



"""simple docstring"""
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       SCREAMING_SNAKE_CASE__       (							lowercase__      ):

    def __init__( self	: List[Any]       ,     lowerCAmelCase_	: Dict = "▁"       ,     lowerCAmelCase_	: Optional[Any] = True       ,     lowerCAmelCase_	: Optional[int] = "<unk>"       ,     lowerCAmelCase_	: Tuple = "</s>"       ,     lowerCAmelCase_	: List[Any] = "<pad>"       ,     ):







      """simple docstring"""







      lowercase_	    =       {
          "pad": {"id": 0, "token": pad_token},
          "eos": {"id": 1, "token": eos_token},
          "unk": {"id": 2, "token": unk_token},
      }

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

      lowercase_	    =       Tokenizer(Unigram())

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

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

      lowercase_	    =       {
          "model": "SentencePieceUnigram",
          "replacement": replacement,
          "add_prefix_space": add_prefix_space,
      }

      super().__init__(lowercase_       ,     lowercase_)

    def     _UpperCAmelCase		( self	: Any       ,     lowerCAmelCase_	: Dict       ,     lowerCAmelCase_	: Optional[int] = 8_0_0_0       ,     lowerCAmelCase_	: int = True       ,     ):







      """simple docstring"""







      lowercase_	    =       trainers.UnigramTrainer(
          vocab_size=lowercase_       ,     special_tokens=self.special_tokens_list       ,     show_progress=lowercase_       ,     )

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

      self.add_unk_id()

    def     _UpperCAmelCase		( self	: List[Any]       ,     lowerCAmelCase_	: Optional[Any]       ,     lowerCAmelCase_	: int = 8_0_0_0       ,     lowerCAmelCase_	: Optional[Any] = True       ,     ):







      """simple docstring"""







      lowercase_	    =       trainers.UnigramTrainer(
          vocab_size=lowercase_       ,     special_tokens=self.special_tokens_list       ,     show_progress=lowercase_       ,     )

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

      self.add_unk_id()




    def     _UpperCAmelCase		( self	: int):







      """simple docstring"""







      lowercase_	    =       json.loads(self._tokenizer.to_str())

      lowercase_	    =       self.special_tokens["unk"]["id"]

      lowercase_	    =       Tokenizer.from_str(json.dumps(lowercase_))



"""simple docstring"""





from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
    from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline


