


'''simple docstring'''

import tempfile

import torch

from diffusers import (
    DEISMultistepScheduler,
    DPMSolverMultistepScheduler,
    DPMSolverSinglestepScheduler,
    UniPCMultistepScheduler,
)

from .test_schedulers import SchedulerCommonTest
class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     int  					=							(DPMSolverSinglestepScheduler,)
      lowerCAmelCase__					:     Optional[int]  					=							(("""num_inference_steps""", 25),)



      def       UpperCamelCase__		(self    :    Optional[int]   ,						**UpperCamelCase    :    Union[str, Any] ):

             '''simple docstring'''







             lowercase__      			= {
                 '''num_train_timesteps''': 1000,
                 '''beta_start''': 0.00_01,
                 '''beta_end''': 0.02,
                 '''beta_schedule''': '''linear''',
                 '''solver_order''': 2,
                 '''prediction_type''': '''epsilon''',
                 '''thresholding''': False,
                 '''sample_max_value''': 1.0,
                 '''algorithm_type''': '''dpmsolver++''',
                 '''solver_type''': '''midpoint''',
                 '''lambda_min_clipped''': -float('''inf''' ),
                 '''variance_type''': None,
             }

             config.update(**UpperCamelCase )
             return config



      def       UpperCamelCase__		(self    :    int   ,						UpperCamelCase    :    Tuple=0   ,						**UpperCamelCase    :    int ):

             '''simple docstring'''







             lowercase__      			= dict(self.forward_default_kwargs )
             lowercase__      			= kwargs.pop('''num_inference_steps'''   ,						UpperCamelCase )
             lowercase__      			= self.dummy_sample
             lowercase__      			= 0.1 * sample
             lowercase__      			= [residual + 0.2, residual + 0.15, residual + 0.10]

             for scheduler_class in self.scheduler_classes:
                    lowercase__      			= self.get_scheduler_config(**UpperCamelCase )
                    lowercase__      			= scheduler_class(**UpperCamelCase )
                    scheduler.set_timesteps(UpperCamelCase )
                    # copy over dummy past residuals
                    lowercase__      			= dummy_past_residuals[: scheduler.config.solver_order]

                    with tempfile.TemporaryDirectory() as tmpdirname:
                           scheduler.save_config(UpperCamelCase )
                           lowercase__      			= scheduler_class.from_pretrained(UpperCamelCase )
                           new_scheduler.set_timesteps(UpperCamelCase )
                           # copy over dummy past residuals
                           lowercase__      			= dummy_past_residuals[: new_scheduler.config.solver_order]

                    lowercase__			,lowercase__      			= sample, sample
                    for t in range(UpperCamelCase   ,						time_step + scheduler.config.solver_order + 1 ):
                           lowercase__      			= scheduler.step(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						**UpperCamelCase ).prev_sample
                           lowercase__      			= new_scheduler.step(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						**UpperCamelCase ).prev_sample

                           assert torch.sum(torch.abs(output - new_output ) ) < 1E-5, "Scheduler outputs are not identical"



      def       UpperCamelCase__		(self    :    str ):

             '''simple docstring'''







             pass



      def       UpperCamelCase__		(self    :    List[Any]   ,						UpperCamelCase    :    Union[str, Any]=0   ,						**UpperCamelCase    :    Optional[int] ):

             '''simple docstring'''







             lowercase__      			= dict(self.forward_default_kwargs )
             lowercase__      			= kwargs.pop('''num_inference_steps'''   ,						UpperCamelCase )
             lowercase__      			= self.dummy_sample
             lowercase__      			= 0.1 * sample
             lowercase__      			= [residual + 0.2, residual + 0.15, residual + 0.10]

             for scheduler_class in self.scheduler_classes:
                    lowercase__      			= self.get_scheduler_config()
                    lowercase__      			= scheduler_class(**UpperCamelCase )
                    scheduler.set_timesteps(UpperCamelCase )

                    # copy over dummy past residuals (must be after setting timesteps)
                    lowercase__      			= dummy_past_residuals[: scheduler.config.solver_order]

                    with tempfile.TemporaryDirectory() as tmpdirname:
                           scheduler.save_config(UpperCamelCase )
                           lowercase__      			= scheduler_class.from_pretrained(UpperCamelCase )
                           # copy over dummy past residuals
                           new_scheduler.set_timesteps(UpperCamelCase )

                           # copy over dummy past residual (must be after setting timesteps)
                           lowercase__      			= dummy_past_residuals[: new_scheduler.config.solver_order]

                    lowercase__      			= scheduler.step(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						**UpperCamelCase ).prev_sample
                    lowercase__      			= new_scheduler.step(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						**UpperCamelCase ).prev_sample

                    assert torch.sum(torch.abs(output - new_output ) ) < 1E-5, "Scheduler outputs are not identical"



      def       UpperCamelCase__		(self    :    Dict   ,						UpperCamelCase    :    Union[str, Any]=None   ,						**UpperCamelCase    :    Any ):

             '''simple docstring'''







             if scheduler is None:
                    lowercase__      			= self.scheduler_classes[0]
                    lowercase__      			= self.get_scheduler_config(**UpperCamelCase )
                    lowercase__      			= scheduler_class(**UpperCamelCase )

             lowercase__      			= self.scheduler_classes[0]
             lowercase__      			= self.get_scheduler_config(**UpperCamelCase )
             lowercase__      			= scheduler_class(**UpperCamelCase )

             lowercase__      			= 10
             lowercase__      			= self.dummy_model()
             lowercase__      			= self.dummy_sample_deter
             scheduler.set_timesteps(UpperCamelCase )

             for i, t in enumerate(scheduler.timesteps ):
                    lowercase__      			= model(UpperCamelCase   ,						UpperCamelCase )
                    lowercase__      			= scheduler.step(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase ).prev_sample

             return sample



      def       UpperCamelCase__		(self    :    Any ):

             '''simple docstring'''







             lowercase__      			= DPMSolverSinglestepScheduler(**self.get_scheduler_config() )
             lowercase__      			= 50
             lowercase__      			= self.dummy_model()
             lowercase__      			= self.dummy_sample_deter
             scheduler.set_timesteps(UpperCamelCase )

             # make sure that the first t is uneven
             for i, t in enumerate(scheduler.timesteps[3:] ):
                    lowercase__      			= model(UpperCamelCase   ,						UpperCamelCase )
                    lowercase__      			= scheduler.step(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase ).prev_sample

             lowercase__      			= torch.mean(torch.abs(UpperCamelCase ) )

             assert abs(result_mean.item() - 0.25_74 ) < 1E-3



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             for timesteps in [25, 50, 100, 999, 1000]:
                    self.check_over_configs(num_train_timesteps=UpperCamelCase )



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             lowercase__      			= DPMSolverSinglestepScheduler(**self.get_scheduler_config() )
             lowercase__      			= self.full_loop(scheduler=UpperCamelCase )
             lowercase__      			= torch.mean(torch.abs(UpperCamelCase ) )

             assert abs(result_mean.item() - 0.27_91 ) < 1E-3

             lowercase__      			= DEISMultistepScheduler.from_config(scheduler.config )
             lowercase__      			= DPMSolverMultistepScheduler.from_config(scheduler.config )
             lowercase__      			= UniPCMultistepScheduler.from_config(scheduler.config )
             lowercase__      			= DPMSolverSinglestepScheduler.from_config(scheduler.config )

             lowercase__      			= self.full_loop(scheduler=UpperCamelCase )
             lowercase__      			= torch.mean(torch.abs(UpperCamelCase ) )

             assert abs(result_mean.item() - 0.27_91 ) < 1E-3



      def       UpperCamelCase__		(self    :    List[Any] ):

             '''simple docstring'''







             self.check_over_configs(thresholding=UpperCamelCase )
             for order in [1, 2, 3]:
                    for solver_type in ["midpoint", "heun"]:
                           for threshold in [0.5, 1.0, 2.0]:
                                  for prediction_type in ["epsilon", "sample"]:
                                         self.check_over_configs(
                                             thresholding=UpperCamelCase   ,						prediction_type=UpperCamelCase   ,						sample_max_value=UpperCamelCase   ,						algorithm_type='''dpmsolver++'''   ,						solver_order=UpperCamelCase   ,						solver_type=UpperCamelCase   ,						)



      def       UpperCamelCase__		(self    :    List[Any] ):

             '''simple docstring'''







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



      def       UpperCamelCase__		(self    :    List[Any] ):

             '''simple docstring'''







             for algorithm_type in ["dpmsolver", "dpmsolver++"]:
                    for solver_type in ["midpoint", "heun"]:
                           for order in [1, 2, 3]:
                                  for prediction_type in ["epsilon", "sample"]:
                                         self.check_over_configs(
                                             solver_order=UpperCamelCase   ,						solver_type=UpperCamelCase   ,						prediction_type=UpperCamelCase   ,						algorithm_type=UpperCamelCase   ,						)
                                         lowercase__      			= self.full_loop(
                                             solver_order=UpperCamelCase   ,						solver_type=UpperCamelCase   ,						prediction_type=UpperCamelCase   ,						algorithm_type=UpperCamelCase   ,						)
                                         assert not torch.isnan(UpperCamelCase ).any(), "Samples have nan numbers"



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             self.check_over_configs(lower_order_final=UpperCamelCase )
             self.check_over_configs(lower_order_final=UpperCamelCase )



      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             self.check_over_configs(lambda_min_clipped=-float('''inf''' ) )
             self.check_over_configs(lambda_min_clipped=-5.1 )



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             self.check_over_configs(variance_type=UpperCamelCase )
             self.check_over_configs(variance_type='''learned_range''' )



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             for num_inference_steps in [1, 2, 3, 5, 10, 50, 100, 999, 1000]:
                    self.check_over_forward(num_inference_steps=UpperCamelCase   ,						time_step=0 )



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             lowercase__      			= self.full_loop()
             lowercase__      			= torch.mean(torch.abs(UpperCamelCase ) )

             assert abs(result_mean.item() - 0.27_91 ) < 1E-3



      def       UpperCamelCase__		(self    :    List[Any] ):

             '''simple docstring'''







             lowercase__      			= self.full_loop(use_karras_sigmas=UpperCamelCase )
             lowercase__      			= torch.mean(torch.abs(UpperCamelCase ) )

             assert abs(result_mean.item() - 0.22_48 ) < 1E-3



      def       UpperCamelCase__		(self    :    List[Any] ):

             '''simple docstring'''







             lowercase__      			= self.full_loop(prediction_type='''v_prediction''' )
             lowercase__      			= torch.mean(torch.abs(UpperCamelCase ) )

             assert abs(result_mean.item() - 0.14_53 ) < 1E-3



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             lowercase__      			= self.full_loop(prediction_type='''v_prediction'''   ,						use_karras_sigmas=UpperCamelCase )
             lowercase__      			= torch.mean(torch.abs(UpperCamelCase ) )

             assert abs(result_mean.item() - 0.06_49 ) < 1E-3






      def       UpperCamelCase__		(self    :    str ):

             '''simple docstring'''







             lowercase__      			= self.scheduler_classes[0]
             lowercase__      			= self.get_scheduler_config(thresholding=UpperCamelCase   ,						dynamic_thresholding_ratio=0 )
             lowercase__      			= scheduler_class(**UpperCamelCase )

             lowercase__      			= 10
             lowercase__      			= self.dummy_model()
             lowercase__      			= self.dummy_sample_deter.half()
             scheduler.set_timesteps(UpperCamelCase )

             for i, t in enumerate(scheduler.timesteps ):
                    lowercase__      			= model(UpperCamelCase   ,						UpperCamelCase )
                    lowercase__      			= scheduler.step(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase ).prev_sample

             assert sample.dtype == torch.floataa








'''simple docstring'''

import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase							:   List[str]  						=	get_tests_dir('fixtures/spiece.model')
@require_sentencepiece
@require_tokenizers
class   __lowerCAmelCase						(lowercase_  ,     unittest.TestCase     ):





      '''simple docstring'''






      lowerCAmelCase__					:     int  					=							DebertaVaTokenizer
      lowerCAmelCase__					:     List[Any]  					=							DebertaVaTokenizerFast
      lowerCAmelCase__					:     str  					=							True
      lowerCAmelCase__					:     Tuple  					=							True



      def       UpperCamelCase__		(self    :    Tuple ):

             '''simple docstring'''







             super().setUp()

             # We have a SentencePiece fixture for testing
             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						unk_token='''<unk>''' )
             tokenizer.save_pretrained(self.tmpdirname )



      def       UpperCamelCase__		(self    :    Union[str, Any]   ,						UpperCamelCase    :    str ):

             '''simple docstring'''







             lowercase__      			= '''this is a test'''
             lowercase__      			= '''this is a test'''
             return input_text, output_text



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             lowercase__      			= '''<pad>'''
             lowercase__      			= 0

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



      def       UpperCamelCase__		(self    :    Dict ):

             '''simple docstring'''







             lowercase__      			= list(self.get_tokenizer().get_vocab().keys() )
             self.assertEqual(vocab_keys[0]   ,						'''<pad>''' )
             self.assertEqual(vocab_keys[1]   ,						'''<unk>''' )
             self.assertEqual(vocab_keys[-1]   ,						'''[PAD]''' )
             self.assertEqual(len(UpperCamelCase )   ,						30001 )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             self.assertEqual(self.get_tokenizer().vocab_size   ,						30000 )



      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             lowercase__      			= ''' \tHeLLo!how  \n Are yoU?  '''
             lowercase__      			= ['''▁hello''', '''!''', '''how''', '''▁are''', '''▁you''', '''?''']
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.''' )
      def       UpperCamelCase__		(self    :    List[Any] ):

             '''simple docstring'''







             pass



      @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.''' )
      def       UpperCamelCase__		(self    :    List[str] ):

             '''simple docstring'''







             pass



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    Union[str, Any] ):

             '''simple docstring'''







             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    Union[str, Any] ):

             '''simple docstring'''







             lowercase__      			= ''' \tHeLLo!how  \n Are yoU?  '''
             lowercase__      			= ['''▁''', '''<unk>''', '''e''', '''<unk>''', '''o''', '''!''', '''how''', '''▁''', '''<unk>''', '''re''', '''▁yo''', '''<unk>''', '''?''']
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    Union[str, Any] ):

             '''simple docstring'''







             lowercase__      			= self.get_tokenizer()
             lowercase__      			= self.get_rust_tokenizer()

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

             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             lowercase__      			= rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= self.get_rust_tokenizer()
             lowercase__      			= tokenizer.encode(UpperCamelCase )
             lowercase__      			= rust_tokenizer.encode(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= '''This is a test'''
             lowercase__      			= [13, 1, 4398, 25, 21, 1289]
             lowercase__      			= ['''▁''', '''T''', '''his''', '''▁is''', '''▁a''', '''▁test''']
             lowercase__      			= ['''▁''', '''<unk>''', '''his''', '''▁is''', '''▁a''', '''▁test''']

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						keep_accents=UpperCamelCase )
             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						keep_accents=UpperCamelCase )

             lowercase__      			= tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= tokenizer.tokenize(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= rust_tokenizer.tokenize(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             # fmt: off
             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= [13, 1, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]
             lowercase__      			= ['''▁''', '''I''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''', ]
             lowercase__      			= ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
             # fmt: on

             lowercase__      			= tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= tokenizer.tokenize(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= rust_tokenizer.tokenize(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= DebertaVaTokenizer(UpperCamelCase )

             lowercase__      			= tokenizer.encode('''sequence builders''' )
             lowercase__      			= tokenizer.encode('''multi-sequence build''' )

             lowercase__      			= tokenizer.build_inputs_with_special_tokens(UpperCamelCase )
             lowercase__      			= tokenizer.build_inputs_with_special_tokens(UpperCamelCase   ,						UpperCamelCase )

             self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]   ,						UpperCamelCase )
             self.assertEqual(
                 [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]   ,						UpperCamelCase   ,						)






      @slow
      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= {'''input_ids''': [[1, 39867, 36, 19390, 486, 27, 35052, 81436, 18, 60685, 1225, 7, 35052, 81436, 18, 9367, 16899, 18, 15937, 53, 594, 773, 18, 16287, 30465, 36, 15937, 6, 41139, 38, 36979, 60763, 191, 6, 34132, 99, 6, 50538, 390, 43230, 6, 34132, 2779, 20850, 14, 699, 1072, 1194, 36, 382, 10901, 53, 7, 699, 1072, 2084, 36, 20422, 630, 53, 19, 105, 3049, 1896, 1053, 16899, 1506, 11, 37978, 4243, 7, 1237, 31869, 200, 16566, 654, 6, 35052, 81436, 7, 55630, 13593, 4, 2], [1, 26, 15011, 13, 667, 8, 1053, 18, 23611, 1237, 72356, 12820, 34, 104134, 1209, 35, 13313, 6627, 21, 202, 347, 7, 164, 2399, 11, 46, 4485, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 5, 1232, 2864, 15785, 14951, 105, 5, 8581, 1250, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''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, 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], [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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
             # fmt: on

             self.tokenizer_integration_test_util(
                 expected_encoding=UpperCamelCase   ,						model_name='''microsoft/deberta-v2-xlarge'''   ,						revision='''ad6e42c1532ddf3a15c39246b63f5559d558b670'''   ,						)




