






import inspect

from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
						import jax





@require_flax
class  snake_case__      :
	def     __magic_name__       (       self				)							->   int:
							__magic_name__		,__magic_name__    :     List[Any]     		=      self.prepare_init_args_and_inputs_for_common()

							__magic_name__    :     List[Any]     		=      self.model_class(**lowerCAmelCase__				)
							__magic_name__    :     Dict     		=      model.init(inputs_dict["""prng_key"""]    ,     inputs_dict["""sample"""]				)
							jax.lax.stop_gradient(lowerCAmelCase__				)

							__magic_name__    :     str     		=      model.apply(lowerCAmelCase__    ,     inputs_dict["""sample"""]				)

							if isinstance(lowerCAmelCase__    ,     lowerCAmelCase__				):
													__magic_name__    :     Optional[Any]     		=      output.sample

							self.assertIsNotNone(lowerCAmelCase__				)
							__magic_name__    :     Union[str, Any]     		=      inputs_dict["""sample"""].shape
							self.assertEqual(output.shape    ,     lowerCAmelCase__    ,     """Input and output shapes do not match"""				)
	def     __magic_name__       (       self				)							->   str:
							__magic_name__		,__magic_name__    :     List[str]     		=      self.prepare_init_args_and_inputs_for_common()

							__magic_name__    :     Any     		=      16
							__magic_name__    :     str     		=      (16, 32)

							__magic_name__    :     List[Any]     		=      self.model_class(**lowerCAmelCase__				)
							__magic_name__    :     int     		=      model.init(inputs_dict["""prng_key"""]    ,     inputs_dict["""sample"""]				)
							jax.lax.stop_gradient(lowerCAmelCase__				)

							__magic_name__    :     Any     		=      model.apply(lowerCAmelCase__    ,     inputs_dict["""sample"""]				)

							if isinstance(lowerCAmelCase__    ,     lowerCAmelCase__				):
													__magic_name__    :     int     		=      output.sample

							self.assertIsNotNone(lowerCAmelCase__				)
							__magic_name__    :     List[str]     		=      inputs_dict["""sample"""].shape
							self.assertEqual(output.shape    ,     lowerCAmelCase__    ,     """Input and output shapes do not match"""				)







	def     __magic_name__       (       self				)							->   Optional[int]:
							__magic_name__    :     Dict     		=      """kwargs""" in inspect.signature(self.model_class.__init__				).parameters
							__magic_name__    :     Optional[int]     		=      len(self.model_class._deprecated_kwargs				) > 0

							if has_kwarg_in_model_class and not has_deprecated_kwarg:
													raise ValueError(
													    F'{self.model_class} has `**kwargs` in its __init__ method but has not defined any deprecated kwargs'
													    """ under the `_deprecated_kwargs` class attribute. Make sure to either remove `**kwargs` if there are"""
													    """ no deprecated arguments or add the deprecated argument with `_deprecated_kwargs ="""
													    """ [<deprecated_argument>]`"""				)

							if not has_kwarg_in_model_class and has_deprecated_kwarg:
													raise ValueError(
													    F'{self.model_class} doesn\'t have `**kwargs` in its __init__ method but has defined deprecated kwargs'
													    """ under the `_deprecated_kwargs` class attribute. Make sure to either add the `**kwargs` argument to"""
													    F' {self.model_class}.__init__ if there are deprecated arguments or remove the deprecated argument'
													    """ from `_deprecated_kwargs = [<deprecated_argument>]`"""				)








__magic_name__:  Tuple  	=			[
    ["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 					UpperCamelCase		( _A				):






						"""simple docstring"""







						__magic_name__    :     str     		=      set()
						for row in edge_array:
												for item in row:
																		distinct_edge.add(item[0]				)
						return list(_A				)

def 					UpperCamelCase		( _A,					_A				):






						"""simple docstring"""







						__magic_name__    :     Union[str, Any]     		=      ["""0"""] * len(_A				)
						for i, row in enumerate(_A				):
												for item in row:
																		if distinct_edge in item[0]:
																								__magic_name__    :     Optional[Any]     		=      """1"""
																								break
						return "".join(_A				)

def 					UpperCamelCase		( _A				):






						"""simple docstring"""







						__magic_name__    :     List[str]     		=      get_distinct_edge(_A				)
						__magic_name__    :     List[str]     		=      {}

						for item in distinct_edge:
												__magic_name__    :     Optional[Any]     		=      get_bitcode(_A,					_A				)
												# print('bit',bit)
												# bt=''.join(bit)
												__magic_name__    :     Union[str, Any]     		=      bit.count("""1"""				)
												__magic_name__    :     Dict     		=      [s, bit]
						# Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
						__magic_name__    :     List[Any]     		=      [
						    [k, v[0], v[1]]
						    for k, v in sorted(frequency_table.items(),					key=lambda _A				: v[1][0],					reverse=_A				)
						]
						return sorted_frequency_table

def 					UpperCamelCase		( _A				):






						"""simple docstring"""







						__magic_name__    :     str     		=      {}
						for _, item in enumerate(_A				):
												nodes.setdefault(item[2],					[]				).append(item[0]				)
						return nodes

def 					UpperCamelCase		( _A				):






						"""simple docstring"""







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

def 					UpperCamelCase		( _A				):






						"""simple docstring"""







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

def 					UpperCamelCase		( ):






						"""simple docstring"""







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

def 					UpperCamelCase		( _A,					_A,					_A,					_A				):






						"""simple docstring"""







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

def 					UpperCamelCase		( _A,					_A				):






						"""simple docstring"""







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

def 					UpperCamelCase		( _A,					_A,					_A,					_A=None				):






						"""simple docstring"""







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

def 					UpperCamelCase		( _A,					_A,					_A				):






						"""simple docstring"""







						__magic_name__    :     Union[str, Any]     		=      int(s / 100 * (len(_A				) - 1)				)
						for i in cluster[k]:
												my_dfs(_A,					tuple(cluster[k][i]				),					(["""Header"""],)				)

def 					UpperCamelCase		( _A				):






						"""simple docstring"""







						__magic_name__    :     str     		=      []
						for edges in paths:
												__magic_name__    :     List[Any]     		=      []
												for j in range(len(_A				) - 1				):
																		__magic_name__    :     Any     		=      list(edges[j]				)
																		for e in temp:
																								__magic_name__    :     Optional[Any]     		=      (e[0], e[1])
																								el.append(_A				)
												freq_sub_el.append(_A				)
						return freq_sub_el

def 					UpperCamelCase		( _A				):






						"""simple docstring"""







						for i in range(len(_A				)				):
												for j in range(len(edge_array[i]				)				):
																		__magic_name__    :     Any     		=      edge_array[i][j].split("""-"""				)
																		__magic_name__    :     Optional[int]     		=      t


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