




import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing





class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE   ):


 '''simple docstring'''







 def __init__(				self    :						Optional[int]							,							_lowerCAmelCase    :						str = "▁"							,							_lowerCAmelCase    :						bool = True							,							_lowerCAmelCase    :						Union[str, AddedToken] = "<unk>"							,							_lowerCAmelCase    :						Union[str, AddedToken] = "</s>"							,							_lowerCAmelCase    :						Union[str, AddedToken] = "<pad>"							,							):
       SCREAMING_SNAKE_CASE_      		=     {
           'pad': {'id': 0, 'token': pad_token},
           'eos': {'id': 1, 'token': eos_token},
           'unk': {'id': 2, 'token': unk_token},
       }

       SCREAMING_SNAKE_CASE_      		=     [None] * len(self.special_tokens		)
       for token_dict in self.special_tokens.values():
             SCREAMING_SNAKE_CASE_      		=     token_dict['token']

       SCREAMING_SNAKE_CASE_      		=     Tokenizer(Unigram()		)

       SCREAMING_SNAKE_CASE_      		=     normalizers.Sequence(
           [
               normalizers.Nmt(),
               normalizers.NFKC(),
               normalizers.Replace(Regex(' {2,}'		)							,							' '		),
               normalizers.Lowercase(),
           ]		)
       SCREAMING_SNAKE_CASE_      		=     pre_tokenizers.Sequence(
           [
               pre_tokenizers.Metaspace(replacement=_lowerCAmelCase							,							add_prefix_space=_lowerCAmelCase		),
               pre_tokenizers.Digits(individual_digits=_lowerCAmelCase		),
               pre_tokenizers.Punctuation(),
           ]		)
       SCREAMING_SNAKE_CASE_      		=     decoders.Metaspace(replacement=_lowerCAmelCase							,							add_prefix_space=_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     TemplateProcessing(
           single=F"$A {self.special_tokens['eos']['token']}"							,							special_tokens=[(self.special_tokens['eos']['token'], self.special_tokens['eos']['id'])]							,							)

       SCREAMING_SNAKE_CASE_      		=     {
           'model': 'SentencePieceUnigram',
           'replacement': replacement,
           'add_prefix_space': add_prefix_space,
       }

       super().__init__(_lowerCAmelCase							,							_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Tuple							,							_lowerCAmelCase    :						Union[str, List[str]]							,							_lowerCAmelCase    :						int = 8_000							,							_lowerCAmelCase    :						bool = True							,							):
       SCREAMING_SNAKE_CASE_      		=     trainers.UnigramTrainer(
           vocab_size=_lowerCAmelCase							,							special_tokens=self.special_tokens_list							,							show_progress=_lowerCAmelCase							,							)

       if isinstance(_lowerCAmelCase							,							_lowerCAmelCase		):
             SCREAMING_SNAKE_CASE_      		=     [files]
       self._tokenizer.train(_lowerCAmelCase							,							trainer=_lowerCAmelCase		)

       self.add_unk_id()



 def  lowerCAmelCase_    (				self    :						Union[str, Any]							,							_lowerCAmelCase    :						Union[Iterator[str], Iterator[Iterator[str]]]							,							_lowerCAmelCase    :						int = 8_000							,							_lowerCAmelCase    :						bool = True							,							):
       SCREAMING_SNAKE_CASE_      		=     trainers.UnigramTrainer(
           vocab_size=_lowerCAmelCase							,							special_tokens=self.special_tokens_list							,							show_progress=_lowerCAmelCase							,							)

       self._tokenizer.train_from_iterator(_lowerCAmelCase							,							trainer=_lowerCAmelCase		)

       self.add_unk_id()




 def  lowerCAmelCase_    (				self    :						List[Any]		):
       SCREAMING_SNAKE_CASE_      		=     json.loads(self._tokenizer.to_str()		)

       SCREAMING_SNAKE_CASE_      		=     self.special_tokens['unk']['id']

       SCREAMING_SNAKE_CASE_      		=     Tokenizer.from_str(json.dumps(_lowerCAmelCase		)		)







# 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

_SCREAMING_SNAKE_CASE   =  TypeVar("T")






class 					SCREAMING_SNAKE_CASE_  (       Generic[T] ):
       """simple docstring"""


       def __init__(				self	:List[Any],      snake_case	:bool = True):



          """simple docstring"""

          _lowercase              ={}  # dictionary of lists
          _lowercase              =directed





       def 				UpperCamelCase__						(				self	:Optional[Any],      snake_case	:T,      snake_case	:T):



          """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)
                _lowercase              =[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)
                _lowercase              =[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:
                _lowercase              =[destination_vertex]
                _lowercase              =[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)
                _lowercase              =[]
             # 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:
                _lowercase              =[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:
                _lowercase              =[destination_vertex]
                _lowercase              =[]

          return self





       def __repr__(				self	:Optional[int]):



          """simple docstring"""

          return pformat(self.adj_list)


