





import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, 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  __lowerCAmelCase     (	lowerCAmelCase__  ,	unittest.TestCase   ):
 lowerCAmelCase__       					=  ReformerTokenizer
 lowerCAmelCase__       					=  ReformerTokenizerFast
 lowerCAmelCase__       					=  True
 lowerCAmelCase__       					=  False
 lowerCAmelCase__       					=  True




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    super().setUp()

    __lowerCamelCase													=    ReformerTokenizer(__UpperCAmelCase	,				keep_accents=__UpperCAmelCase				)
    tokenizer.save_pretrained(self.tmpdirname				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    '''<s>'''
    __lowerCamelCase													=    1

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




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    list(self.get_tokenizer().get_vocab().keys()				)

    self.assertEqual(vocab_keys[0]	,				'''<unk>'''				)
    self.assertEqual(vocab_keys[1]	,				'''<s>'''				)
    self.assertEqual(vocab_keys[-1]	,				'''j'''				)
    self.assertEqual(len(__UpperCAmelCase				)	,				1000				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    self.assertEqual(self.get_tokenizer().vocab_size	,				1000				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    if not self.test_rust_tokenizer:
       return

    __lowerCamelCase													=    self.get_tokenizer()
    __lowerCamelCase													=    self.get_rust_tokenizer()

    __lowerCamelCase													=    '''I was born in 92000, and this is falsé.'''

    __lowerCamelCase													=    tokenizer.tokenize(__UpperCAmelCase				)
    __lowerCamelCase													=    rust_tokenizer.tokenize(__UpperCAmelCase				)
    self.assertListEqual(__UpperCAmelCase	,				__UpperCAmelCase				)

    __lowerCamelCase													=    tokenizer.encode(__UpperCAmelCase	,				add_special_tokens=__UpperCAmelCase				)
    __lowerCamelCase													=    rust_tokenizer.encode(__UpperCAmelCase	,				add_special_tokens=__UpperCAmelCase				)
    self.assertListEqual(__UpperCAmelCase	,				__UpperCAmelCase				)

    __lowerCamelCase													=    self.get_rust_tokenizer()
    __lowerCamelCase													=    tokenizer.encode(__UpperCAmelCase				)
    __lowerCamelCase													=    rust_tokenizer.encode(__UpperCAmelCase				)
    self.assertListEqual(__UpperCAmelCase	,				__UpperCAmelCase				)




 def        lowerCamelCase      (						self	,				__UpperCAmelCase=15				):



    '''simple docstring'''
    for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
          __lowerCamelCase													=    self.rust_tokenizer_class.from_pretrained(__UpperCAmelCase	,				**__UpperCAmelCase				)

          # Simple input
          __lowerCamelCase													=    '''This is a simple input'''
          __lowerCamelCase													=    ['''This is a simple input 1''', '''This is a simple input 2''']
          __lowerCamelCase													=    ('''This is a simple input''', '''This is a pair''')
          __lowerCamelCase													=    [
              ('''This is a simple input 1''', '''This is a simple input 2'''),
              ('''This is a simple pair 1''', '''This is a simple pair 2'''),
          ]

          # Simple input tests
          self.assertRaises(__UpperCAmelCase	,				tokenizer_r.encode	,				__UpperCAmelCase	,				max_length=__UpperCAmelCase	,				padding='''max_length'''				)

          # Simple input
          self.assertRaises(__UpperCAmelCase	,				tokenizer_r.encode_plus	,				__UpperCAmelCase	,				max_length=__UpperCAmelCase	,				padding='''max_length'''				)

          # Simple input
          self.assertRaises(
              __UpperCAmelCase	,				tokenizer_r.batch_encode_plus	,				__UpperCAmelCase	,				max_length=__UpperCAmelCase	,				padding='''max_length'''	,				)

          # Pair input
          self.assertRaises(__UpperCAmelCase	,				tokenizer_r.encode	,				__UpperCAmelCase	,				max_length=__UpperCAmelCase	,				padding='''max_length'''				)

          # Pair input
          self.assertRaises(__UpperCAmelCase	,				tokenizer_r.encode_plus	,				__UpperCAmelCase	,				max_length=__UpperCAmelCase	,				padding='''max_length'''				)

          # Pair input
          self.assertRaises(
              __UpperCAmelCase	,				tokenizer_r.batch_encode_plus	,				__UpperCAmelCase	,				max_length=__UpperCAmelCase	,				padding='''max_length'''	,				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    pass




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    ReformerTokenizer(__UpperCAmelCase	,				keep_accents=__UpperCAmelCase				)

    __lowerCamelCase													=    tokenizer.tokenize('''This is a test'''				)
    self.assertListEqual(__UpperCAmelCase	,				['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']				)

    self.assertListEqual(
        tokenizer.convert_tokens_to_ids(__UpperCAmelCase				)	,				[285, 46, 10, 170, 382]	,				)

    __lowerCamelCase													=    tokenizer.tokenize('''I was born in 92000, and this is falsé.'''				)
    self.assertListEqual(
        __UpperCAmelCase	,				[
            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''',
            '''.''',
        ]	,				)
    __lowerCamelCase													=    tokenizer.convert_tokens_to_ids(__UpperCAmelCase				)
    self.assertListEqual(
        __UpperCAmelCase	,				[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]	,				)

    __lowerCamelCase													=    tokenizer.convert_ids_to_tokens(__UpperCAmelCase				)
    self.assertListEqual(
        __UpperCAmelCase	,				[
            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				):



    '''simple docstring'''
    return ReformerTokenizer.from_pretrained('''google/reformer-crime-and-punishment'''				)




 @slow
 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    '''Hello World!'''
    __lowerCamelCase													=    [126, 32, 262, 152, 38, 72, 287]

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




 @slow
 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    (
        '''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'''
    )
    __lowerCamelCase													=    [
        108,
        265,
        24,
        111,
        4,
        258,
        156,
        35,
        28,
        275,
        3,
        259,
        297,
        260,
        84,
        4,
        35,
        110,
        44,
        8,
        259,
        91,
        268,
        21,
        11,
        209,
        274,
        109,
        266,
        277,
        117,
        86,
        93,
        315,
        258,
        278,
        258,
        277,
        258,
        0,
        258,
        288,
        258,
        319,
        258,
        0,
        258,
        0,
        258,
        0,
        258,
        0,
        258,
        287,
        258,
        315,
        258,
        289,
        258,
        278,
        99,
        269,
        266,
        262,
        8,
        259,
        241,
        4,
        217,
        230,
        268,
        266,
        55,
        168,
        106,
        75,
        193,
        266,
        223,
        27,
        49,
        26,
        282,
        25,
        264,
        299,
        19,
        26,
        0,
        258,
        277,
        117,
        86,
        93,
        176,
        183,
        270,
        11,
        262,
        42,
        61,
        265,
    ]

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




 @require_torch
 @slow
 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    import torch

    from transformers import ReformerConfig, ReformerModel

    # Build sequence
    __lowerCamelCase													=    list(self.big_tokenizer.get_vocab().keys()				)[:10]
    __lowerCamelCase													=    ''' '''.join(__UpperCAmelCase				)
    __lowerCamelCase													=    self.big_tokenizer.encode_plus(__UpperCAmelCase	,				return_tensors='''pt'''				)
    __lowerCamelCase													=    self.big_tokenizer.batch_encode_plus([sequence, sequence]	,				return_tensors='''pt'''				)

    __lowerCamelCase													=    ReformerConfig()
    # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
    __lowerCamelCase													=    encoded_sequence['''input_ids'''].shape
    __lowerCamelCase													=    ReformerModel(__UpperCAmelCase				)

    # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
    assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

    with torch.no_grad():
       model(**__UpperCAmelCase				)
       model(**__UpperCAmelCase				)




 @slow
 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    {'''input_ids''': [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], '''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]]}  # noqa: E501
    # fmt: on

    # This tokenizer does not know some characters like ")".
    # That is the reason why we use very simple texts here.
    # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
    __lowerCamelCase													=    [
        '''This is a very simple sentence.''',
        '''The quick brown fox jumps over the lazy dog.''',
    ]

    self.tokenizer_integration_test_util(
        expected_encoding=__UpperCAmelCase	,				model_name='''google/reformer-crime-and-punishment'''	,				revision='''0e6c3decb8211d49bf881013425dc8b0448b3f5a'''	,				padding=__UpperCAmelCase	,				sequences=__UpperCAmelCase	,				)











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_			=					{
    """configuration_clipseg""": [
        """CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """CLIPSegConfig""",
        """CLIPSegTextConfig""",
        """CLIPSegVisionConfig""",
    ],
    """processing_clipseg""": ["""CLIPSegProcessor"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_			=					[
      """CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """CLIPSegModel""",
      """CLIPSegPreTrainedModel""",
      """CLIPSegTextModel""",
      """CLIPSegVisionModel""",
      """CLIPSegForImageSegmentation""",
  ]

if TYPE_CHECKING:
  from .configuration_clipseg import (
      CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
      CLIPSegConfig,
      CLIPSegTextConfig,
      CLIPSegVisionConfig,
  )
  from .processing_clipseg import CLIPSegProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_clipseg import (
        CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
        CLIPSegForImageSegmentation,
        CLIPSegModel,
        CLIPSegPreTrainedModel,
        CLIPSegTextModel,
        CLIPSegVisionModel,
    )

else:
  import sys

  a_			=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






