





"""simple docstring"""
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


__UpperCamelCase     :						Optional[Any]						       =  get_tests_dir('''fixtures/test_sentencepiece.model''')







@require_sentencepiece
@require_tokenizers
class       a							(   a_   , unittest.TestCase  ):
 snake_case__             =       ReformerTokenizer
 snake_case__             =       ReformerTokenizerFast
 snake_case__             =       True
 snake_case__             =       False
 snake_case__             =       True



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  super().setUp()

  lowerCAmelCase    				= ReformerTokenizer(_snake_case				,       keep_accents=_snake_case     )
  tokenizer.save_pretrained(self.tmpdirname     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  lowerCAmelCase    				= '<s>'
  lowerCAmelCase    				= 1

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



 def    UpperCamelCase__  (     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(_snake_case     )				,       10_00     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  self.assertEqual(self.get_tokenizer().vocab_size				,       10_00     )



 def    UpperCamelCase__  (     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(_snake_case     )
  lowerCAmelCase    				= rust_tokenizer.tokenize(_snake_case     )
  self.assertListEqual(_snake_case				,       _snake_case     )

  lowerCAmelCase    				= tokenizer.encode(_snake_case				,       add_special_tokens=_snake_case     )
  lowerCAmelCase    				= rust_tokenizer.encode(_snake_case				,       add_special_tokens=_snake_case     )
  self.assertListEqual(_snake_case				,       _snake_case     )

  lowerCAmelCase    				= self.get_rust_tokenizer()
  lowerCAmelCase    				= tokenizer.encode(_snake_case     )
  lowerCAmelCase    				= rust_tokenizer.encode(_snake_case     )
  self.assertListEqual(_snake_case				,       _snake_case     )



 def    UpperCamelCase__  (     self				,       _snake_case=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(_snake_case				,       **_snake_case     )

    # 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(_snake_case				,       tokenizer_r.encode				,       _snake_case				,       max_length=_snake_case				,       padding='max_length'     )

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

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

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

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

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



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  pass



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  lowerCAmelCase    				= ReformerTokenizer(_snake_case				,       keep_accents=_snake_case     )

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

  self.assertListEqual(
      tokenizer.convert_tokens_to_ids(_snake_case     )				,       [2_85, 46, 10, 1_70, 3_82]				,       )

  lowerCAmelCase    				= tokenizer.tokenize('I was born in 92000, and this is falsé.'     )
  self.assertListEqual(
      _snake_case				,       [
          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(_snake_case     )
  self.assertListEqual(
      _snake_case				,       [8, 21, 84, 55, 24, 19, 7, 0, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 0, 4]				,       )

  lowerCAmelCase    				= tokenizer.convert_ids_to_tokens(_snake_case     )
  self.assertListEqual(
      _snake_case				,       [
          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    UpperCamelCase__  (     self     ):







  """simple docstring"""






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



 @slow
 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  lowerCAmelCase    				= 'Hello World!'
  lowerCAmelCase    				= [1_26, 32, 2_62, 1_52, 38, 72, 2_87]

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



 @slow
 def    UpperCamelCase__  (     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    				= [
      1_08,
      2_65,
      24,
      1_11,
      4,
      2_58,
      1_56,
      35,
      28,
      2_75,
      3,
      2_59,
      2_97,
      2_60,
      84,
      4,
      35,
      1_10,
      44,
      8,
      2_59,
      91,
      2_68,
      21,
      11,
      2_09,
      2_74,
      1_09,
      2_66,
      2_77,
      1_17,
      86,
      93,
      3_15,
      2_58,
      2_78,
      2_58,
      2_77,
      2_58,
      0,
      2_58,
      2_88,
      2_58,
      3_19,
      2_58,
      0,
      2_58,
      0,
      2_58,
      0,
      2_58,
      0,
      2_58,
      2_87,
      2_58,
      3_15,
      2_58,
      2_89,
      2_58,
      2_78,
      99,
      2_69,
      2_66,
      2_62,
      8,
      2_59,
      2_41,
      4,
      2_17,
      2_30,
      2_68,
      2_66,
      55,
      1_68,
      1_06,
      75,
      1_93,
      2_66,
      2_23,
      27,
      49,
      26,
      2_82,
      25,
      2_64,
      2_99,
      19,
      26,
      0,
      2_58,
      2_77,
      1_17,
      86,
      93,
      1_76,
      1_83,
      2_70,
      11,
      2_62,
      42,
      61,
      2_65,
  ]

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



 @require_torch
 @slow
 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import torch

  from transformers import ReformerConfig, ReformerModel

  # Build sequence
  lowerCAmelCase    				= list(self.big_tokenizer.get_vocab().keys()     )[:10]
  lowerCAmelCase    				= ' '.join(_snake_case     )
  lowerCAmelCase    				= self.big_tokenizer.encode_plus(_snake_case				,       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(_snake_case     )

  # 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(**_snake_case     )
   model(**_snake_case     )



 @slow
 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  lowerCAmelCase    				= {'input_ids': [[1_08, 2_65, 24, 1_11, 4, 2_58, 1_56, 7, 51, 2_79, 58, 7, 76, 25, 69, 2_78], [1_40, 2_43, 2_64, 1_34, 17, 2_67, 77, 2_63, 22, 2_62, 2_97, 2_58, 3_04, 1_77, 2_79, 2_66, 14, 89, 13, 35, 2_61, 2_99, 2_72, 1_37, 2_75, 2_78]], '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=_snake_case				,       model_name='google/reformer-crime-and-punishment'				,       revision='0e6c3decb8211d49bf881013425dc8b0448b3f5a'				,       padding=_snake_case				,       sequences=_snake_case				,       )









from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase   :    str     =		logging.get_logger(__name__)

UpperCAmelCase   :    List[Any]     =		{
    "facebook/vit-mae-base": "https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json",
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}







class        __lowercase       (							a_  ):



		"""simple docstring"""

		UpperCamelCase     :					Optional[Any]			       =		"vit_mae"







		def __init__( self		,      A=7_68		,      A=12		,      A=12		,      A=30_72		,      A="gelu"		,      A=0.0		,      A=0.0		,      A=0.02		,      A=1e-1_2		,      A=2_24		,      A=16		,      A=3		,      A=True		,      A=16		,      A=5_12		,      A=8		,      A=20_48		,      A=0.75		,      A=False		,      **A		,      )  -> Dict:







					'''simple docstring'''







					super().__init__(**A	)

					lowerCamelCase    		=  hidden_size
					lowerCamelCase    		=  num_hidden_layers
					lowerCamelCase    		=  num_attention_heads
					lowerCamelCase    		=  intermediate_size
					lowerCamelCase    		=  hidden_act
					lowerCamelCase    		=  hidden_dropout_prob
					lowerCamelCase    		=  attention_probs_dropout_prob
					lowerCamelCase    		=  initializer_range
					lowerCamelCase    		=  layer_norm_eps
					lowerCamelCase    		=  image_size
					lowerCamelCase    		=  patch_size
					lowerCamelCase    		=  num_channels
					lowerCamelCase    		=  qkv_bias
					lowerCamelCase    		=  decoder_num_attention_heads
					lowerCamelCase    		=  decoder_hidden_size
					lowerCamelCase    		=  decoder_num_hidden_layers
					lowerCamelCase    		=  decoder_intermediate_size
					lowerCamelCase    		=  mask_ratio
					lowerCamelCase    		=  norm_pix_loss

