






"""simple docstring"""




_snake_case					   =     [
    ['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__  (  UpperCamelCase__       ):



  '''simple docstring'''
  _a						: Union[str, Any]    =			set()
  for row in edge_array:
    for item in row:
      distinct_edge.add(item[0]       )
  return list(UpperCamelCase__       )

def     lowerCAmelCase__  (  UpperCamelCase__  ,     UpperCamelCase__       ):



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

def     lowerCAmelCase__  (  UpperCamelCase__       ):



  '''simple docstring'''
  _a						: Optional[Any]    =			get_distinct_edge(UpperCamelCase__       )
  _a						: str    =			{}

  for item in distinct_edge:
    _a						: Optional[int]    =			get_bitcode(UpperCamelCase__  ,     UpperCamelCase__       )
    # print('bit',bit)
    # bt=''.join(bit)
    _a						: Optional[int]    =			bit.count("""1"""       )
    _a						: Union[str, Any]    =			[s, bit]
  # Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
  _a						: Tuple    =			[
      [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     lowerCAmelCase__  (  UpperCamelCase__       ):



  '''simple docstring'''
  _a						: Dict    =			{}
  for _, item in enumerate(UpperCamelCase__       ):
    nodes.setdefault(item[2]  ,     []       ).append(item[0]       )
  return nodes

def     lowerCAmelCase__  (  UpperCamelCase__       ):



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

def     lowerCAmelCase__  (  UpperCamelCase__       ):



  '''simple docstring'''
  return [i * 1_0_0 / len(UpperCamelCase__       ) for i in cluster]

def     lowerCAmelCase__  (  ):



  '''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     lowerCAmelCase__  (  UpperCamelCase__  ,     UpperCamelCase__  ,     UpperCamelCase__  ,     UpperCamelCase__       ):



  '''simple docstring'''
  for i in cluster[ca]:
    _a						: Tuple    =			0
    _a						: 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:
            _a						: Dict    =			[nodes[j]]
          count += 1
      if count == 0:
        _a						: List[str]    =			ca + 1
      else:
        break

def     lowerCAmelCase__  (  UpperCamelCase__  ,     UpperCamelCase__       ):



  '''simple docstring'''
  _a						: Tuple    =			cluster[max(cluster.keys()       )]
  _a						: Any    =			"""Header"""
  _a						: Union[str, Any]    =			{}
  for i in x:
    if (["Header"],) in graph:
      graph[(["Header"],)].append(x[i]       )
    else:
      _a						: Dict    =			[x[i]]
  for i in x:
    _a						: List[Any]    =			[["""Header"""]]
  _a						: Any    =			1
  while i < max(UpperCamelCase__       ) - 1:
    create_edge(UpperCamelCase__  ,     UpperCamelCase__  ,     UpperCamelCase__  ,     UpperCamelCase__       )
    _a						: Any    =			i + 1
  return graph

def     lowerCAmelCase__  (  UpperCamelCase__  ,     UpperCamelCase__  ,     UpperCamelCase__  ,     UpperCamelCase__=None       ):



  '''simple docstring'''
  _a						: Optional[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     lowerCAmelCase__  (  UpperCamelCase__  ,     UpperCamelCase__  ,     UpperCamelCase__       ):



  '''simple docstring'''
  _a						: Any    =			int(s / 1_0_0 * (len(UpperCamelCase__       ) - 1)       )
  for i in cluster[k]:
    my_dfs(UpperCamelCase__  ,     tuple(cluster[k][i]       )  ,     (["""Header"""],)       )

def     lowerCAmelCase__  (  UpperCamelCase__       ):



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

def     lowerCAmelCase__  (  UpperCamelCase__       ):



  '''simple docstring'''
  for i in range(len(UpperCamelCase__       )       ):
    for j in range(len(edge_array[i]       )       ):
      _a						: Tuple    =			edge_array[i][j].split("""-"""       )
      _a						: Optional[int]    =			t


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









"""simple docstring"""




import os
from shutil import copyfile
from typing import TYPE_CHECKING, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
from ...utils.versions import require_version


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation

require_version('tokenizers>=0.13.3')

if is_sentencepiece_available():
 from .tokenization_llama import LlamaTokenizer
else:
 _snake_case					   =     None

_snake_case					   =     logging.get_logger(__name__)
_snake_case					   =     {'vocab_file': 'tokenizer.model', 'tokenizer_file': 'tokenizer.json'}

_snake_case   ,				_snake_case					   =     '[INST]', '[/INST]'
_snake_case   ,				_snake_case					   =     '<<SYS>>\n', '\n<</SYS>>\n\n'

# fmt: off
_snake_case					   =     'You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\\nanswers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\\nthat your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not\\ncorrect. If you don\'t know the answer to a question, please don\'t share false information.'






class  UpperCamelCase    (			snake_case_   ):
 UpperCamelCase      : Any    =      VOCAB_FILES_NAMES
 UpperCamelCase      : Tuple    =      LlamaTokenizer
 UpperCamelCase      : Union[str, Any]    =      '''left'''
 UpperCamelCase      : str    =      ['''input_ids''', '''attention_mask''']


 def __init__(  self	:		Union[str, Any]							,		UpperCAmelCase__	:		Optional[int]=None							,		UpperCAmelCase__	:		Dict=None							,		UpperCAmelCase__	:		Optional[int]=False							,		UpperCAmelCase__	:		Optional[Any]="<unk>"							,		UpperCAmelCase__	:		str="<s>"							,		UpperCAmelCase__	:		List[Any]="</s>"							,		UpperCAmelCase__	:		Tuple=True							,		UpperCAmelCase__	:		int=False							,		**UpperCAmelCase__	:		Tuple							,		)      -> Dict:
   super().__init__(
       vocab_file=UpperCAmelCase__							,		tokenizer_file=UpperCAmelCase__							,		clean_up_tokenization_spaces=UpperCAmelCase__							,		unk_token=UpperCAmelCase__							,		bos_token=UpperCAmelCase__							,		eos_token=UpperCAmelCase__							,		**UpperCAmelCase__							,		)
   _a						: List[str]    =			add_bos_token
   _a						: Union[str, Any]    =			add_eos_token
   self.update_post_processor()

   _a						: List[str]    =			vocab_file
   _a						: Union[str, Any]    =			False if not self.vocab_file else True


 def _lowercase			(  self	:		List[str]							)      -> int:
   _a						: Dict    =			self.bos_token
   _a						: Union[str, Any]    =			self.bos_token_id

   _a						: int    =			self.eos_token
   _a						: str    =			self.eos_token_id

   _a						: Optional[Any]    =			f"""{(bos+':0 ') * self.add_bos_token}$A:0{(' '+eos+':0') * self.add_eos_token}"""
   _a						: str    =			f"""{single}{(' '+bos+':1') * self.add_bos_token} $B:1{(' '+eos+':1') * self.add_eos_token}"""

   _a						: Optional[int]    =			[]
   if self.add_bos_token:
     special_tokens.append((bos, bos_token_id)							)
   if self.add_eos_token:
     special_tokens.append((eos, eos_token_id)							)
   _a						: str    =			processors.TemplateProcessing(
       single=UpperCAmelCase__							,		pair=UpperCAmelCase__							,		special_tokens=UpperCAmelCase__							)


 @property
 def _lowercase			(  self	:		Optional[int]							)      -> Optional[Any]:
   return self._add_eos_token


 @property
 def _lowercase			(  self	:		Dict							)      -> str:
   return self._add_bos_token


 @add_eos_token.setter
 def _lowercase			(  self	:		Any							,		UpperCAmelCase__	:		int							)      -> List[str]:
   _a						: Any    =			value
   self.update_post_processor()


 @add_bos_token.setter
 def _lowercase			(  self	:		Any							,		UpperCAmelCase__	:		int							)      -> List[str]:
   _a						: Optional[Any]    =			value
   self.update_post_processor()


 def _lowercase			(  self	:		Dict							,		UpperCAmelCase__	:		str							,		UpperCAmelCase__	:		Optional[str] = None							)      -> Tuple[str]:
   if not self.can_save_slow_tokenizer:
     raise ValueError(
         """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
         """tokenizer."""							)

   if not os.path.isdir(UpperCAmelCase__							):
     logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
     return
   _a						: str    =			os.path.join(
       UpperCAmelCase__							,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)

   if os.path.abspath(self.vocab_file							) != os.path.abspath(UpperCAmelCase__							):
     copyfile(self.vocab_file							,		UpperCAmelCase__							)

   return (out_vocab_file,)







 def _lowercase			(  self	:		Tuple							,		UpperCAmelCase__	:		"Conversation"							)      -> Optional[Any]:
   _a						: str    =			list(conversation.iter_texts()							)
   if not all([is_user for is_user, msg in dialogue[::2]]							) or not all(
       [not is_user for is_user, msg in dialogue[1::2]]							):
     raise ValueError(
         """The model only supports 'user' and 'assistant' roles, starting with user and alternating (u/a/u/a/u...)"""							)

   _a						: Tuple    =			[]
   if len(conversation.past_user_inputs							) > 0:
     if not conversation.past_user_inputs[0].startswith(UpperCAmelCase__							) or E_SYS not in conversation.past_user_inputs[0]:
       _a						: Union[str, Any]    =			(
           B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
       )
   elif not dialogue[0][1].startswith(UpperCAmelCase__							) or E_SYS not in dialogue[0][1]:
     _a						: str    =			(dialogue[0][0], B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + dialogue[0][1])

   dialog_tokens += sum(
       [
           [self.bos_token_id]
           + self.encode(
               f"""{B_INST} {(prompt[1]).strip()} {E_INST} {(answer[1]).strip()} """							,		add_special_tokens=UpperCAmelCase__							)
           + [self.eos_token_id]
           for prompt, answer in zip(dialogue[::2]							,		dialogue[1::2]							)
       ]							,		[]							,		)
   if not (dialogue[-1][0]):
     raise ValueError(f"""Last message must be from user, got {dialogue[-1]['role']}"""							)
   dialog_tokens += [self.bos_token_id] + self.encode(
       f"""{B_INST} {(dialogue[-1][1]).strip()} {E_INST}"""							,		add_special_tokens=UpperCAmelCase__							)
   return dialog_tokens

