





"""simple docstring"""






import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


A			      =	get_tests_dir('''fixtures/test_sentencepiece.model''')




@require_sentencepiece
@require_tokenizers
class 					__lowercase      (      __SCREAMING_SNAKE_CASE ,   unittest.TestCase				):







					'''simple docstring'''




					__lowerCAmelCase	=	XGLMTokenizer
					__lowerCAmelCase	=	XGLMTokenizerFast
					__lowerCAmelCase	=	True
					__lowerCAmelCase	=	True







					def 			_lowerCamelCase		(    self  ):
									super().setUp()

									# We have a SentencePiece fixture for testing
									__a			:    Tuple      							=	XGLMTokenizer(A_						,      keep_accents=A_  )
									tokenizer.save_pretrained(self.tmpdirname  )







					def 			_lowerCamelCase		(    self  ):
									__a			:    str      							=	'''<pad>'''
									__a			:    Optional[int]      							=	1

									self.assertEqual(self.get_tokenizer()._convert_token_to_id(A_  )						,      A_  )
									self.assertEqual(self.get_tokenizer()._convert_id_to_token(A_  )						,      A_  )







					def 			_lowerCamelCase		(    self  ):
									__a			:    int      							=	list(self.get_tokenizer().get_vocab().keys()  )

									self.assertEqual(vocab_keys[0]						,      '''<s>'''  )
									self.assertEqual(vocab_keys[1]						,      '''<pad>'''  )
									self.assertEqual(len(A_  )						,      1008  )







					def 			_lowerCamelCase		(    self  ):
									self.assertEqual(self.get_tokenizer().vocab_size						,      1008  )







					def 			_lowerCamelCase		(    self  ):
									__a			:    Optional[int]      							=	XGLMTokenizer(A_						,      keep_accents=A_  )

									__a			:    str      							=	tokenizer.tokenize('''This is a test'''  )
									self.assertListEqual(A_						,      ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']  )

									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(A_  )						,      [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]						,      )

									__a			:    List[str]      							=	tokenizer.tokenize('''I was born in 92000, and this is falsé.'''  )
									self.assertListEqual(
									    A_						,      [
									        SPIECE_UNDERLINE + '''I''',
									        SPIECE_UNDERLINE + '''was''',
									        SPIECE_UNDERLINE + '''b''',
									        '''or''',
									        '''n''',
									        SPIECE_UNDERLINE + '''in''',
									        SPIECE_UNDERLINE + '''''',
									        '''9''',
									        '''2''',
									        '''0''',
									        '''0''',
									        '''0''',
									        ''',''',
									        SPIECE_UNDERLINE + '''and''',
									        SPIECE_UNDERLINE + '''this''',
									        SPIECE_UNDERLINE + '''is''',
									        SPIECE_UNDERLINE + '''f''',
									        '''al''',
									        '''s''',
									        '''é''',
									        '''.''',
									    ]						,      )
									__a			:    int      							=	tokenizer.convert_tokens_to_ids(A_  )
									self.assertListEqual(
									    A_						,      [
									        value + tokenizer.fairseq_offset
									        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
									    ]						,      )

									__a			:    Optional[int]      							=	tokenizer.convert_ids_to_tokens(A_  )
									self.assertListEqual(
									    A_						,      [
									        SPIECE_UNDERLINE + '''I''',
									        SPIECE_UNDERLINE + '''was''',
									        SPIECE_UNDERLINE + '''b''',
									        '''or''',
									        '''n''',
									        SPIECE_UNDERLINE + '''in''',
									        SPIECE_UNDERLINE + '''''',
									        '''<unk>''',
									        '''2''',
									        '''0''',
									        '''0''',
									        '''0''',
									        ''',''',
									        SPIECE_UNDERLINE + '''and''',
									        SPIECE_UNDERLINE + '''this''',
									        SPIECE_UNDERLINE + '''is''',
									        SPIECE_UNDERLINE + '''f''',
									        '''al''',
									        '''s''',
									        '''<unk>''',
									        '''.''',
									    ]						,      )







					@cached_property
					def 			_lowerCamelCase		(    self  ):
									return XGLMTokenizer.from_pretrained('''facebook/xglm-564M'''  )







					def 			_lowerCamelCase		(    self  ):

									with tempfile.NamedTemporaryFile() as f:
													shutil.copyfile(A_						,      f.name  )
													__a			:    Optional[Any]      							=	XGLMTokenizer(f.name						,      keep_accents=A_  )
													__a			:    int      							=	pickle.dumps(A_  )
									pickle.loads(A_  )







					def 			_lowerCamelCase		(    self  ):

									if not self.test_rust_tokenizer:
													return

									__a			:    Optional[int]      							=	self.get_tokenizer()
									__a			:    List[str]      							=	self.get_rust_tokenizer()

									__a			:    List[str]      							=	'''I was born in 92000, and this is falsé.'''

									__a			:    str      							=	tokenizer.tokenize(A_  )
									__a			:    Union[str, Any]      							=	rust_tokenizer.tokenize(A_  )
									self.assertListEqual(A_						,      A_  )

									__a			:    List[str]      							=	tokenizer.encode(A_						,      add_special_tokens=A_  )
									__a			:    Any      							=	rust_tokenizer.encode(A_						,      add_special_tokens=A_  )
									self.assertListEqual(A_						,      A_  )

									__a			:    Optional[int]      							=	self.get_rust_tokenizer()
									__a			:    int      							=	tokenizer.encode(A_  )
									__a			:    int      							=	rust_tokenizer.encode(A_  )
									self.assertListEqual(A_						,      A_  )







					@slow
					def 			_lowerCamelCase		(    self  ):
									__a			:    Union[str, Any]      							=	'''Hello World!'''
									__a			:    Dict      							=	[2, 31227, 4447, 35]

									self.assertListEqual(A_						,      self.big_tokenizer.encode(A_  )  )







					@slow
					def 			_lowerCamelCase		(    self  ):
									__a			:    Dict      							=	(
									    '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
									    ''' add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth'''
									)
									# fmt: off
									__a			:    Any      							=	[2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 71630, 28085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 13675, 377, 652, 7580, 10341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 202277, 17892, 33, 60, 87, 4, 3234, 157, 61, 2667, 52376, 19, 88, 23, 735]
									# fmt: on

									self.assertListEqual(A_						,      self.big_tokenizer.encode(A_  )  )







					@slow
					def 			_lowerCamelCase		(    self  ):
									__a			:    int      							=	{
									    '''input_ids''': [[2, 108825, 1163, 15, 88010, 473, 15898, 157, 13672, 1857, 312, 8, 238021, 1163, 53, 13672, 1857, 312, 8, 53283, 182396, 8, 18566, 16, 36733, 4101, 8, 230, 244017, 122553, 7, 15, 132597, 4, 293, 12511, 7610, 4, 3414, 132597, 9, 4, 32361, 362, 4, 734, 28512, 32569, 18, 4, 32361, 26096, 14982, 73, 18715, 21433, 235261, 15, 492, 12427, 16, 53, 18715, 21433, 65454, 15, 23659, 563, 16, 278, 597, 2843, 595, 7931, 182396, 64186, 22, 886, 595, 132981, 53, 25540, 3449, 43982, 39901, 5951, 878, 330, 4, 27694, 80269, 312, 53, 6517, 11780, 611, 20408, 5], [2, 6, 132597, 67, 42897, 33, 592, 8, 163729, 25540, 361, 136997, 109514, 173230, 7, 501, 60, 102913, 196, 5631, 235, 63243, 473, 6, 231757, 74, 5277, 7905, 53, 3095, 37317, 22, 454, 183874, 5], [2, 268, 31298, 46530, 6, 132935, 43831, 7, 597, 32, 24, 3688, 9865, 5]],
									    '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
									}  # noqa: E501
									# fmt: on

									self.tokenizer_integration_test_util(
									    expected_encoding=A_						,      model_name='''facebook/xglm-564M'''						,      padding=A_						,      )






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A					:				List[str]				=			{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _A					:				Dict				=			[
      """WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """WavLMForAudioFrameClassification""",
      """WavLMForCTC""",
      """WavLMForSequenceClassification""",
      """WavLMForXVector""",
      """WavLMModel""",
      """WavLMPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_wavlm import (
        WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        WavLMForAudioFrameClassification,
        WavLMForCTC,
        WavLMForSequenceClassification,
        WavLMForXVector,
        WavLMModel,
        WavLMPreTrainedModel,
    )

else:
  import sys

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