

UpperCAmelCase__			:  Dict					     =     [
    ["""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   (  _A      )  ->    int:
      SCREAMING_SNAKE_CASE			:   str	  = set()
      for row in edge_array:
            for item in row:
                  distinct_edge.add(item[0]      )
      return list(_A      )






def        __lowercase   (  _A    ,     _A      )  ->    List[Any]:
      SCREAMING_SNAKE_CASE			:   int	  = ["""0"""] * len(_A      )
      for i, row in enumerate(_A      ):
            for item in row:
                  if distinct_edge in item[0]:
                        SCREAMING_SNAKE_CASE			:   Union[str, Any]	  = """1"""
                        break
      return "".join(_A      )






def        __lowercase   (  _A      )  ->    str:
      SCREAMING_SNAKE_CASE			:   Tuple	  = get_distinct_edge(_A      )
      SCREAMING_SNAKE_CASE			:   Dict	  = {}

      for item in distinct_edge:
            SCREAMING_SNAKE_CASE			:   List[Any]	  = get_bitcode(_A    ,     _A      )
            # print('bit',bit)
            # bt=''.join(bit)
            SCREAMING_SNAKE_CASE			:   List[str]	  = bit.count("""1"""      )
            SCREAMING_SNAKE_CASE			:   Any	  = [s, bit]
      # Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
      SCREAMING_SNAKE_CASE			:   Optional[int]	  = [
          [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        __lowercase   (  _A      )  ->    Union[str, Any]:
      SCREAMING_SNAKE_CASE			:   Optional[int]	  = {}
      for _, item in enumerate(_A      ):
            nodes.setdefault(item[2]    ,     []      ).append(item[0]      )
      return nodes






def        __lowercase   (  _A      )  ->    str:
      SCREAMING_SNAKE_CASE			:   List[str]	  = {}
      for key, value in nodes.items():
            SCREAMING_SNAKE_CASE			:   Optional[Any]	  = value
      return cluster






def        __lowercase   (  _A      )  ->    List[str]:
      return [i * 100 / len(_A      ) for i in cluster]






def        __lowercase   (  )  ->    None:
      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        __lowercase   (  _A    ,     _A    ,     _A    ,     _A      )  ->    Dict:
      for i in cluster[ca]:
            SCREAMING_SNAKE_CASE			:   Optional[Any]	  = 0
            SCREAMING_SNAKE_CASE			:   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:
                                    SCREAMING_SNAKE_CASE			:   List[str]	  = [nodes[j]]
                              count += 1
                  if count == 0:
                        SCREAMING_SNAKE_CASE			:   Tuple	  = ca + 1
                  else:
                        break






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






def        __lowercase   (  _A    ,     _A    ,     _A    ,     _A=None      )  ->    List[Any]:
      SCREAMING_SNAKE_CASE			:   Tuple	  = (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        __lowercase   (  _A    ,     _A    ,     _A      )  ->    Any:
      SCREAMING_SNAKE_CASE			:   List[str]	  = int(s / 100 * (len(_A      ) - 1)      )
      for i in cluster[k]:
            my_dfs(_A    ,     tuple(cluster[k][i]      )    ,     (["""Header"""],)      )






def        __lowercase   (  _A      )  ->    List[str]:
      SCREAMING_SNAKE_CASE			:   Union[str, Any]	  = []
      for edges in paths:
            SCREAMING_SNAKE_CASE			:   str	  = []
            for j in range(len(_A      ) - 1      ):
                  SCREAMING_SNAKE_CASE			:   Dict	  = list(edges[j]      )
                  for e in temp:
                        SCREAMING_SNAKE_CASE			:   List[str]	  = (e[0], e[1])
                        el.append(_A      )
            freq_sub_el.append(_A      )
      return freq_sub_el






def        __lowercase   (  _A      )  ->    Dict:
      for i in range(len(_A      )      ):
            for j in range(len(edge_array[i]      )      ):
                  SCREAMING_SNAKE_CASE			:   Dict	  = edge_array[i][j].split("""-"""      )
                  SCREAMING_SNAKE_CASE			:   Union[str, Any]	  = t


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







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase__			:  Optional[Any]					     =     {
    """configuration_musicgen""": [
        """MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """MusicgenConfig""",
        """MusicgenDecoderConfig""",
    ],
    """processing_musicgen""": ["""MusicgenProcessor"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__			:  Any					     =     [
      """MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """MusicgenForConditionalGeneration""",
      """MusicgenForCausalLM""",
      """MusicgenModel""",
      """MusicgenPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_musicgen import (
      MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP,
      MusicgenConfig,
      MusicgenDecoderConfig,
  )
  from .processing_musicgen import MusicgenProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_musicgen import (
        MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
        MusicgenForCausalLM,
        MusicgenForConditionalGeneration,
        MusicgenModel,
        MusicgenPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase__			:  Dict					     =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




