


'''simple docstring'''





from arguments import TokenizerTrainingArguments
from datasets import load_dataset
from tqdm import tqdm

from transformers import AutoTokenizer, HfArgumentParser
from transformers.models.gpta.tokenization_gpta import bytes_to_unicode




def 			__lowercase	(						_UpperCamelCase=10     )    ->Optional[int]:







      """simple docstring"""

      for _ in tqdm(range(0,    args.n_examples,    _UpperCamelCase     )     ):
            yield [next(_UpperCamelCase     )[args.text_column] for _ in range(_UpperCamelCase     )]


# Configuration
__a   				=      HfArgumentParser(TokenizerTrainingArguments)
__a   				=      parser.parse_args()

# Base tokenizer
__a   				=      AutoTokenizer.from_pretrained(args.base_tokenizer)
__a   				=      list(bytes_to_unicode().values())

# Load dataset
__a   				=      load_dataset(args.dataset_name, split='''train''', streaming=True)
__a   				=      iter(dataset)


# Training and saving
__a   				=      tokenizer.train_new_from_iterator(
    batch_iterator(), vocab_size=args.vocab_size, initial_alphabet=base_vocab
)



new_tokenizer.save_pretrained(args.tokenizer_name, push_to_hub=args.push_to_hub)





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__a   				=      {'''configuration_yoso''': ['''YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YosoConfig''']}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a   				=      [
      '''YOSO_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''YosoForMaskedLM''',
      '''YosoForMultipleChoice''',
      '''YosoForQuestionAnswering''',
      '''YosoForSequenceClassification''',
      '''YosoForTokenClassification''',
      '''YosoLayer''',
      '''YosoModel''',
      '''YosoPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_yoso import YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP, YosoConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_yoso import (
        YOSO_PRETRAINED_MODEL_ARCHIVE_LIST,
        YosoForMaskedLM,
        YosoForMultipleChoice,
        YosoForQuestionAnswering,
        YosoForSequenceClassification,
        YosoForTokenClassification,
        YosoLayer,
        YosoModel,
        YosoPreTrainedModel,
    )


else:
  import sys

  __a   				=      _LazyModule(__name__, globals()['''__file__'''], _import_structure)

