"""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


__magic_name__     					=       get_tests_dir("fixtures/test_sentencepiece.model")

@require_sentencepiece
@require_tokenizers
class SCREAMING_SNAKE_CASE  (     UpperCAmelCase_ ,   unittest.TestCase						):







 """simple docstring"""


 a_							:						List[Any]	      =ReformerTokenizer
 a_							:						str	      =ReformerTokenizerFast
 a_							:						List[Any]	      =True
 a_							:						Dict	      =False
 a_							:						Tuple	      =True


 def 							_lowerCAmelCase					( self		:   Tuple					)					->      str:




    '''simple docstring'''






    super().setUp()

    a__  					=		ReformerTokenizer(SCREAMING_SNAKE_CASE_       , keep_accents=SCREAMING_SNAKE_CASE_					)
    tokenizer.save_pretrained(self.tmpdirname					)


 def 							_lowerCAmelCase					( self		:   Dict					)					->      List[str]:




    '''simple docstring'''






    a__  					=		"""<s>"""
    a__  					=		1

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


 def 							_lowerCAmelCase					( self		:   List[Any]					)					->      Optional[Any]:




    '''simple docstring'''






    a__  					=		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(SCREAMING_SNAKE_CASE_					)       , 1000					)


 def 							_lowerCAmelCase					( self		:   List[str]					)					->      Union[str, Any]:




    '''simple docstring'''






    self.assertEqual(self.get_tokenizer().vocab_size       , 1000					)


 def 							_lowerCAmelCase					( self		:   Dict					)					->      List[str]:




    '''simple docstring'''






    if not self.test_rust_tokenizer:
       return

    a__  					=		self.get_tokenizer()
    a__  					=		self.get_rust_tokenizer()

    a__  					=		"""I was born in 92000, and this is falsé."""

    a__  					=		tokenizer.tokenize(SCREAMING_SNAKE_CASE_					)
    a__  					=		rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE_					)
    self.assertListEqual(SCREAMING_SNAKE_CASE_       , SCREAMING_SNAKE_CASE_					)

    a__  					=		tokenizer.encode(SCREAMING_SNAKE_CASE_       , add_special_tokens=SCREAMING_SNAKE_CASE_					)
    a__  					=		rust_tokenizer.encode(SCREAMING_SNAKE_CASE_       , add_special_tokens=SCREAMING_SNAKE_CASE_					)
    self.assertListEqual(SCREAMING_SNAKE_CASE_       , SCREAMING_SNAKE_CASE_					)

    a__  					=		self.get_rust_tokenizer()
    a__  					=		tokenizer.encode(SCREAMING_SNAKE_CASE_					)
    a__  					=		rust_tokenizer.encode(SCREAMING_SNAKE_CASE_					)
    self.assertListEqual(SCREAMING_SNAKE_CASE_       , SCREAMING_SNAKE_CASE_					)


 def 							_lowerCAmelCase					( self		:   Dict       , _snake_case		:   Optional[Any]=15					)					->      Tuple:




    '''simple docstring'''






    for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''					):
          a__  					=		self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_       , **SCREAMING_SNAKE_CASE_					)

          # Simple input
          a__  					=		"""This is a simple input"""
          a__  					=		["""This is a simple input 1""", """This is a simple input 2"""]
          a__  					=		("""This is a simple input""", """This is a pair""")
          a__  					=		[
              ("""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(SCREAMING_SNAKE_CASE_       , tokenizer_r.encode       , SCREAMING_SNAKE_CASE_       , max_length=SCREAMING_SNAKE_CASE_       , padding='max_length'					)

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

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

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

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

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


 def 							_lowerCAmelCase					( self		:   Any					)					->      int:




    '''simple docstring'''






    pass


 def 							_lowerCAmelCase					( self		:   List[str]					)					->      Optional[int]:




    '''simple docstring'''






    a__  					=		ReformerTokenizer(SCREAMING_SNAKE_CASE_       , keep_accents=SCREAMING_SNAKE_CASE_					)

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

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

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

    a__  					=		tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_					)
    self.assertListEqual(
        SCREAMING_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 							_lowerCAmelCase					( self		:   List[str]					)					->      Dict:




    '''simple docstring'''






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


 @slow
 def 							_lowerCAmelCase					( self		:   Tuple					)					->      Optional[int]:




    '''simple docstring'''






    a__  					=		"""Hello World!"""
    a__  					=		[126, 32, 262, 152, 38, 72, 287]

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


 @slow
 def 							_lowerCAmelCase					( self		:   str					)					->      Any:




    '''simple docstring'''






    a__  					=		(
        """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"""
    )
    a__  					=		[
        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(SCREAMING_SNAKE_CASE_       , self.big_tokenizer.encode(SCREAMING_SNAKE_CASE_					)					)


 @require_torch
 @slow
 def 							_lowerCAmelCase					( self		:   Tuple					)					->      str:




    '''simple docstring'''






    import torch

    from transformers import ReformerConfig, ReformerModel

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

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



 @slow
 def 							_lowerCAmelCase					( self		:   Tuple					)					->      Union[str, Any]:




    '''simple docstring'''






    a__  					=		{"""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
    a__  					=		[
        """This is a very simple sentence.""",
        """The quick brown fox jumps over the lazy dog.""",
    ]

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




import unittest

import torch
from torch import nn

from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory

def 		UpperCamelCase						(   )		->						List[Any]:


  '''simple docstring'''






  raise RuntimeError("""CUDA out of memory.""" )



class    _snake_case (						nn.Module				):


 def __init__(       self):


   '''simple docstring'''




   super().__init__()
   lowercase__	: Optional[Any]     		=   nn.Linear(3       ,	4)
   lowercase__	: Union[str, Any]     		=   nn.BatchNormad(4)
   lowercase__	: str     		=   nn.Linear(4       ,	5)



 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   return self.lineara(self.batchnorm(self.lineara(SCREAMING_SNAKE_CASE_)))



class    _snake_case (						unittest.TestCase				):


 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: List[str]     		=   []

   @find_executable_batch_size(starting_batch_size=1_28)
   def mock_training_loop_function(SCREAMING_SNAKE_CASE_):
     nonlocal batch_sizes
     batch_sizes.append(SCREAMING_SNAKE_CASE_)
     if batch_size != 8:
       raise_fake_out_of_memory()

   mock_training_loop_function()
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	[1_28, 64, 32, 16, 8])


 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: int     		=   []

   @find_executable_batch_size(starting_batch_size=1_28)
   def mock_training_loop_function(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_):
     nonlocal batch_sizes
     batch_sizes.append(SCREAMING_SNAKE_CASE_)
     if batch_size != 8:
       raise_fake_out_of_memory()
     return batch_size, arga

   lowercase__		,     lowercase__	: int     		=   mock_training_loop_function("""hello""")
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	[1_28, 64, 32, 16, 8])
   self.assertListEqual([bs, arga]       ,	[8, """hello"""])


 def   lowercase__  (       self):


   '''simple docstring'''




   @find_executable_batch_size(starting_batch_size=0)
   def mock_training_loop_function(SCREAMING_SNAKE_CASE_):
     pass

   with self.assertRaises(SCREAMING_SNAKE_CASE_) as cm:
     mock_training_loop_function()
     self.assertIn("""No executable batch size found, reached zero."""       ,	cm.exception.args[0])


 def   lowercase__  (       self):


   '''simple docstring'''




   @find_executable_batch_size(starting_batch_size=16)
   def mock_training_loop_function(SCREAMING_SNAKE_CASE_):
     if batch_size > 0:
       raise_fake_out_of_memory()
     pass

   with self.assertRaises(SCREAMING_SNAKE_CASE_) as cm:
     mock_training_loop_function()
     self.assertIn("""No executable batch size found, reached zero."""       ,	cm.exception.args[0])


 def   lowercase__  (       self):


   '''simple docstring'''




   @find_executable_batch_size(starting_batch_size=1_28)
   def mock_training_loop_function(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_):
     if batch_size != 8:
       raise raise_fake_out_of_memory()

   with self.assertRaises(SCREAMING_SNAKE_CASE_) as cm:
     mock_training_loop_function(1_28       ,	"""hello"""       ,	"""world""")
     self.assertIn("""Batch size was passed into `f`"""       ,	cm.exception.args[0])
     self.assertIn("""`f(arg1='hello', arg2='world')"""       ,	cm.exception.args[0])


 def   lowercase__  (       self):


   '''simple docstring'''




   @find_executable_batch_size(starting_batch_size=16)
   def mock_training_loop_function(SCREAMING_SNAKE_CASE_):
     raise ValueError("""Oops, we had an error!""")

   with self.assertRaises(SCREAMING_SNAKE_CASE_) as cm:
     mock_training_loop_function()
     self.assertIn("""Oops, we had an error!"""       ,	cm.exception.args[0])



 @require_cuda
 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: str     		=   torch.cuda.memory_allocated()
   lowercase__	: str     		=   ModelForTest()
   model.cuda()
   self.assertGreater(torch.cuda.memory_allocated()       ,	SCREAMING_SNAKE_CASE_)
   lowercase__	: Tuple     		=   release_memory(SCREAMING_SNAKE_CASE_)
   self.assertEqual(torch.cuda.memory_allocated()       ,	SCREAMING_SNAKE_CASE_)






