




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

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

          lowerCamelCase__          =						Tokenizer(Unigram()							)

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

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

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

          super().__init__(_snake_case   ,	_snake_case							)
   def    __UpperCAmelCase       (       self			:				int   ,	SCREAMING_SNAKE_CASE_			:				Union[str, List[str]]   ,	SCREAMING_SNAKE_CASE_			:				int = 8000   ,	SCREAMING_SNAKE_CASE_			:				bool = True   ,	):
          lowerCamelCase__          =						trainers.UnigramTrainer(
              vocab_size=_snake_case   ,	special_tokens=self.special_tokens_list   ,	show_progress=_snake_case   ,	)

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

          self.add_unk_id()
   def    __UpperCAmelCase       (       self			:				Any   ,	SCREAMING_SNAKE_CASE_			:				Union[Iterator[str], Iterator[Iterator[str]]]   ,	SCREAMING_SNAKE_CASE_			:				int = 8000   ,	SCREAMING_SNAKE_CASE_			:				bool = True   ,	):
          lowerCamelCase__          =						trainers.UnigramTrainer(
              vocab_size=_snake_case   ,	special_tokens=self.special_tokens_list   ,	show_progress=_snake_case   ,	)

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

          self.add_unk_id()





   def    __UpperCAmelCase       (       self			:				Union[str, Any]							):
          lowerCamelCase__          =						json.loads(self._tokenizer.to_str()							)

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

          lowerCamelCase__          =						Tokenizer.from_str(json.dumps(_snake_case							)							)











SCREAMING_SNAKE_CASE__   			=   '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

SCREAMING_SNAKE_CASE__   			=   [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
SCREAMING_SNAKE_CASE__   			=   {
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}




