


import os
import unittest

from transformers import ElectraTokenizerFast
from transformers.models.electra.tokenization_electra import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    ElectraTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english


@require_tokenizers
class        A_					(       a__					,      unittest.TestCase    ):




      '''simple docstring'''


      __snake_case					       =   ElectraTokenizer
      __snake_case					       =   ElectraTokenizerFast
      __snake_case					       =   True
      __snake_case					       =   True
      __snake_case					       =   filter_non_english




      def      _snake_case	(				self:       Dict				):
       super().setUp()

       __lowerCamelCase		:							Any							=						[
           '[UNK]',
           '[CLS]',
           '[SEP]',
           '[PAD]',
           '[MASK]',
           'want',
           '##want',
           '##ed',
           'wa',
           'un',
           'runn',
           '##ing',
           ',',
           'low',
           'lowest',
       ]
       __lowerCamelCase		:							List[str]							=						os.path.join(self.tmpdirname						,      VOCAB_FILES_NAMES['vocab_file']				)
       with open(self.vocab_file						,      'w'						,      encoding='utf-8'				) as vocab_writer:
        vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]				)				)




      def      _snake_case	(				self:       Dict						,      a:       Optional[Any]				):
       __lowerCamelCase		:							Optional[Any]							=						'UNwant\u00E9d,running'
       __lowerCamelCase		:							Union[str, Any]							=						'unwanted, running'
       return input_text, output_text




      def      _snake_case	(				self:       str				):
       __lowerCamelCase		:							Optional[Any]							=						self.tokenizer_class(self.vocab_file				)

       __lowerCamelCase		:							Union[str, Any]							=						tokenizer.tokenize('UNwant\u00E9d,running'				)
       self.assertListEqual(_snake_case						,      ['un', '##want', '##ed', ',', 'runn', '##ing']				)
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case				)						,      [9, 6, 7, 12, 10, 11]				)




      def      _snake_case	(				self:       str				):






       if not self.test_rust_tokenizer:
        return

       __lowerCamelCase		:							Union[str, Any]							=						self.get_tokenizer()
       __lowerCamelCase		:							Optional[Any]							=						self.get_rust_tokenizer()

       __lowerCamelCase		:							Union[str, Any]							=						'UNwant\u00E9d,running'

       __lowerCamelCase		:							Optional[int]							=						tokenizer.tokenize(_snake_case				)
       __lowerCamelCase		:							Any							=						rust_tokenizer.tokenize(_snake_case				)
       self.assertListEqual(_snake_case						,      _snake_case				)

       __lowerCamelCase		:							Union[str, Any]							=						tokenizer.encode(_snake_case						,      add_special_tokens=_snake_case				)
       __lowerCamelCase		:							Tuple							=						rust_tokenizer.encode(_snake_case						,      add_special_tokens=_snake_case				)
       self.assertListEqual(_snake_case						,      _snake_case				)

       __lowerCamelCase		:							Tuple							=						self.get_rust_tokenizer()
       __lowerCamelCase		:							str							=						tokenizer.encode(_snake_case				)
       __lowerCamelCase		:							Union[str, Any]							=						rust_tokenizer.encode(_snake_case				)
       self.assertListEqual(_snake_case						,      _snake_case				)

       # With lower casing
       __lowerCamelCase		:							Optional[int]							=						self.get_tokenizer(do_lower_case=_snake_case				)
       __lowerCamelCase		:							Dict							=						self.get_rust_tokenizer(do_lower_case=_snake_case				)

       __lowerCamelCase		:							Dict							=						'UNwant\u00E9d,running'

       __lowerCamelCase		:							int							=						tokenizer.tokenize(_snake_case				)
       __lowerCamelCase		:							List[str]							=						rust_tokenizer.tokenize(_snake_case				)
       self.assertListEqual(_snake_case						,      _snake_case				)

       __lowerCamelCase		:							str							=						tokenizer.encode(_snake_case						,      add_special_tokens=_snake_case				)
       __lowerCamelCase		:							Dict							=						rust_tokenizer.encode(_snake_case						,      add_special_tokens=_snake_case				)
       self.assertListEqual(_snake_case						,      _snake_case				)

       __lowerCamelCase		:							Dict							=						self.get_rust_tokenizer()
       __lowerCamelCase		:							List[str]							=						tokenizer.encode(_snake_case				)
       __lowerCamelCase		:							List[Any]							=						rust_tokenizer.encode(_snake_case				)
       self.assertListEqual(_snake_case						,      _snake_case				)




      def      _snake_case	(				self:       Optional[int]				):
       __lowerCamelCase		:							Dict							=						BasicTokenizer()

       self.assertListEqual(tokenizer.tokenize('ah\u535A\u63A8zz'				)						,      ['ah', '\u535A', '\u63A8', 'zz']				)




      def      _snake_case	(				self:       List[str]				):
       __lowerCamelCase		:							Dict							=						BasicTokenizer(do_lower_case=_snake_case				)

       self.assertListEqual(
           tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '				)						,      ['hello', '!', 'how', 'are', 'you', '?']				)
       self.assertListEqual(tokenizer.tokenize('H\u00E9llo'				)						,      ['hello']				)




      def      _snake_case	(				self:       List[str]				):
       __lowerCamelCase		:							Optional[Any]							=						BasicTokenizer(do_lower_case=_snake_case						,      strip_accents=_snake_case				)

       self.assertListEqual(
           tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '				)						,      ['hällo', '!', 'how', 'are', 'you', '?']				)
       self.assertListEqual(tokenizer.tokenize('H\u00E9llo'				)						,      ['h\u00E9llo']				)




      def      _snake_case	(				self:       Dict				):
       __lowerCamelCase		:							str							=						BasicTokenizer(do_lower_case=_snake_case						,      strip_accents=_snake_case				)

       self.assertListEqual(
           tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '				)						,      ['hallo', '!', 'how', 'are', 'you', '?']				)
       self.assertListEqual(tokenizer.tokenize('H\u00E9llo'				)						,      ['hello']				)




      def      _snake_case	(				self:       List[Any]				):
       __lowerCamelCase		:							str							=						BasicTokenizer(do_lower_case=_snake_case				)

       self.assertListEqual(
           tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '				)						,      ['hallo', '!', 'how', 'are', 'you', '?']				)
       self.assertListEqual(tokenizer.tokenize('H\u00E9llo'				)						,      ['hello']				)




      def      _snake_case	(				self:       Any				):
       __lowerCamelCase		:							Any							=						BasicTokenizer(do_lower_case=_snake_case				)

       self.assertListEqual(
           tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '				)						,      ['HeLLo', '!', 'how', 'Are', 'yoU', '?']				)




      def      _snake_case	(				self:       List[str]				):
       __lowerCamelCase		:							Union[str, Any]							=						BasicTokenizer(do_lower_case=_snake_case						,      strip_accents=_snake_case				)

       self.assertListEqual(
           tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '				)						,      ['HäLLo', '!', 'how', 'Are', 'yoU', '?']				)




      def      _snake_case	(				self:       List[Any]				):
       __lowerCamelCase		:							Optional[Any]							=						BasicTokenizer(do_lower_case=_snake_case						,      strip_accents=_snake_case				)

       self.assertListEqual(
           tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '				)						,      ['HaLLo', '!', 'how', 'Are', 'yoU', '?']				)




      def      _snake_case	(				self:       Union[str, Any]				):
       __lowerCamelCase		:							str							=						BasicTokenizer(do_lower_case=_snake_case						,      never_split=['[UNK]']				)

       self.assertListEqual(
           tokenizer.tokenize(' \tHeLLo!how  \n Are yoU? [UNK]'				)						,      ['HeLLo', '!', 'how', 'Are', 'yoU', '?', '[UNK]']				)




      def      _snake_case	(				self:       Union[str, Any]				):
       __lowerCamelCase		:							str							=						['[UNK]', '[CLS]', '[SEP]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing']

       __lowerCamelCase		:							Optional[Any]							=						{}
       for i, token in enumerate(_snake_case				):
        __lowerCamelCase		:							Union[str, Any]							=						i
       __lowerCamelCase		:							Optional[int]							=						WordpieceTokenizer(vocab=_snake_case						,      unk_token='[UNK]'				)

       self.assertListEqual(tokenizer.tokenize(''				)						,      []				)

       self.assertListEqual(tokenizer.tokenize('unwanted running'				)						,      ['un', '##want', '##ed', 'runn', '##ing']				)

       self.assertListEqual(tokenizer.tokenize('unwantedX running'				)						,      ['[UNK]', 'runn', '##ing']				)




      def      _snake_case	(				self:       Tuple				):
       self.assertTrue(_is_whitespace(' '				)				)
       self.assertTrue(_is_whitespace('\t'				)				)
       self.assertTrue(_is_whitespace('\r'				)				)
       self.assertTrue(_is_whitespace('\n'				)				)
       self.assertTrue(_is_whitespace('\u00A0'				)				)

       self.assertFalse(_is_whitespace('A'				)				)
       self.assertFalse(_is_whitespace('-'				)				)




      def      _snake_case	(				self:       Tuple				):
       self.assertTrue(_is_control('\u0005'				)				)

       self.assertFalse(_is_control('A'				)				)
       self.assertFalse(_is_control(' '				)				)
       self.assertFalse(_is_control('\t'				)				)
       self.assertFalse(_is_control('\r'				)				)




      def      _snake_case	(				self:       str				):
       self.assertTrue(_is_punctuation('-'				)				)
       self.assertTrue(_is_punctuation('$'				)				)
       self.assertTrue(_is_punctuation('`'				)				)
       self.assertTrue(_is_punctuation('.'				)				)

       self.assertFalse(_is_punctuation('A'				)				)
       self.assertFalse(_is_punctuation(' '				)				)




      def      _snake_case	(				self:       Tuple				):
       __lowerCamelCase		:							Tuple							=						self.get_tokenizer()
       __lowerCamelCase		:							int							=						self.get_rust_tokenizer()

       # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
       self.assertListEqual([tokenizer.tokenize(_snake_case				) for t in ['Test', '\xad', 'test']]						,      [['[UNK]'], [], ['[UNK]']]				)

       self.assertListEqual(
           [rust_tokenizer.tokenize(_snake_case				) for t in ['Test', '\xad', 'test']]						,      [['[UNK]'], [], ['[UNK]']]				)




      @slow
      def      _snake_case	(				self:       Optional[Any]				):
       __lowerCamelCase		:							Optional[Any]							=						self.tokenizer_class.from_pretrained('google/electra-base-discriminator'				)

       __lowerCamelCase		:							Any							=						tokenizer.encode('sequence builders'						,      add_special_tokens=_snake_case				)
       __lowerCamelCase		:							List[Any]							=						tokenizer.encode('multi-sequence build'						,      add_special_tokens=_snake_case				)

       __lowerCamelCase		:							Optional[int]							=						tokenizer.build_inputs_with_special_tokens(_snake_case				)
       __lowerCamelCase		:							Any							=						tokenizer.build_inputs_with_special_tokens(_snake_case						,      _snake_case				)

       assert encoded_sentence == [101] + text + [102]
       assert encoded_pair == [101] + text + [102] + text_a + [102]




      def      _snake_case	(				self:       Any				):






       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'				):
         __lowerCamelCase		:							Optional[int]							=						self.rust_tokenizer_class.from_pretrained(_snake_case						,      **_snake_case				)

         __lowerCamelCase		:							Tuple							=						F'A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'
         __lowerCamelCase		:							Dict							=						tokenizer_r.encode_plus(
             _snake_case						,      return_attention_mask=_snake_case						,      return_token_type_ids=_snake_case						,      return_offsets_mapping=_snake_case						,      add_special_tokens=_snake_case						,      )

         __lowerCamelCase		:							Any							=						tokenizer_r.do_lower_case if hasattr(_snake_case						,      'do_lower_case'				) else False
         __lowerCamelCase		:							Union[str, Any]							=						(
             [
                 ((0, 0), tokenizer_r.cls_token),
                 ((0, 1), 'A'),
                 ((1, 2), ','),
                 ((3, 5), 'na'),
                 ((5, 6), '##ï'),
                 ((6, 8), '##ve'),
                 ((9, 15), tokenizer_r.mask_token),
                 ((16, 21), 'Allen'),
                 ((21, 23), '##NL'),
                 ((23, 24), '##P'),
                 ((25, 33), 'sentence'),
                 ((33, 34), '.'),
                 ((0, 0), tokenizer_r.sep_token),
             ]
             if not do_lower_case
             else [
                 ((0, 0), tokenizer_r.cls_token),
                 ((0, 1), 'a'),
                 ((1, 2), ','),
                 ((3, 8), 'naive'),
                 ((9, 15), tokenizer_r.mask_token),
                 ((16, 21), 'allen'),
                 ((21, 23), '##nl'),
                 ((23, 24), '##p'),
                 ((25, 33), 'sentence'),
                 ((33, 34), '.'),
                 ((0, 0), tokenizer_r.sep_token),
             ]
         )

         self.assertEqual(
             [e[1] for e in expected_results]						,      tokenizer_r.convert_ids_to_tokens(tokens['input_ids']				)				)
         self.assertEqual([e[0] for e in expected_results]						,      tokens['offset_mapping']				)




      def      _snake_case	(				self:       Union[str, Any]				):
       __lowerCamelCase		:							List[str]							=						['的', '人', '有']
       __lowerCamelCase		:							str							=						''.join(_snake_case				)
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'				):
         __lowerCamelCase		:							List[Any]							=						True
         __lowerCamelCase		:							str							=						self.tokenizer_class.from_pretrained(_snake_case						,      **_snake_case				)
         __lowerCamelCase		:							Tuple							=						self.rust_tokenizer_class.from_pretrained(_snake_case						,      **_snake_case				)

         __lowerCamelCase		:							Any							=						tokenizer_p.encode(_snake_case						,      add_special_tokens=_snake_case				)
         __lowerCamelCase		:							int							=						tokenizer_r.encode(_snake_case						,      add_special_tokens=_snake_case				)

         __lowerCamelCase		:							str							=						tokenizer_r.convert_ids_to_tokens(_snake_case				)
         __lowerCamelCase		:							Union[str, Any]							=						tokenizer_p.convert_ids_to_tokens(_snake_case				)

         # it is expected that each Chinese character is not preceded by "##"
         self.assertListEqual(_snake_case						,      _snake_case				)
         self.assertListEqual(_snake_case						,      _snake_case				)

         __lowerCamelCase		:							Union[str, Any]							=						False
         __lowerCamelCase		:							int							=						self.rust_tokenizer_class.from_pretrained(_snake_case						,      **_snake_case				)
         __lowerCamelCase		:							Union[str, Any]							=						self.tokenizer_class.from_pretrained(_snake_case						,      **_snake_case				)

         __lowerCamelCase		:							List[Any]							=						tokenizer_r.encode(_snake_case						,      add_special_tokens=_snake_case				)
         __lowerCamelCase		:							Tuple							=						tokenizer_p.encode(_snake_case						,      add_special_tokens=_snake_case				)

         __lowerCamelCase		:							int							=						tokenizer_r.convert_ids_to_tokens(_snake_case				)
         __lowerCamelCase		:							List[str]							=						tokenizer_p.convert_ids_to_tokens(_snake_case				)

         # it is expected that only the first Chinese character is not preceded by "##".
         __lowerCamelCase		:							Optional[int]							=						[
             F'##{token}' if idx != 0 else token for idx, token in enumerate(_snake_case				)
         ]
         self.assertListEqual(_snake_case						,      _snake_case				)
         self.assertListEqual(_snake_case						,      _snake_case				)








"""simple docstring"""
import torch

from diffusers import HeunDiscreteScheduler
from diffusers.utils import torch_device

from .test_schedulers import SchedulerCommonTest







class 	a				(					a__   ):
 snake_case__    	=    (HeunDiscreteScheduler,)
 snake_case__    	=    1_0



 def 					UpperCamelCase__   (			self							,    **_snake_case			):







  """simple docstring"""






  lowerCAmelCase  							=      {
      'num_train_timesteps': 11_00,
      'beta_start': 0.0_001,
      'beta_end': 0.02,
      'beta_schedule': 'linear',
  }

  config.update(**_snake_case			)
  return config



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  for timesteps in [10, 50, 1_00, 10_00]:
   self.check_over_configs(num_train_timesteps=_snake_case			)



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  for beta_start, beta_end in zip([0.00_001, 0.0_001, 0.001]							,    [0.0_002, 0.002, 0.02]			):
   self.check_over_configs(beta_start=_snake_case							,    beta_end=_snake_case			)



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  for schedule in ["linear", "scaled_linear", "exp"]:
   self.check_over_configs(beta_schedule=_snake_case			)



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  for clip_sample_range in [1.0, 2.0, 3.0]:
   self.check_over_configs(clip_sample_range=_snake_case							,    clip_sample=_snake_case			)



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  for prediction_type in ["epsilon", "v_prediction", "sample"]:
   self.check_over_configs(prediction_type=_snake_case			)



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  lowerCAmelCase  							=      self.scheduler_classes[0]
  lowerCAmelCase  							=      self.get_scheduler_config()
  lowerCAmelCase  							=      scheduler_class(**_snake_case			)

  scheduler.set_timesteps(self.num_inference_steps			)

  lowerCAmelCase  							=      self.dummy_model()
  lowerCAmelCase  							=      self.dummy_sample_deter * scheduler.init_noise_sigma
  lowerCAmelCase  							=      sample.to(_snake_case			)

  for i, t in enumerate(scheduler.timesteps			):
   lowerCAmelCase  							=      scheduler.scale_model_input(_snake_case							,    _snake_case			)

   lowerCAmelCase  							=      model(_snake_case							,    _snake_case			)

   lowerCAmelCase  							=      scheduler.step(_snake_case							,    _snake_case							,    _snake_case			)
   lowerCAmelCase  							=      output.prev_sample

  lowerCAmelCase  							=      torch.sum(torch.abs(_snake_case			)			)
  lowerCAmelCase  							=      torch.mean(torch.abs(_snake_case			)			)

  if torch_device in ["cpu", "mps"]:
   assert abs(result_sum.item() - 0.1_233			) < 1E-2
   assert abs(result_mean.item() - 0.0_002			) < 1E-3
  else:
   # CUDA
   assert abs(result_sum.item() - 0.1_233			) < 1E-2
   assert abs(result_mean.item() - 0.0_002			) < 1E-3



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  lowerCAmelCase  							=      self.scheduler_classes[0]
  lowerCAmelCase  							=      self.get_scheduler_config(prediction_type='v_prediction'			)
  lowerCAmelCase  							=      scheduler_class(**_snake_case			)

  scheduler.set_timesteps(self.num_inference_steps			)

  lowerCAmelCase  							=      self.dummy_model()
  lowerCAmelCase  							=      self.dummy_sample_deter * scheduler.init_noise_sigma
  lowerCAmelCase  							=      sample.to(_snake_case			)

  for i, t in enumerate(scheduler.timesteps			):
   lowerCAmelCase  							=      scheduler.scale_model_input(_snake_case							,    _snake_case			)

   lowerCAmelCase  							=      model(_snake_case							,    _snake_case			)

   lowerCAmelCase  							=      scheduler.step(_snake_case							,    _snake_case							,    _snake_case			)
   lowerCAmelCase  							=      output.prev_sample

  lowerCAmelCase  							=      torch.sum(torch.abs(_snake_case			)			)
  lowerCAmelCase  							=      torch.mean(torch.abs(_snake_case			)			)

  if torch_device in ["cpu", "mps"]:
   assert abs(result_sum.item() - 4.69_34E-07			) < 1E-2
   assert abs(result_mean.item() - 6.11_12E-10			) < 1E-3
  else:
   # CUDA
   assert abs(result_sum.item() - 4.6_93_42_86_50_17_09_72E-07			) < 1E-2
   assert abs(result_mean.item() - 0.0_002			) < 1E-3



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  lowerCAmelCase  							=      self.scheduler_classes[0]
  lowerCAmelCase  							=      self.get_scheduler_config()
  lowerCAmelCase  							=      scheduler_class(**_snake_case			)

  scheduler.set_timesteps(self.num_inference_steps							,    device=_snake_case			)

  lowerCAmelCase  							=      self.dummy_model()
  lowerCAmelCase  							=      self.dummy_sample_deter.to(_snake_case			) * scheduler.init_noise_sigma

  for t in scheduler.timesteps:
   lowerCAmelCase  							=      scheduler.scale_model_input(_snake_case							,    _snake_case			)

   lowerCAmelCase  							=      model(_snake_case							,    _snake_case			)

   lowerCAmelCase  							=      scheduler.step(_snake_case							,    _snake_case							,    _snake_case			)
   lowerCAmelCase  							=      output.prev_sample

  lowerCAmelCase  							=      torch.sum(torch.abs(_snake_case			)			)
  lowerCAmelCase  							=      torch.mean(torch.abs(_snake_case			)			)

  if str(_snake_case			).startswith('cpu'			):
   # The following sum varies between 148 and 156 on mps. Why?
   assert abs(result_sum.item() - 0.1_233			) < 1E-2
   assert abs(result_mean.item() - 0.0_002			) < 1E-3
  elif str(_snake_case			).startswith('mps'			):
   # Larger tolerance on mps
   assert abs(result_mean.item() - 0.0_002			) < 1E-2
  else:
   # CUDA
   assert abs(result_sum.item() - 0.1_233			) < 1E-2
   assert abs(result_mean.item() - 0.0_002			) < 1E-3



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  lowerCAmelCase  							=      self.scheduler_classes[0]
  lowerCAmelCase  							=      self.get_scheduler_config()
  lowerCAmelCase  							=      scheduler_class(**_snake_case							,    use_karras_sigmas=_snake_case			)

  scheduler.set_timesteps(self.num_inference_steps							,    device=_snake_case			)

  lowerCAmelCase  							=      self.dummy_model()
  lowerCAmelCase  							=      self.dummy_sample_deter.to(_snake_case			) * scheduler.init_noise_sigma
  lowerCAmelCase  							=      sample.to(_snake_case			)

  for t in scheduler.timesteps:
   lowerCAmelCase  							=      scheduler.scale_model_input(_snake_case							,    _snake_case			)

   lowerCAmelCase  							=      model(_snake_case							,    _snake_case			)

   lowerCAmelCase  							=      scheduler.step(_snake_case							,    _snake_case							,    _snake_case			)
   lowerCAmelCase  							=      output.prev_sample

  lowerCAmelCase  							=      torch.sum(torch.abs(_snake_case			)			)
  lowerCAmelCase  							=      torch.mean(torch.abs(_snake_case			)			)

  assert abs(result_sum.item() - 0.00_015			) < 1E-2
  assert abs(result_mean.item() - 1.98_69_55_45_35_03_46_95E-07			) < 1E-2





