






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        __snake_case(					__UpperCamelCase     ,       unittest.TestCase      ):
 lowercase :       List[str]		      =		MPNetTokenizer
 lowercase :       List[str]		      =		MPNetTokenizerFast
 lowercase :       int		      =		True
 lowercase :       Any		      =		True



 def 						UpperCAmelCase    (	self   :   Optional[int]	):

    """simple docstring"""






    super().setUp()

    lowercase__						:	Optional[int]         = [
        """[UNK]""",
        """[CLS]""",
        """[SEP]""",
        """[PAD]""",
        """[MASK]""",
        """want""",
        """##want""",
        """##ed""",
        """wa""",
        """un""",
        """runn""",
        """##ing""",
        """,""",
        """low""",
        """lowest""",
    ]
    lowercase__						:	Optional[int]         = 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 						UpperCAmelCase    (	self   :   Optional[int] ,		UpperCAmelCase__   :   Any	):

    """simple docstring"""






    lowercase__						:	Optional[int]         = """UNwant\u00E9d,running"""
    lowercase__						:	Union[str, Any]         = """unwanted, running"""
    return input_text, output_text



 def 						UpperCAmelCase    (	self   :   List[str]	):

    """simple docstring"""






    lowercase__						:	Optional[Any]         = self.tokenizer_class(self.vocab_file	)

    lowercase__						:	Union[str, Any]         = tokenizer.tokenize("""UNwant\u00E9d,running"""	)
    self.assertListEqual(UpperCAmelCase__ ,		["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]	)
    self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase__	) ,		[9, 6, 7, 12, 10, 11]	)







 @slow
 def 						UpperCAmelCase    (	self   :   Union[str, Any]	):

    """simple docstring"""






    lowercase__						:	Any         = self.tokenizer_class.from_pretrained("""microsoft/mpnet-base"""	)

    lowercase__						:	Any         = tokenizer.encode("""sequence builders""" ,		add_special_tokens=UpperCAmelCase__	)
    lowercase__						:	Union[str, Any]         = tokenizer.encode("""multi-sequence build""" ,		add_special_tokens=UpperCAmelCase__	)

    lowercase__						:	str         = tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__	)
    lowercase__						:	str         = tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__ ,		UpperCAmelCase__	)

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










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a    =       {'configuration_nat': ['NAT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NatConfig']}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a    =       [
     'NAT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'NatForImageClassification',
     'NatModel',
     'NatPreTrainedModel',
     'NatBackbone',
 ]

if TYPE_CHECKING:
 from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_nat import (
      NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
      NatBackbone,
      NatForImageClassification,
      NatModel,
      NatPreTrainedModel,
  )

else:
 import sys

 a    =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


