
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       (  __UpperCamelCase	,		unittest.TestCase					):
					__a					=    MPNetTokenizer
					__a					=    MPNetTokenizerFast
					__a					=    True
					__a					=    True
					def lowercase_			(		self    ):
								"""simple docstring"""







								super().setUp()

								lowerCAmelCase__ :    Tuple				      =			[
								    '''[UNK]''',
								    '''[CLS]''',
								    '''[SEP]''',
								    '''[PAD]''',
								    '''[MASK]''',
								    '''want''',
								    '''##want''',
								    '''##ed''',
								    '''wa''',
								    '''un''',
								    '''runn''',
								    '''##ing''',
								    ''',''',
								    '''low''',
								    '''lowest''',
								]
								lowerCAmelCase__ :    Tuple				      =			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 lowercase_			(		self ,	SCREAMING_SNAKE_CASE__    ):
								"""simple docstring"""







								lowerCAmelCase__ :    List[Any]				      =			'''UNwant\u00E9d,running'''
								lowerCAmelCase__ :    str				      =			'''unwanted, running'''
								return input_text, output_text
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Any				      =			self.tokenizer_class(self.vocab_file    )

								lowerCAmelCase__ :    Optional[Any]				      =			tokenizer.tokenize('''UNwant\u00E9d,running'''    )
								self.assertListEqual(SCREAMING_SNAKE_CASE__ ,	['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing''']    )
								self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__    ) ,	[9, 6, 7, 12, 10, 11]    )
					@slow
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    str				      =			self.tokenizer_class.from_pretrained('''microsoft/mpnet-base'''    )

								lowerCAmelCase__ :    List[Any]				      =			tokenizer.encode('''sequence builders''' ,	add_special_tokens=SCREAMING_SNAKE_CASE__    )
								lowerCAmelCase__ :    List[str]				      =			tokenizer.encode('''multi-sequence build''' ,	add_special_tokens=SCREAMING_SNAKE_CASE__    )

								lowerCAmelCase__ :    str				      =			tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE__    )
								lowerCAmelCase__ :    Any				      =			tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE__ ,	SCREAMING_SNAKE_CASE__    )

								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_tf_available, is_torch_available


A__       :   Union[str, Any]   						=					{"""configuration_cvt""": ["""CVT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CvtConfig"""]}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__       :   Union[str, Any]   						=					[
							    """CVT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """CvtForImageClassification""",
							    """CvtModel""",
							    """CvtPreTrainedModel""",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__       :   str   						=					[
							    """TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFCvtForImageClassification""",
							    """TFCvtModel""",
							    """TFCvtPreTrainedModel""",
							]

if TYPE_CHECKING:
							from .configuration_cvt import CVT_PRETRAINED_CONFIG_ARCHIVE_MAP, CvtConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_cvt import (
														    CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    CvtForImageClassification,
														    CvtModel,
														    CvtPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_cvt import (
														    TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFCvtForImageClassification,
														    TFCvtModel,
														    TFCvtPreTrainedModel,
														)


else:
							import sys

							A__       :   Optional[Any]   						=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



