

'''simple docstring'''




import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class     lowercase_		(						A__	,    unittest.TestCase	):

  '''simple docstring'''





  __lowerCAmelCase   :	List[Any]      					=				MPNetTokenizer
  __lowerCAmelCase   :	Dict      					=				MPNetTokenizerFast
  __lowerCAmelCase   :	List[str]      					=				True
  __lowerCAmelCase   :	Union[str, Any]      					=				True
  def   snake_case_     (       self       )							->			Any:


    """simple docstring"""
    super().setUp()

    UpperCAmelCase  							=		[
        '[UNK]',
        '[CLS]',
        '[SEP]',
        '[PAD]',
        '[MASK]',
        'want',
        '##want',
        '##ed',
        'wa',
        'un',
        'runn',
        '##ing',
        ',',
        'low',
        'lowest',
    ]
    UpperCAmelCase  							=		os.path.join(self.tmpdirname				,	VOCAB_FILES_NAMES['vocab_file']       )
    with open(self.vocab_file				,	'w'				,	encoding='utf-8'       ) as vocab_writer:
      vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]       )       )
  def   snake_case_     (       self				,	a_       )							->			Tuple:


    """simple docstring"""
    UpperCAmelCase  							=		'UNwant\u00E9d,running'
    UpperCAmelCase  							=		'unwanted, running'
    return input_text, output_text
  def   snake_case_     (       self       )							->			int:


    """simple docstring"""
    UpperCAmelCase  							=		self.tokenizer_class(self.vocab_file       )

    UpperCAmelCase  							=		tokenizer.tokenize('UNwant\u00E9d,running'       )
    self.assertListEqual(a_				,	['un', '##want', '##ed', ',', 'runn', '##ing']       )
    self.assertListEqual(tokenizer.convert_tokens_to_ids(a_       )				,	[9, 6, 7, 1_2, 1_0, 1_1]       )





  @slow
  def   snake_case_     (       self       )							->			int:


    """simple docstring"""
    UpperCAmelCase  							=		self.tokenizer_class.from_pretrained('microsoft/mpnet-base'       )

    UpperCAmelCase  							=		tokenizer.encode('sequence builders'				,	add_special_tokens=a_       )
    UpperCAmelCase  							=		tokenizer.encode('multi-sequence build'				,	add_special_tokens=a_       )

    UpperCAmelCase  							=		tokenizer.build_inputs_with_special_tokens(a_       )
    UpperCAmelCase  							=		tokenizer.build_inputs_with_special_tokens(a_				,	a_       )

    assert encoded_sentence == [0] + text + [2]
    assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]





'''simple docstring'''




from typing import TypeVar

from .arrow_dataset import Dataset, _split_by_node_map_style_dataset
from .iterable_dataset import IterableDataset, _split_by_node_iterable_dataset


_a			:	Optional[int]								=  TypeVar('DatasetType', Dataset, IterableDataset)


def  lowerCamelCase__						(  SCREAMING_SNAKE_CASE :				DatasetType    ,				SCREAMING_SNAKE_CASE :				int    ,				SCREAMING_SNAKE_CASE :				int  ):
  if isinstance(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE  ):
    return _split_by_node_map_style_dataset(SCREAMING_SNAKE_CASE    ,				rank=SCREAMING_SNAKE_CASE    ,				world_size=SCREAMING_SNAKE_CASE  )
  else:
    return _split_by_node_iterable_dataset(SCREAMING_SNAKE_CASE    ,				rank=SCREAMING_SNAKE_CASE    ,				world_size=SCREAMING_SNAKE_CASE  )


