
"""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      lowerCamelCase_     (						lowerCamelCase_			)  ->      Dict:


					'''simple docstring'''
					__a:    List[str]		     =       set()
					for row in edge_array:
										for item in row:
															distinct_edge.add(item[0]			)
					return list(lowerCamelCase_			)


def      lowerCamelCase_     (						lowerCamelCase_						,					lowerCamelCase_			)  ->      int:


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


def      lowerCamelCase_     (						lowerCamelCase_			)  ->      List[str]:


					'''simple docstring'''
					__a:    List[str]		     =       get_distinct_edge(lowerCamelCase_			)
					__a:    List[Any]		     =       {}

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


def      lowerCamelCase_     (						lowerCamelCase_			)  ->      Any:


					'''simple docstring'''
					__a:    Optional[int]		     =       {}
					for _, item in enumerate(lowerCamelCase_			):
										nodes.setdefault(item[2]						,					[]			).append(item[0]			)
					return nodes


def      lowerCamelCase_     (						lowerCamelCase_			)  ->      Dict:


					'''simple docstring'''
					__a:    Optional[Any]		     =       {}
					for key, value in nodes.items():
										__a:    int		     =       value
					return cluster


def      lowerCamelCase_     (						lowerCamelCase_			)  ->      Union[str, Any]:


					'''simple docstring'''
					return [i * 1_00 / len(lowerCamelCase_			) for i in cluster]


def      lowerCamelCase_     (						)  ->      None:


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


def      lowerCamelCase_     (						lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			)  ->      List[str]:


					'''simple docstring'''
					for i in cluster[ca]:
										__a:    Any		     =       0
										__a:    Dict		     =       ca + 1
										while ca < max(cluster.keys()			):
															for j in cluster[ca]:
																				if int(lowerCamelCase_						,					2			) & int(lowerCamelCase_						,					2			) == int(lowerCamelCase_						,					2			):
																									if tuple(nodes[i]			) in graph:
																														graph[tuple(nodes[i]			)].append(nodes[j]			)
																									else:
																														__a:    List[str]		     =       [nodes[j]]
																									count += 1
															if count == 0:
																				__a:    Any		     =       ca + 1
															else:
																				break


def      lowerCamelCase_     (						lowerCamelCase_						,					lowerCamelCase_			)  ->      str:


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


def      lowerCamelCase_     (						lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_=None			)  ->      Any:


					'''simple docstring'''
					__a:    Optional[Any]		     =       (path or []) + [start]
					if start == end:
										paths.append(lowerCamelCase_			)
					for node in graph[start]:
										if tuple(lowerCamelCase_			) not in path:
															my_dfs(lowerCamelCase_						,					tuple(lowerCamelCase_			)						,					lowerCamelCase_						,					lowerCamelCase_			)


def      lowerCamelCase_     (						lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			)  ->      Optional[Any]:


					'''simple docstring'''
					__a:    Optional[int]		     =       int(s / 1_00 * (len(lowerCamelCase_			) - 1)			)
					for i in cluster[k]:
										my_dfs(lowerCamelCase_						,					tuple(cluster[k][i]			)						,					(["""Header"""],)			)


def      lowerCamelCase_     (						lowerCamelCase_			)  ->      Optional[int]:


					'''simple docstring'''
					__a:    List[str]		     =       []
					for edges in paths:
										__a:    Optional[int]		     =       []
										for j in range(len(lowerCamelCase_			) - 1			):
															__a:    List[str]		     =       list(edges[j]			)
															for e in temp:
																				__a:    Union[str, Any]		     =       (e[0], e[1])
																				el.append(lowerCamelCase_			)
										freq_sub_el.append(lowerCamelCase_			)
					return freq_sub_el


def      lowerCamelCase_     (						lowerCamelCase_			)  ->      Optional[Any]:


					'''simple docstring'''
					for i in range(len(lowerCamelCase_			)			):
										for j in range(len(edge_array[i]			)			):
															__a:    Optional[Any]		     =       edge_array[i][j].split("""-"""			)
															__a:    str		     =       t


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


"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowercase		:    Tuple			=       {
    'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
    'tokenization_codegen': ['CodeGenTokenizer'],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    int			=       ['CodeGenTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Optional[int]			=       [
			    'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'CodeGenForCausalLM',
			    'CodeGenModel',
			    'CodeGenPreTrainedModel',
			]

if TYPE_CHECKING:
			from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
			from .tokenization_codegen import CodeGenTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_codegen_fast import CodeGenTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_codegen import (
						    CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CodeGenForCausalLM,
						    CodeGenModel,
						    CodeGenPreTrainedModel,
						)

else:
			import sys

			lowercase		:    Optional[Any]			=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
