






"""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		:  str						=		get_tests_dir('fixtures/test_sentencepiece.model')

@require_sentencepiece
@require_tokenizers
class        a     (   lowerCAmelCase_,				unittest.TestCase	):
    UpperCAmelCase_ :     Any	     =ReformerTokenizer
    UpperCAmelCase_ :     str	     =ReformerTokenizerFast
    UpperCAmelCase_ :     Union[str, Any]	     =True
    UpperCAmelCase_ :     Union[str, Any]	     =False
    UpperCAmelCase_ :     Any	     =True







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

      lowercase							    =       ReformerTokenizer(snake_case_							,		keep_accents=snake_case_       )
      tokenizer.save_pretrained(self.tmpdirname       )







    def 			UpperCamelCase_      (			self       ):
      lowercase							    =       '<s>'
      lowercase							    =       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       ):
      lowercase							    =       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_       )							,		1_0_0_0       )







    def 			UpperCamelCase_      (			self       ):
      self.assertEqual(self.get_tokenizer().vocab_size							,		1_0_0_0       )







    def 			UpperCamelCase_      (			self       ):
      if not self.test_rust_tokenizer:
        return

      lowercase							    =       self.get_tokenizer()
      lowercase							    =       self.get_rust_tokenizer()

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

      lowercase							    =       tokenizer.tokenize(snake_case_       )
      lowercase							    =       rust_tokenizer.tokenize(snake_case_       )
      self.assertListEqual(snake_case_							,		snake_case_       )

      lowercase							    =       tokenizer.encode(snake_case_							,		add_special_tokens=snake_case_       )
      lowercase							    =       rust_tokenizer.encode(snake_case_							,		add_special_tokens=snake_case_       )
      self.assertListEqual(snake_case_							,		snake_case_       )

      lowercase							    =       self.get_rust_tokenizer()
      lowercase							    =       tokenizer.encode(snake_case_       )
      lowercase							    =       rust_tokenizer.encode(snake_case_       )
      self.assertListEqual(snake_case_							,		snake_case_       )







    def 			UpperCamelCase_      (			self							,		_lowerCamelCase=1_5       ):
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'       ):
          lowercase							    =       self.rust_tokenizer_class.from_pretrained(snake_case_							,		**snake_case_       )

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







    def 			UpperCamelCase_      (			self       ):
      lowercase							    =       ReformerTokenizer(snake_case_							,		keep_accents=snake_case_       )

      lowercase							    =       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_8_5, 4_6, 1_0, 1_7_0, 3_8_2]							,		)

      lowercase							    =       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',
              '.',
          ]							,		)
      lowercase							    =       tokenizer.convert_tokens_to_ids(snake_case_       )
      self.assertListEqual(
          snake_case_							,		[8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]							,		)

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







    @slow
    def 			UpperCamelCase_      (			self       ):
      lowercase							    =       'Hello World!'
      lowercase							    =       [1_2_6, 3_2, 2_6_2, 1_5_2, 3_8, 7_2, 2_8_7]

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







    @slow
    def 			UpperCamelCase_      (			self       ):
      lowercase							    =       (
          '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'
      )
      lowercase							    =       [
          1_0_8,
          2_6_5,
          2_4,
          1_1_1,
          4,
          2_5_8,
          1_5_6,
          3_5,
          2_8,
          2_7_5,
          3,
          2_5_9,
          2_9_7,
          2_6_0,
          8_4,
          4,
          3_5,
          1_1_0,
          4_4,
          8,
          2_5_9,
          9_1,
          2_6_8,
          2_1,
          1_1,
          2_0_9,
          2_7_4,
          1_0_9,
          2_6_6,
          2_7_7,
          1_1_7,
          8_6,
          9_3,
          3_1_5,
          2_5_8,
          2_7_8,
          2_5_8,
          2_7_7,
          2_5_8,
          0,
          2_5_8,
          2_8_8,
          2_5_8,
          3_1_9,
          2_5_8,
          0,
          2_5_8,
          0,
          2_5_8,
          0,
          2_5_8,
          0,
          2_5_8,
          2_8_7,
          2_5_8,
          3_1_5,
          2_5_8,
          2_8_9,
          2_5_8,
          2_7_8,
          9_9,
          2_6_9,
          2_6_6,
          2_6_2,
          8,
          2_5_9,
          2_4_1,
          4,
          2_1_7,
          2_3_0,
          2_6_8,
          2_6_6,
          5_5,
          1_6_8,
          1_0_6,
          7_5,
          1_9_3,
          2_6_6,
          2_2_3,
          2_7,
          4_9,
          2_6,
          2_8_2,
          2_5,
          2_6_4,
          2_9_9,
          1_9,
          2_6,
          0,
          2_5_8,
          2_7_7,
          1_1_7,
          8_6,
          9_3,
          1_7_6,
          1_8_3,
          2_7_0,
          1_1,
          2_6_2,
          4_2,
          6_1,
          2_6_5,
      ]

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







    @require_torch
    @slow
    def 			UpperCamelCase_      (			self       ):
      import torch

      from transformers import ReformerConfig, ReformerModel

      # Build sequence
      lowercase							    =       list(self.big_tokenizer.get_vocab().keys()       )[:1_0]
      lowercase							    =       ' '.join(snake_case_       )
      lowercase							    =       self.big_tokenizer.encode_plus(snake_case_							,		return_tensors='pt'       )
      lowercase							    =       self.big_tokenizer.batch_encode_plus([sequence, sequence]							,		return_tensors='pt'       )

      lowercase							    =       ReformerConfig()
      # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
      lowercase							    =       encoded_sequence['input_ids'].shape
      lowercase							    =       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       ):
      # fmt: off
      lowercase							    =       {'input_ids': [[1_0_8, 2_6_5, 2_4, 1_1_1, 4, 2_5_8, 1_5_6, 7, 5_1, 2_7_9, 5_8, 7, 7_6, 2_5, 6_9, 2_7_8], [1_4_0, 2_4_3, 2_6_4, 1_3_4, 1_7, 2_6_7, 7_7, 2_6_3, 2_2, 2_6_2, 2_9_7, 2_5_8, 3_0_4, 1_7_7, 2_7_9, 2_6_6, 1_4, 8_9, 1_3, 3_5, 2_6_1, 2_9_9, 2_7_2, 1_3_7, 2_7_5, 2_7_8]], '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
      lowercase							    =       [
          '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_							,		)









'''simple docstring'''




from .integrations import (
    is_optuna_available,
    is_ray_available,
    is_sigopt_available,
    is_wandb_available,
    run_hp_search_optuna,
    run_hp_search_ray,
    run_hp_search_sigopt,
    run_hp_search_wandb,
)
from .trainer_utils import (
    HPSearchBackend,
    default_hp_space_optuna,
    default_hp_space_ray,
    default_hp_space_sigopt,
    default_hp_space_wandb,
)
from .utils import logging


__SCREAMING_SNAKE_CASE     :int       =				logging.get_logger(__name__)







class   A_	:
 _lowerCamelCase  : str
 _lowerCamelCase  : str           =							None




 @staticmethod
 def      lowercase	(					):
      raise NotImplementedError




 def      lowercase	(					self       :    Union[str, Any]	,			snake_case_       :    Optional[int]	,			snake_case_       :    int	,			snake_case_       :    str	,			**snake_case_       :    List[Any]    ):
      raise NotImplementedError




 def      lowercase	(					self       :    Any	,			snake_case_       :    int    ):
      raise NotImplementedError




 def      lowercase	(					self       :    List[str]    ):
      if not self.is_available():
           raise RuntimeError(
               f'You picked the {self.name} backend, but it is not installed. Run {self.pip_install()}.'    )




 @classmethod
 def      lowercase	(					cls       :    List[Any]    ):
      return f'`pip install {cls.pip_package or cls.name}`'







class   A_	(  lowerCAmelCase_			):
 _lowerCamelCase  : int           =							"""optuna"""




 @staticmethod
 def      lowercase	(					):
      return is_optuna_available()




 def      lowercase	(					self       :    List[str]	,			snake_case_       :    Any	,			snake_case_       :    int	,			snake_case_       :    str	,			**snake_case_       :    Tuple    ):
      return run_hp_search_optuna(snake_case_	,			snake_case_	,			snake_case_	,			**snake_case_    )




 def      lowercase	(					self       :    int	,			snake_case_       :    Optional[int]    ):
      return default_hp_space_optuna(snake_case_    )







class   A_	(  lowerCAmelCase_			):
 _lowerCamelCase  : Any           =							"""ray"""
 _lowerCamelCase  : Tuple           =							"""'ray[tune]'"""




 @staticmethod
 def      lowercase	(					):
      return is_ray_available()




 def      lowercase	(					self       :    Optional[Any]	,			snake_case_       :    Any	,			snake_case_       :    int	,			snake_case_       :    str	,			**snake_case_       :    List[str]    ):
      return run_hp_search_ray(snake_case_	,			snake_case_	,			snake_case_	,			**snake_case_    )




 def      lowercase	(					self       :    Any	,			snake_case_       :    str    ):
      return default_hp_space_ray(snake_case_    )







class   A_	(  lowerCAmelCase_			):
 _lowerCamelCase  : int           =							"""sigopt"""




 @staticmethod
 def      lowercase	(					):
      return is_sigopt_available()




 def      lowercase	(					self       :    Any	,			snake_case_       :    int	,			snake_case_       :    int	,			snake_case_       :    str	,			**snake_case_       :    Dict    ):
      return run_hp_search_sigopt(snake_case_	,			snake_case_	,			snake_case_	,			**snake_case_    )




 def      lowercase	(					self       :    Dict	,			snake_case_       :    Optional[Any]    ):
      return default_hp_space_sigopt(snake_case_    )







class   A_	(  lowerCAmelCase_			):
 _lowerCamelCase  : Optional[int]           =							"""wandb"""




 @staticmethod
 def      lowercase	(					):
      return is_wandb_available()




 def      lowercase	(					self       :    Optional[Any]	,			snake_case_       :    Optional[Any]	,			snake_case_       :    int	,			snake_case_       :    str	,			**snake_case_       :    Optional[Any]    ):
      return run_hp_search_wandb(snake_case_	,			snake_case_	,			snake_case_	,			**snake_case_    )




 def      lowercase	(					self       :    Any	,			snake_case_       :    Union[str, Any]    ):
      return default_hp_space_wandb(snake_case_    )





__SCREAMING_SNAKE_CASE     :Dict       =				{
    HPSearchBackend(backend.name): backend for backend in [OptunaBackend, RayTuneBackend, SigOptBackend, WandbBackend]
}
def 	UpperCAmelCase_							(					)		->       str:


     '''simple docstring'''



     _UpperCAmelCase     							=   [backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
     if len(__lowercase       ) > 0:
          _UpperCAmelCase     							=   available_backends[0].name
          if len(__lowercase       ) > 1:
               logger.info(
                   f'{len(__lowercase       )} hyperparameter search backends available. Using {name} as the default.'       )
          return name
     raise RuntimeError(
         "No hyperparameter search backend available.\n"
         + "\n".join(
             f' - To install {backend.name} run {backend.pip_install()}'
             for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values()       )       )




