





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer


a__      :     int         =		logging.get_logger(__name__)

a__      :     int         =		{'vocab_file': 'vocab.txt'}

a__      :     Optional[Any]         =		{
    'vocab_file': {
        'YituTech/conv-bert-base': 'https://huggingface.co/YituTech/conv-bert-base/resolve/main/vocab.txt',
        'YituTech/conv-bert-medium-small': (
            'https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/vocab.txt'
        ),
        'YituTech/conv-bert-small': 'https://huggingface.co/YituTech/conv-bert-small/resolve/main/vocab.txt',
    }
}

a__      :     Optional[Any]         =		{
    'YituTech/conv-bert-base': 512,
    'YituTech/conv-bert-medium-small': 512,
    'YituTech/conv-bert-small': 512,
}


a__      :     Dict         =		{
    'YituTech/conv-bert-base': {'do_lower_case': True},
    'YituTech/conv-bert-medium-small': {'do_lower_case': True},
    'YituTech/conv-bert-small': {'do_lower_case': True},
}





class UpperCAmelCase_				( _SCREAMING_SNAKE_CASE ):
  __lowerCAmelCase   :						Union[str, Any]							=   VOCAB_FILES_NAMES
  __lowerCAmelCase   :						Dict							=   PRETRAINED_VOCAB_FILES_MAP
  __lowerCAmelCase   :						str							=   PRETRAINED_INIT_CONFIGURATION
  __lowerCAmelCase   :						Any							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __lowerCAmelCase   :						List[Any]							=   ConvBertTokenizer


  def __init__(							self ,__snake_case=None ,__snake_case=None ,__snake_case=True ,__snake_case="[UNK]" ,__snake_case="[SEP]" ,__snake_case="[PAD]" ,__snake_case="[CLS]" ,__snake_case="[MASK]" ,__snake_case=True ,__snake_case=None ,**__snake_case ,):



       """simple docstring"""





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

       A_          =       json.loads(self.backend_tokenizer.normalizer.__getstate__() )
       if (
           normalizer_state.get('''lowercase''' ,__snake_case ) != do_lower_case
           or normalizer_state.get('''strip_accents''' ,__snake_case ) != strip_accents
           or normalizer_state.get('''handle_chinese_chars''' ,__snake_case ) != tokenize_chinese_chars
       ):
            A_          =       getattr(__snake_case ,normalizer_state.pop('''type''' ) )
            A_          =       do_lower_case
            A_          =       strip_accents
            A_          =       tokenize_chinese_chars
            A_          =       normalizer_class(**__snake_case )

       A_          =       do_lower_case


  def 						__UpperCAmelCase     (							self ,__snake_case ,__snake_case=None ):



       """simple docstring"""





       A_          =       [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 ,__snake_case ,__snake_case = None ):



       """simple docstring"""





       A_          =       [self.sep_token_id]
       A_          =       [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 ,__snake_case ,__snake_case = None ):



       """simple docstring"""





       A_          =       self._tokenizer.model.save(__snake_case ,name=__snake_case )
       return tuple(__snake_case )










# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

a__      :     Optional[int]         =		TypeVar('T')





class UpperCAmelCase_				( Generic[T] ):


  def __init__(							self ,__snake_case = True ):



       """simple docstring"""





       A_          =       {}  # dictionary of lists
       A_          =       directed


  def 						__UpperCAmelCase     (							self ,__snake_case ,__snake_case ):



       """simple docstring"""





       if not self.directed:  # For undirected graphs
            # if both source vertex and destination vertex are both present in the
            # adjacency list, add destination vertex to source vertex list of adjacent
            # vertices and add source vertex to destination vertex list of adjacent
            # vertices.
            if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                 self.adj_list[source_vertex].append(__snake_case )
                 self.adj_list[destination_vertex].append(__snake_case )
            # if only source vertex is present in adjacency list, add destination vertex
            # to source vertex list of adjacent vertices, then create a new vertex with
            # destination vertex as key and assign a list containing the source vertex
            # as it's first adjacent vertex.
            elif source_vertex in self.adj_list:
                 self.adj_list[source_vertex].append(__snake_case )
                 A_          =       [source_vertex]
            # if only destination vertex is present in adjacency list, add source vertex
            # to destination vertex list of adjacent vertices, then create a new vertex
            # with source vertex as key and assign a list containing the source vertex
            # as it's first adjacent vertex.
            elif destination_vertex in self.adj_list:
                 self.adj_list[destination_vertex].append(__snake_case )
                 A_          =       [destination_vertex]
            # if both source vertex and destination vertex are not present in adjacency
            # list, create a new vertex with source vertex as key and assign a list
            # containing the destination vertex as it's first adjacent vertex also
            # create a new vertex with destination vertex as key and assign a list
            # containing the source vertex as it's first adjacent vertex.
            else:
                 A_          =       [destination_vertex]
                 A_          =       [source_vertex]
       else:  # For directed graphs
            # if both source vertex and destination vertex are present in adjacency
            # list, add destination vertex to source vertex list of adjacent vertices.
            if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                 self.adj_list[source_vertex].append(__snake_case )
            # if only source vertex is present in adjacency list, add destination
            # vertex to source vertex list of adjacent vertices and create a new vertex
            # with destination vertex as key, which has no adjacent vertex
            elif source_vertex in self.adj_list:
                 self.adj_list[source_vertex].append(__snake_case )
                 A_          =       []
            # if only destination vertex is present in adjacency list, create a new
            # vertex with source vertex as key and assign a list containing destination
            # vertex as first adjacent vertex
            elif destination_vertex in self.adj_list:
                 A_          =       [destination_vertex]
            # if both source vertex and destination vertex are not present in adjacency
            # list, create a new vertex with source vertex as key and a list containing
            # destination vertex as it's first adjacent vertex. Then create a new vertex
            # with destination vertex as key, which has no adjacent vertex
            else:
                 A_          =       [destination_vertex]
                 A_          =       []

       return self




  def __repr__(							self ):



       """simple docstring"""





       return pformat(self.adj_list )



