




'''simple docstring'''



UpperCAmelCase_				:     Optional[Any]     			=						[
    ['''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       (_lowerCamelCase							:   Tuple		)->      List[Any]:




     '''simple docstring'''





     __snake_case			    =     set()
     for row in edge_array:
          for item in row:
               distinct_edge.add(item[0]		)
     return list(_lowerCamelCase		)







def 	_UpperCamelCase       (_lowerCamelCase							:   Tuple      ,		_lowerCamelCase							:   Optional[Any]		)->      int:




     '''simple docstring'''





     __snake_case			    =     ['''0'''] * len(_lowerCamelCase		)
     for i, row in enumerate(_lowerCamelCase		):
          for item in row:
               if distinct_edge in item[0]:
                    __snake_case			    =     '''1'''
                    break
     return "".join(_lowerCamelCase		)







def 	_UpperCamelCase       (_lowerCamelCase							:   Optional[int]		)->      Union[str, Any]:




     '''simple docstring'''





     __snake_case			    =     get_distinct_edge(_lowerCamelCase		)
     __snake_case			    =     {}

     for item in distinct_edge:
          __snake_case			    =     get_bitcode(_lowerCamelCase      ,		_lowerCamelCase		)
          # print('bit',bit)
          # bt=''.join(bit)
          __snake_case			    =     bit.count('''1'''		)
          __snake_case			    =     [s, bit]
     # Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
     __snake_case			    =     [
         [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 	_UpperCamelCase       (_lowerCamelCase							:   Tuple		)->      Optional[int]:




     '''simple docstring'''





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







def 	_UpperCamelCase       (_lowerCamelCase							:   Dict		)->      Dict:




     '''simple docstring'''





     __snake_case			    =     {}
     for key, value in nodes.items():
          __snake_case			    =     value
     return cluster







def 	_UpperCamelCase       (_lowerCamelCase							:   List[Any]		)->      Optional[int]:




     '''simple docstring'''





     return [i * 1_00 / len(_lowerCamelCase		) for i in cluster]







def 	_UpperCamelCase       ()->      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 	_UpperCamelCase       (_lowerCamelCase							:   str      ,		_lowerCamelCase							:   Tuple      ,		_lowerCamelCase							:   List[str]      ,		_lowerCamelCase							:   List[str]		)->      Dict:




     '''simple docstring'''





     for i in cluster[ca]:
          __snake_case			    =     0
          __snake_case			    =     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:
                              __snake_case			    =     [nodes[j]]
                         count += 1
               if count == 0:
                    __snake_case			    =     ca + 1
               else:
                    break







def 	_UpperCamelCase       (_lowerCamelCase							:   List[str]      ,		_lowerCamelCase							:   List[str]		)->      Tuple:




     '''simple docstring'''





     __snake_case			    =     cluster[max(cluster.keys()		)]
     __snake_case			    =     '''Header'''
     __snake_case			    =     {}
     for i in x:
          if (["Header"],) in graph:
               graph[(["Header"],)].append(x[i]		)
          else:
               __snake_case			    =     [x[i]]
     for i in x:
          __snake_case			    =     [['''Header''']]
     __snake_case			    =     1
     while i < max(_lowerCamelCase		) - 1:
          create_edge(_lowerCamelCase      ,		_lowerCamelCase      ,		_lowerCamelCase      ,		_lowerCamelCase		)
          __snake_case			    =     i + 1
     return graph







def 	_UpperCamelCase       (_lowerCamelCase							:   Union[str, Any]      ,		_lowerCamelCase							:   Optional[Any]      ,		_lowerCamelCase							:   Tuple      ,		_lowerCamelCase							:   Union[str, Any]=None		)->      Any:




     '''simple docstring'''





     __snake_case			    =     (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 	_UpperCamelCase       (_lowerCamelCase							:   int      ,		_lowerCamelCase							:   List[str]      ,		_lowerCamelCase							:   List[Any]		)->      Tuple:




     '''simple docstring'''





     __snake_case			    =     int(s / 1_00 * (len(_lowerCamelCase		) - 1)		)
     for i in cluster[k]:
          my_dfs(_lowerCamelCase      ,		tuple(cluster[k][i]		)      ,		(['''Header'''],)		)







def 	_UpperCamelCase       (_lowerCamelCase							:   Optional[int]		)->      str:




     '''simple docstring'''





     __snake_case			    =     []
     for edges in paths:
          __snake_case			    =     []
          for j in range(len(_lowerCamelCase		) - 1		):
               __snake_case			    =     list(edges[j]		)
               for e in temp:
                    __snake_case			    =     (e[0], e[1])
                    el.append(_lowerCamelCase		)
          freq_sub_el.append(_lowerCamelCase		)
     return freq_sub_el







def 	_UpperCamelCase       (_lowerCamelCase							:   int		)->      int:




     '''simple docstring'''





     for i in range(len(_lowerCamelCase		)		):
          for j in range(len(edge_array[i]		)		):
               __snake_case			    =     edge_array[i][j].split('''-'''		)
               __snake_case			    =     t


if __name__ == "__main__":
     preprocess(edge_array)
     UpperCAmelCase_				:     Union[str, Any]     			=						get_frequency_table(edge_array)
     UpperCAmelCase_				:     Tuple     			=						get_nodes(frequency_table)
     UpperCAmelCase_				:     List[Any]     			=						get_cluster(nodes)
     UpperCAmelCase_				:     List[str]     			=						get_support(cluster)
     UpperCAmelCase_				:     int     			=						construct_graph(cluster, nodes)
     find_freq_subgraph_given_support(6_0, cluster, graph)
     UpperCAmelCase_				:     list     			=						[]
     UpperCAmelCase_				:     List[Any]     			=						freq_subgraphs_edge_list(paths)
     print_all()












'''simple docstring'''



import os

from packaging import version

from .. import __version__
from .accelerate_utils import apply_forward_hook
from .constants import (
    CONFIG_NAME,
    DEPRECATED_REVISION_ARGS,
    DIFFUSERS_CACHE,
    DIFFUSERS_DYNAMIC_MODULE_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    ONNX_EXTERNAL_WEIGHTS_NAME,
    ONNX_WEIGHTS_NAME,
    SAFETENSORS_WEIGHTS_NAME,
    TEXT_ENCODER_ATTN_MODULE,
    WEIGHTS_NAME,
)
from .deprecation_utils import deprecate
from .doc_utils import replace_example_docstring
from .dynamic_modules_utils import get_class_from_dynamic_module
from .hub_utils import (
    HF_HUB_OFFLINE,
    _add_variant,
    _get_model_file,
    extract_commit_hash,
    http_user_agent,
)
from .import_utils import (
    BACKENDS_MAPPING,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    DummyObject,
    OptionalDependencyNotAvailable,
    is_accelerate_available,
    is_accelerate_version,
    is_bsa_available,
    is_flax_available,
    is_ftfy_available,
    is_inflect_available,
    is_invisible_watermark_available,
    is_k_diffusion_available,
    is_k_diffusion_version,
    is_librosa_available,
    is_note_seq_available,
    is_omegaconf_available,
    is_onnx_available,
    is_safetensors_available,
    is_scipy_available,
    is_tensorboard_available,
    is_tf_available,
    is_torch_available,
    is_torch_version,
    is_torchsde_available,
    is_transformers_available,
    is_transformers_version,
    is_unidecode_available,
    is_wandb_available,
    is_xformers_available,
    requires_backends,
)
from .logging import get_logger
from .outputs import BaseOutput
from .pil_utils import PIL_INTERPOLATION, numpy_to_pil, pt_to_pil
from .torch_utils import is_compiled_module, randn_tensor


if is_torch_available():
     from .testing_utils import (
         floats_tensor,
         load_hf_numpy,
         load_image,
         load_numpy,
         load_pt,
         nightly,
         parse_flag_from_env,
         print_tensor_test,
         require_torch_a,
         require_torch_gpu,
         skip_mps,
         slow,
         torch_all_close,
         torch_device,
     )
     from .torch_utils import maybe_allow_in_graph

from .testing_utils import export_to_gif, export_to_video


UpperCAmelCase_				:     int     			=						get_logger(__name__)







def 	_UpperCamelCase       (_lowerCamelCase							:   Union[str, Any]		)->      Tuple:




     '''simple docstring'''





     if version.parse(_lowerCamelCase		) < version.parse(_lowerCamelCase		):
          if "dev" in min_version:
               __snake_case			    =     (
                   '''This example requires a source install from HuggingFace diffusers (see '''
                   '''`https://huggingface.co/docs/diffusers/installation#install-from-source`),'''
               )
          else:
               __snake_case			    =     f'''This example requires a minimum version of {min_version},'''
          error_message += f''' but the version found is {__version__}.\n'''
          raise ImportError(_lowerCamelCase		)






