self.forward ).parameters )
								lowerCamelCase_   : Any       =						{k: v for k, v in kwargs.items() if k in signature}
								return self(*lowercase_     ,				**lowercase_ )

			def     UpperCAmelCase__	(self     ,				A     ,				A = None     ,				A = None     ,				A = None     ,				):
								raise NotImplementedError('''This method should be implemented by the derived class.''' )






			def     UpperCAmelCase__	(self ):
								lowerCamelCase_   : List[Any]       =						super().to_dict()
								lowerCamelCase_   : Tuple       =						output.pop('''_out_features''' )
								lowerCamelCase_   : str       =						output.pop('''_out_indices''' )
								return output

class 		__lowercase			:

			@property
			def     UpperCAmelCase__	(self ):
								return self._out_features

			@out_features.setter
			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_, lowerCamelCase_   : str       =						get_aligned_output_features_output_indices(
								    out_features=lowercase_     ,				out_indices=lowercase_     ,				stage_names=self.stage_names )

			@property
			def     UpperCAmelCase__	(self ):
								return self._out_indices

			@out_indices.setter
			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_, lowerCamelCase_   : Any       =						get_aligned_output_features_output_indices(
								    out_features=lowercase_     ,				out_indices=lowercase_     ,				stage_names=self.stage_names )






			def     UpperCAmelCase__	(self ):
								lowerCamelCase_   : Any       =						super().to_dict()
								lowerCamelCase_   : Optional[int]       =						output.pop('''_out_features''' )
								lowerCamelCase_   : Optional[Any]       =						output.pop('''_out_indices''' )
								return output




'''simple docstring'''


__lowercase							:				str					=       [
    ['''ab-e1''', '''ac-e3''', '''ad-e5''', '''bc-e4''', '''bd-e2''', '''be-e6''', '''bh-e12''', '''cd-e2''', '''ce-e4''',
     '''de-e1''', '''df-e8''', '''dg-e5''', '''dh-e10''', '''ef-e3''', '''eg-e2''', '''fg-e6''', '''gh-e6''', '''hi-e3'''],
    ['''ab-e1''', '''ac-e3''', '''ad-e5''', '''bc-e4''', '''bd-e2''', '''be-e6''', '''cd-e2''', '''de-e1''', '''df-e8''',
     '''ef-e3''', '''eg-e2''', '''fg-e6'''],
    ['''ab-e1''', '''ac-e3''', '''bc-e4''', '''bd-e2''', '''de-e1''', '''df-e8''', '''dg-e5''', '''ef-e3''', '''eg-e2''',
     '''eh-e12''', '''fg-e6''', '''fh-e10''', '''gh-e6'''],
    ['''ab-e1''', '''ac-e3''', '''bc-e4''', '''bd-e2''', '''bh-e12''', '''cd-e2''', '''df-e8''', '''dh-e10'''],
    ['''ab-e1''', '''ac-e3''', '''ad-e5''', '''bc-e4''', '''bd-e2''', '''cd-e2''', '''ce-e4''', '''de-e1''', '''df-e8''',
     '''dg-e5''', '''ef-e3''', '''eg-e2''', '''fg-e6''']
]




def lowercase_		(				_lowercase			)       ->							Optional[int]:
					'''simple docstring'''

					lowerCamelCase_   : Union[str, Any]       =						set()
					for row in edge_array:
										for item in row:
															distinct_edge.add(item[0]			)
					return list(_lowercase			)




def lowercase_		(				_lowercase     ,    _lowercase			)       ->							int:
					'''simple docstring'''

					lowerCamelCase_   : List[Any]       =						['''0'''] * len(_lowercase			)
					for i, row in enumerate(_lowercase			):
										for item in row:
															if distinct_edge in item[0]:
																				lowerCamelCase_   : Union[str, Any]       =						'''1'''
																				break
					return "".join(_lowercase			)




def lowercase_		(				_lowercase			)       ->							Optional[int]:
					'''simple docstring'''

					lowerCamelCase_   : int       =						get_distinct_edge(_lowercase			)
					lowerCamelCase_   : Any       =						{}

					for item in distinct_edge:
										lowerCamelCase_   : Dict       =						get_bitcode(_lowercase     ,    _lowercase			)
										# print('bit',bit)
										# bt=''.join(bit)
										lowerCamelCase_   : Dict       =						bit.count('''1'''			)
										lowerCamelCase_   : Tuple       =						[s, bit]
					# Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
					lowerCamelCase_   : int       =						[
					    [k, v[0], v[1]]
					    for k, v in sorted(frequency_table.items()     ,    key=lambda _lowercase			: v[1][0]     ,    reverse=_lowercase			)
					]
					return sorted_frequency_table




def lowercase_		(				_lowercase			)       ->							Any:
					'''simple docstring'''

					lowerCamelCase_   : Dict       =						{}
					for _, item in enumerate(_lowercase			):
										nodes.setdefault(item[2]     ,    []			).append(item[0]			)
					return nodes




def lowercase_		(				_lowercase			)       ->							str:
					'''simple docstring'''

					lowerCamelCase_   : List[Any]       =						{}
					for key, value in nodes.items():
										lowerCamelCase_   : Optional[int]       =						value
					return cluster




def lowercase_		(				_lowercase			)       ->							Optional[int]:
					'''simple docstring'''

					return [i * 100 / len(_lowercase			) for i in cluster]




def lowercase_		(				)       ->							None:
					'''simple docstring'''

					print('''\nNodes\n'''			)
					for key, value in nodes.items():
										print(_lowercase     ,    _lowercase			)
					print('''\nSupport\n'''			)
					print(_lowercase			)
					print('''\n Cluster \n'''			)
					for key, value in sorted(cluster.items()     ,    reverse=_lowercase			):
										print(_lowercase     ,    _lowercase			)
					print('''\n Graph\n'''			)
					for key, value in graph.items():
										print(_lowercase     ,    _lowercase			)
					print('''\n Edge List of Frequent subgraphs \n'''			)
					for edge_list in freq_subgraph_edge_list:
										print(_lowercase			)




def lowercase_		(				_lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase			)       ->							Tuple:
					'''simple docstring'''

					for i in cluster[ca]:
										lowerCamelCase_   : str       =						0
										lowerCamelCase_   : Optional[Any]       =						ca + 1
										while ca < max(cluster.keys()			):
															for j in cluster[ca]:
																				if int(_lowercase     ,    2			) & int(_lowercase     ,    2			) == int(_lowercase     ,    2			):
																									if tuple(nodes[i]			) in graph:
																														graph[tuple(nodes[i]			)].append(nodes[j]			)
																									else:
																														lowerCamelCase_   : Union[str, Any]       =						[nodes[j]]
																									count += 1
															if count == 0:
																				lowerCamelCase_   : Any       =						ca + 1
															else:
																				break




def lowercase_		(				_lowercase     ,    _lowercase			)       ->							Dict:
					'''simple docstring'''

					lowerCamelCase_   : List[str]       =						cluster[max(cluster.keys()			)]
					lowerCamelCase_   : Tuple       =						'''Header'''
					lowerCamelCase_   : Optional[int]       =						{}
					for i in x:
										if (["Header"],) in graph:
															graph[(["Header"],)].append(x[i]			)
										else:
															lowerCamelCase_   : Any       =						[x[i]]
					for i in x:
										lowerCamelCase_   : Any       =						[['''Header''']]
					lowerCamelCase_   : List[Any]       =						1
					while i < max(_lowercase			) - 1:
										create_edge(_lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase			)
										lowerCamelCase_   : Tuple       =						i + 1
					return graph




def lowercase_		(				_lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase=None			)       ->							Dict:
					'''simple docstring'''

					lowerCamelCase_   : List[str]       =						(path or []) + [start]
					if start == end:
										paths.append(_lowercase			)
					for node in graph[start]:
										if tuple(_lowercase			) not in path:
															my_dfs(_lowercase     ,    tuple(_lowercase			)     ,    _lowercase     ,    _lowercase			)




def lowercase_		(				_lowercase     ,    _lowercase     ,    _lowercase			)       ->							int:
					'''simple docstring'''

					lowerCamelCase_   : Dict       =						int(s / 100 * (len(_lowercase			) - 1)			)
					for i in cluster[k]:
										my_dfs(_lowercase     ,    tuple(cluster[k][i]			)     ,    (['''Header'''],)			)




def lowercase_		(				_lowercase			)       ->							Optional[Any]:
					'''simple docstring'''

					lowerCamelCase_   : Tuple       =						[]
					for edges in paths:
										lowerCamelCase_   : Optional[int]       =						[]
										for j in range(len(_lowercase			) - 1			):
															lowerCamelCase_   : List[str]       =						list(edges[j]			)
															for e in temp:
																				lowerCamelCase_   : Dict       =						(e[0], e[1])
																				el.append(_lowercase			)
										freq_sub_el.append(_lowercase			)
					return freq_sub_el




def lowercase_		(				_lowercase			)       ->							int:
					'''simple docstring'''

					for i in range(len(_lowercase			)			):
										for j in range(len(edge_array[i]			)			):
															lowerCamelCase_   : Any       =						edge_array[i][j].split('''-'''			)
															lowerCamelCase_   : Optional[Any]       =						t


if __name__ == "__main__":
					preprocess(edge_array)
					__lowercase							:				List[Any]					=       get_frequency_table(edge_array)
					__lowercase							:				Optional[Any]					=       get_nodes(frequency_table)
					__lowercase							:				int					=       get_cluster(nodes)
					__lowercase							:				Any					=       get_support(cluster)
					__lowercase							:				int					=       construct_graph(cluster, nodes)
					find_freq_subgraph_given_support(60, cluster, graph)
					__lowercase							:				list					=       []
					__lowercase							:				Optional[int]					=       freq_subgraphs_edge_list(paths)
					print_all()


