


'''simple docstring'''

import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


lowerCamelCase							:   Optional[int]  						=	logging.get_logger(__name__)

lowerCamelCase							:   List[str]  						=	{'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

lowerCamelCase							:   Tuple  						=	{
    'vocab_file': {
        'junnyu/roformer_chinese_small': 'https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt',
        'junnyu/roformer_chinese_base': 'https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt',
        'junnyu/roformer_chinese_char_small': (
            'https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt'
        ),
        'junnyu/roformer_chinese_char_base': (
            'https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt'
        ),
        'junnyu/roformer_small_discriminator': (
            'https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt'
        ),
        'junnyu/roformer_small_generator': (
            'https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt'
        ),
    }
}

lowerCamelCase							:   int  						=	{
    'junnyu/roformer_chinese_small': 1_536,
    'junnyu/roformer_chinese_base': 1_536,
    'junnyu/roformer_chinese_char_small': 512,
    'junnyu/roformer_chinese_char_base': 512,
    'junnyu/roformer_small_discriminator': 128,
    'junnyu/roformer_small_generator': 128,
}


lowerCamelCase							:   Union[str, Any]  						=	{
    'junnyu/roformer_chinese_small': {'do_lower_case': True},
    'junnyu/roformer_chinese_base': {'do_lower_case': True},
    'junnyu/roformer_chinese_char_small': {'do_lower_case': True},
    'junnyu/roformer_chinese_char_base': {'do_lower_case': True},
    'junnyu/roformer_small_discriminator': {'do_lower_case': True},
    'junnyu/roformer_small_generator': {'do_lower_case': True},
}
class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     Optional[Any]  					=							VOCAB_FILES_NAMES
      lowerCAmelCase__					:     List[str]  					=							PRETRAINED_VOCAB_FILES_MAP
      lowerCAmelCase__					:     Optional[Any]  					=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCAmelCase__					:     Tuple  					=							PRETRAINED_INIT_CONFIGURATION
      lowerCAmelCase__					:     List[str]  					=							RoFormerTokenizer



      def __init__(self    :    int   ,						UpperCamelCase    :    Dict=None   ,						UpperCamelCase    :    List[Any]=None   ,						UpperCamelCase    :    Union[str, Any]=True   ,						UpperCamelCase    :    Tuple="[UNK]"   ,						UpperCamelCase    :    Union[str, Any]="[SEP]"   ,						UpperCamelCase    :    int="[PAD]"   ,						UpperCamelCase    :    List[Any]="[CLS]"   ,						UpperCamelCase    :    Optional[int]="[MASK]"   ,						UpperCamelCase    :    List[Any]=True   ,						UpperCamelCase    :    Dict=None   ,						**UpperCamelCase    :    List[Any]   ,						):

             '''simple docstring'''







             super().__init__(
                 UpperCamelCase   ,						tokenizer_file=UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						unk_token=UpperCamelCase   ,						sep_token=UpperCamelCase   ,						pad_token=UpperCamelCase   ,						cls_token=UpperCamelCase   ,						mask_token=UpperCamelCase   ,						tokenize_chinese_chars=UpperCamelCase   ,						strip_accents=UpperCamelCase   ,						**UpperCamelCase   ,						)

             lowercase__      			= json.loads(self.backend_tokenizer.normalizer.__getstate__() )
             if (
                 pre_tok_state.get('''lowercase'''   ,						UpperCamelCase ) != do_lower_case
                 or pre_tok_state.get('''strip_accents'''   ,						UpperCamelCase ) != strip_accents
             ):
                    lowercase__      			= getattr(UpperCamelCase   ,						pre_tok_state.pop('''type''' ) )
                    lowercase__      			= do_lower_case
                    lowercase__      			= strip_accents
                    lowercase__      			= pre_tok_class(**UpperCamelCase )

             lowercase__      			= do_lower_case



      def __getstate__(self    :    Optional[int] ):

             '''simple docstring'''







             lowercase__      			= self.__dict__.copy()
             lowercase__      			= BertPreTokenizer()
             return state



      def __setstate__(self    :    int   ,						UpperCamelCase    :    Tuple ):

             '''simple docstring'''







             lowercase__      			= d
             lowercase__      			= self.__dict__['''_tokenizer'''].get_vocab()
             lowercase__      			= PreTokenizer.custom(JiebaPreTokenizer(UpperCamelCase ) )



      def       UpperCamelCase__		(self    :    Optional[int]   ,						UpperCamelCase    :    Optional[Any]   ,						UpperCamelCase    :    List[str]=None ):

             '''simple docstring'''







             lowercase__      			= [self.cls_token_id] + token_ids_a + [self.sep_token_id]

             if token_ids_a:
                    output += token_ids_a + [self.sep_token_id]

             return output



      def       UpperCamelCase__		(self    :    Dict   ,						UpperCamelCase    :    List[int]   ,						UpperCamelCase    :    Optional[List[int]] = None ):

             '''simple docstring'''







             lowercase__      			= [self.sep_token_id]
             lowercase__      			= [self.cls_token_id]
             if token_ids_a is None:
                    return len(cls + token_ids_a + sep ) * [0]
             return len(cls + token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]



      def       UpperCamelCase__		(self    :    Dict   ,						UpperCamelCase    :    str   ,						UpperCamelCase    :    Optional[str] = None ):

             '''simple docstring'''







             lowercase__      			= self._tokenizer.model.save(UpperCamelCase   ,						name=UpperCamelCase )
             return tuple(UpperCamelCase )






      def       UpperCamelCase__		(self    :    Any   ,						UpperCamelCase    :    Optional[int]   ,						UpperCamelCase    :    Union[str, Any]=None   ,						UpperCamelCase    :    Optional[Any]=None   ,						UpperCamelCase    :    Union[str, Any]=False   ,						**UpperCamelCase    :    Any   ,						):

             '''simple docstring'''







             lowercase__      			= BertPreTokenizer()
             return super().save_pretrained(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						**UpperCamelCase )








'''simple docstring'''

from __future__ import annotations

from typing import Generic, TypeVar

a_  :				List[str]						= TypeVar("""T""")





class      snake_case    (    Generic[T]			):





  """simple docstring"""




  def __init__(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  data
   lowerCamelCase_      =  self
   lowerCamelCase_      =  0





class      snake_case    (    Generic[T]			):





  """simple docstring"""




  def __init__(    self     ):







   """simple docstring"""
   # map from node name to the node object
   lowerCamelCase_      =  {}






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   # create a new set with x as its member
   lowerCamelCase_      =  DisjointSetTreeNode(UpperCamelCase     )






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   # find the set x belongs to (with path-compression)
   lowerCamelCase_      =  self.map[data]
   if elem_ref != elem_ref.parent:
    lowerCamelCase_      =  self.find_set(elem_ref.parent.data     )
   return elem_ref.parent






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase     ):







   """simple docstring"""
   # helper function for union operation
   if nodea.rank > nodea.rank:
    lowerCamelCase_      =  nodea
   else:
    lowerCamelCase_      =  nodea
    if nodea.rank == nodea.rank:
     nodea.rank += 1







  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase     ):







   """simple docstring"""
   # merge 2 disjoint sets
   self.link(self.find_set(UpperCamelCase     )			,  self.find_set(UpperCamelCase     )     )





class      snake_case    (    Generic[T]			):





  """simple docstring"""




  def __init__(    self     ):







   """simple docstring"""
   # connections: map from the node to the neighbouring nodes (with weights)
   lowerCamelCase_      =  {}






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   # add a node ONLY if its not present in the graph
   if node not in self.connections:
    lowerCamelCase_      =  {}






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase     ):







   """simple docstring"""
   # add an edge with the given weight
   self.add_node(UpperCamelCase     )
   self.add_node(UpperCamelCase     )
   lowerCamelCase_      =  weight
   lowerCamelCase_      =  weight







  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  []
   lowerCamelCase_      =  set()
   for start in self.connections:
    for end in self.connections[start]:
     if (start, end) not in seen:
      seen.add((end, start)     )
      edges.append((start, end, self.connections[start][end])     )
   edges.sort(key=lambda UpperCamelCase     : x[2]     )

   # creating the disjoint set
   lowerCamelCase_      =  DisjointSetTree[T]()
   for node in self.connections:
    disjoint_set.make_set(UpperCamelCase     )

   # MST generation
   lowerCamelCase_      =  0
   lowerCamelCase_      =  0
   lowerCamelCase_      =  GraphUndirectedWeighted[T]()
   while num_edges < len(self.connections     ) - 1:
    lowerCamelCase_ ,lowerCamelCase_ ,lowerCamelCase_      =  edges[index]
    index += 1
    lowerCamelCase_      =  disjoint_set.find_set(UpperCamelCase     )
    lowerCamelCase_      =  disjoint_set.find_set(UpperCamelCase     )
    if parent_u != parent_v:
     num_edges += 1
     graph.add_edge(UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase     )
     disjoint_set.union(UpperCamelCase			,  UpperCamelCase     )
   return graph



