






'''simple docstring'''
UpperCamelCase__	=     [
    ['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 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase							):


   """simple docstring"""




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




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase  ,						_UpperCamelCase							):


   """simple docstring"""




   lowercase_		:      int          =       ["0"] * len(_UpperCamelCase							)
   for i, row in enumerate(_UpperCamelCase							):
      for item in row:
         if distinct_edge in item[0]:
            lowercase_		:      List[Any]          =       "1"
            break
   return "".join(_UpperCamelCase							)




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase							):


   """simple docstring"""




   lowercase_		:      Optional[Any]          =       get_distinct_edge(_UpperCamelCase							)
   lowercase_		:      Union[str, Any]          =       {}

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




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase							):


   """simple docstring"""




   lowercase_		:      int          =       {}
   for _, item in enumerate(_UpperCamelCase							):
      nodes.setdefault(item[2]  ,						[]							).append(item[0]							)
   return nodes




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase							):


   """simple docstring"""




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




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase							):


   """simple docstring"""




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




def 						__SCREAMING_SNAKE_CASE   (					):


   """simple docstring"""




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




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase  ,						_UpperCamelCase  ,						_UpperCamelCase  ,						_UpperCamelCase							):


   """simple docstring"""




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




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase  ,						_UpperCamelCase							):


   """simple docstring"""




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




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase  ,						_UpperCamelCase  ,						_UpperCamelCase  ,						_UpperCamelCase=None							):


   """simple docstring"""




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




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase  ,						_UpperCamelCase  ,						_UpperCamelCase							):


   """simple docstring"""




   lowercase_		:      Tuple          =       int(s / 100 * (len(_UpperCamelCase							) - 1)							)
   for i in cluster[k]:
      my_dfs(_UpperCamelCase  ,						tuple(cluster[k][i]							)  ,						(["Header"],)							)




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase							):


   """simple docstring"""




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




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase							):


   """simple docstring"""




   for i in range(len(_UpperCamelCase							)							):
      for j in range(len(edge_array[i]							)							):
         lowercase_		:      List[str]          =       edge_array[i][j].split("-"							)
         lowercase_		:      int          =       t


if __name__ == "__main__":
 preprocess(edge_array)
 UpperCamelCase__	=     get_frequency_table(edge_array)
 UpperCamelCase__	=     get_nodes(frequency_table)
 UpperCamelCase__	=     get_cluster(nodes)
 UpperCamelCase__	=     get_support(cluster)
 UpperCamelCase__	=     construct_graph(cluster, nodes)
 find_freq_subgraph_given_support(60, cluster, graph)
 UpperCamelCase__	=     []
 UpperCamelCase__	=     freq_subgraphs_edge_list(paths)
 print_all()












'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


UpperCamelCase__	=     {
    'configuration_unispeech_sat': ['UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechSatConfig'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCamelCase__	=     [
     'UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'UniSpeechSatForAudioFrameClassification',
     'UniSpeechSatForCTC',
     'UniSpeechSatForPreTraining',
     'UniSpeechSatForSequenceClassification',
     'UniSpeechSatForXVector',
     'UniSpeechSatModel',
     'UniSpeechSatPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_unispeech_sat import (
      UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
      UniSpeechSatForAudioFrameClassification,
      UniSpeechSatForCTC,
      UniSpeechSatForPreTraining,
      UniSpeechSatForSequenceClassification,
      UniSpeechSatForXVector,
      UniSpeechSatModel,
      UniSpeechSatPreTrainedModel,
  )

else:
 import sys

 UpperCamelCase__	=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




