



'''simple docstring'''



from dataclasses import dataclass, field
from typing import Optional
@dataclass
class 	lowerCamelCase_							:
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot'    ,				metadata={'help': 'Model name or path of model to be trained.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='./'    ,				metadata={'help': 'Save dir where model repo is cloned and models updates are saved to.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot-clean-train'    ,				metadata={'help': 'Name or path of training dataset.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot-clean-valid'    ,				metadata={'help': 'Name or path of validation dataset.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=2    ,				metadata={'help': 'Batch size for training.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=2    ,				metadata={'help': 'Batch size for evaluation.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(default=0.1    ,				metadata={'help': 'Value of weight decay.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=1_0_0_0_0    ,				metadata={'help': 'Size of buffer used to shuffle streaming dataset.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(default=2E-4    ,				metadata={'help': 'Learning rate fo training.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(default='cosine'    ,				metadata={'help': 'Learning rate.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=7_5_0    ,				metadata={'help': 'Number of warmup steps in the learning rate schedule.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=1_6    ,				metadata={'help': 'Number of gradient accumulation steps.'}			)
						_lowerCAmelCase     :   Optional[bool]	     =				field(
						    default=snake_case_    ,				metadata={'help': 'Use gradient checkpointing to reduce memory footprint.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=5_0_0_0_0    ,				metadata={'help': 'Maximum number of training steps.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=-1    ,				metadata={'help': 'Maximum number of evaluation steps. If -1 the full dataset is evaluated.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=1_0_2_4    ,				metadata={'help': 'Sequence lengths used for training.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=1    ,				metadata={'help': 'Training seed.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=1_0_2_4    ,				metadata={'help': 'Interval to save checkpoints. Measured as number of forward passes not training steps.'}    ,				)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default=snake_case_    ,				metadata={'help': 'States path if the training should continue from a checkpoint folder.'}			)
						_lowerCAmelCase     :   Optional[bool]	     =				field(default=snake_case_    ,				metadata={'help': 'If True the data is pretokenized.'}			)


@dataclass
class 	lowerCamelCase_							:
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot'    ,				metadata={'help': 'Model name or path of model to be evaluated.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot-clean-valid'    ,				metadata={'help': 'Name or path of validation dataset.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=2    ,				metadata={'help': 'Batch size used for evaluation.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=-1    ,				metadata={'help': 'Maximum number of evaluation steps. If -1 the full dataset is evaluated.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=1_0_2_4    ,				metadata={'help': 'Length of sequences to be evaluated.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=1    ,				metadata={'help': 'Random seed used for evaluation.'}			)


@dataclass
class 	lowerCamelCase_							:
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot'    ,				metadata={'help': 'Model name or path of model to be evaluated.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=snake_case_    ,				metadata={'help': 'Number of workers used for code evaluation.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=snake_case_    ,				metadata={'help': 'The number of human-eval tasks to run. If not included all tasks are evaluated.'}    ,				)
						_lowerCAmelCase     :   Optional[bool]	     =				field(
						    default=snake_case_    ,				metadata={'help': 'Sample from the language model\'s output distribution.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(default=0.2    ,				metadata={'help': 'Sampling temperature used for generation.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=2_5_6    ,				metadata={'help': 'Maximum number of newly generated tokens.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=0    ,				metadata={'help': 'Top-k parameter used for generation.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(default=0.95    ,				metadata={'help': 'Top-p parameter used for nucleus sampling.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=1_0    ,				metadata={'help': 'Number of generations to run in parallel.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=2_0_0    ,				metadata={'help': 'Number of completions to generate for each sample.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=1    ,				metadata={'help': 'Random seed used for evaluation.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='eval_results.json'    ,				metadata={'help': 'Random seed used for evaluation.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='0'    ,				metadata={'help': 'Allow `code_eval` to execute Python code on machine'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=-1    ,				metadata={
						        'help': (
						            'Determine which device to run the `text-generation` Pipeline on. -1 is CPU and any zero or positive'
						            ' number corresponds to which GPU device id to run on.'
						        )
						    }    ,				)


@dataclass
class 	lowerCamelCase_							:
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=snake_case_    ,				metadata={
						        'help': 'The number of CPU cores to use for parallel preprocessing. Default uses the maximum available.'
						    }    ,				)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='transformersbook/codeparrot'    ,				metadata={'help': 'Folder or name of dataset to process.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot-clean'    ,				metadata={'help': 'Folder to save processed processed dataset.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=1_0_0_0_0_0    ,				metadata={'help': 'Number of files to save per JSON output file.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(default='content'    ,				metadata={'help': 'Column containing text data to process.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(
						    default=1_0_0_0    ,				metadata={'help': 'Maximum line length in file, otherwise file is filtered.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(
						    default=1_0_0    ,				metadata={'help': 'Maximum mean line length in file, otherwise file is filtered.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(
						    default=0.25    ,				metadata={'help': 'Maximum fraction of non-alphanumeric characters, otherwise file is filtered.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(
						    default=1.5    ,				metadata={'help': 'Minimum character token ratio for the file, otherwise file is filtered.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(
						    default=0.7    ,				metadata={'help': 'Probability for filtering config, test and uncommon files.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot'    ,				metadata={'help': 'Name or path to the tokenizer.'}    ,				)
						_lowerCAmelCase     :   Optional[bool]	     =				field(
						    default=snake_case_    ,				metadata={'help': 'If True, near-duplicate samples are removed.'}			)
						_lowerCAmelCase     :   Optional[float]	     =				field(
						    default=0.85    ,				metadata={'help': 'Jaccard threshold for near-duplicate samples.'}			)


@dataclass
class 	lowerCamelCase_							:
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='gpt2'    ,				metadata={'help': 'Base tokenizer to build new tokenizer from.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='transformersbook/codeparrot-train'    ,				metadata={'help': 'Dataset to train tokenizer on.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(default='content'    ,				metadata={'help': 'Column containing text data to process.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=2_0_0_0_0_0    ,				metadata={'help': 'Number of examples to train tokenizer on.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(
						    default=3_2_7_6_8    ,				metadata={'help': 'Number of examples to train the tokenizer on.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(default='codeparrot'    ,				metadata={'help': 'Name of new tokenizer.'}			)
						_lowerCAmelCase     :   Optional[bool]	     =				field(default=snake_case_    ,				metadata={'help': 'Push saved tokenizer to the hub.'}			)


@dataclass
class 	lowerCamelCase_							:
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot'    ,				metadata={'help': 'Name or path to the tokenizer.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot-clean-train'    ,				metadata={'help': 'Name or path to the dataset to pretokenize.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='tokenized-codeparrot-train'    ,				metadata={'help': 'Repo name of the pretokenized data.'}			)
						_lowerCAmelCase     :   Optional[int]	     =				field(default=snake_case_    ,				metadata={'help': 'Number of workers used for code evaluation.'}			)


@dataclass
class 	lowerCamelCase_							:
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='gpt2-large'    ,				metadata={'help': 'Configuration to use for model initialization.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(
						    default='codeparrot/codeparrot'    ,				metadata={'help': 'Tokenizer attached to model.'}			)
						_lowerCAmelCase     :   Optional[str]	     =				field(default='codeparrot'    ,				metadata={'help': 'Name of the created model.'}			)
						_lowerCAmelCase     :   Optional[bool]	     =				field(default=snake_case_    ,				metadata={'help': 'Push saved tokenizer to the hub.'}			)









'''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_     :       Dict								=						get_tests_dir('fixtures/spiece.model')
@require_sentencepiece
@require_tokenizers
class 	lowerCamelCase_							(					snake_case_    ,				unittest.TestCase			):
						_lowerCAmelCase     :   Union[str, Any]	     =				DebertaVaTokenizer
						_lowerCAmelCase     :   List[Any]	     =				DebertaVaTokenizerFast
						_lowerCAmelCase     :   Optional[Any]	     =				True
						_lowerCAmelCase     :   int	     =				True







						def 					__lowercase    (  self   :      Optional[Any]				):

													"""simple docstring"""
													super().setUp()

													# We have a SentencePiece fixture for testing
													SCREAMING_SNAKE_CASE					:      Tuple     					=			DebertaVaTokenizer(lowerCAmelCase__				,    unk_token='''<unk>'''				)
													tokenizer.save_pretrained(self.tmpdirname				)







						def 					__lowercase    (  self   :      List[str]				,    lowerCAmelCase__   :      Any				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      List[str]     					=			'''this is a test'''
													SCREAMING_SNAKE_CASE					:      Tuple     					=			'''this is a test'''
													return input_text, output_text







						def 					__lowercase    (  self   :      int				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			'''<pad>'''
													SCREAMING_SNAKE_CASE					:      Tuple     					=			0

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







						def 					__lowercase    (  self   :      Optional[int]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Tuple     					=			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(lowerCAmelCase__				)				,    3_00_01				)







						def 					__lowercase    (  self   :      str				):

													"""simple docstring"""
													self.assertEqual(self.get_tokenizer().vocab_size				,    3_00_00				)







						def 					__lowercase    (  self   :      List[str]				):

													"""simple docstring"""
													# fmt: off
													SCREAMING_SNAKE_CASE					:      int     					=			''' \tHeLLo!how  \n Are yoU?  '''
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			['''▁hello''', '''!''', '''how''', '''▁are''', '''▁you''', '''?''']
													# fmt: on

													SCREAMING_SNAKE_CASE					:      Any     					=			DebertaVaTokenizer(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Tuple     					=			tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Dict     					=			DebertaVaTokenizerFast(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







						@unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'''				)
						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													pass







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

													"""simple docstring"""
													pass







						def 					__lowercase    (  self   :      int				):

													"""simple docstring"""
													# fmt: off
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			'''I was born in 92000, and this is falsé.'''
													SCREAMING_SNAKE_CASE					:      Any     					=			['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
													# fmt: on

													SCREAMING_SNAKE_CASE					:      Dict     					=			DebertaVaTokenizer(lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			DebertaVaTokenizerFast(lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      str     					=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Optional[Any]				):

													"""simple docstring"""
													# fmt: off
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			'''I was born in 92000, and this is falsé.'''
													SCREAMING_SNAKE_CASE					:      List[str]     					=			['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
													# fmt: on

													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			DebertaVaTokenizer(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      int     					=			DebertaVaTokenizerFast(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Any     					=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Any				):

													"""simple docstring"""
													# fmt: off
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			'''I was born in 92000, and this is falsé.'''
													SCREAMING_SNAKE_CASE					:      Dict     					=			['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
													# fmt: on

													SCREAMING_SNAKE_CASE					:      Tuple     					=			DebertaVaTokenizer(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Any     					=			tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Any     					=			DebertaVaTokenizerFast(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													# fmt: off
													SCREAMING_SNAKE_CASE					:      str     					=			'''I was born in 92000, and this is falsé.'''
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
													# fmt: on

													SCREAMING_SNAKE_CASE					:      List[Any]     					=			DebertaVaTokenizer(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      str     					=			tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			DebertaVaTokenizerFast(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      List[str]     					=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







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

													"""simple docstring"""
													# fmt: off
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			''' \tHeLLo!how  \n Are yoU?  '''
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			['''▁''', '''<unk>''', '''e''', '''<unk>''', '''o''', '''!''', '''how''', '''▁''', '''<unk>''', '''re''', '''▁yo''', '''<unk>''', '''?''']
													# fmt: on

													SCREAMING_SNAKE_CASE					:      List[str]     					=			DebertaVaTokenizer(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Any     					=			DebertaVaTokenizerFast(lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				,    split_by_punct=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      List[str]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      List[str]     					=			self.get_tokenizer()
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			self.get_rust_tokenizer()

													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			'''I was born in 92000, and this is falsé.'''

													SCREAMING_SNAKE_CASE					:      Tuple     					=			tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)
													SCREAMING_SNAKE_CASE					:      List[str]     					=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      List[Any]     					=			tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      str     					=			rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Tuple     					=			self.get_rust_tokenizer()
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			tokenizer.encode(lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Any     					=			rust_tokenizer.encode(lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      List[str]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Tuple     					=			'''This is a test'''
													SCREAMING_SNAKE_CASE					:      List[str]     					=			[13, 1, 43_98, 25, 21, 12_89]
													SCREAMING_SNAKE_CASE					:      Tuple     					=			['''▁''', '''T''', '''his''', '''▁is''', '''▁a''', '''▁test''']
													SCREAMING_SNAKE_CASE					:      Any     					=			['''▁''', '''<unk>''', '''his''', '''▁is''', '''▁a''', '''▁test''']

													SCREAMING_SNAKE_CASE					:      List[str]     					=			DebertaVaTokenizer(lowerCAmelCase__				,    keep_accents=lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      str     					=			DebertaVaTokenizerFast(lowerCAmelCase__				,    keep_accents=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      List[Any]     					=			tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			tokenizer.tokenize(lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Any     					=			tokenizer.convert_ids_to_tokens(lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      List[str]     					=			rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      str     					=			rust_tokenizer.tokenize(lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Any     					=			rust_tokenizer.convert_ids_to_tokens(lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													# fmt: off
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			'''I was born in 92000, and this is falsé.'''
													SCREAMING_SNAKE_CASE					:      int     					=			[13, 1, 23, 3_86, 19, 5_61, 30_50, 15, 17, 48, 25, 82_56, 18, 1, 9]
													SCREAMING_SNAKE_CASE					:      Dict     					=			['''▁''', '''I''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''', ]
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
													# fmt: on

													SCREAMING_SNAKE_CASE					:      List[Any]     					=			tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Tuple     					=			tokenizer.tokenize(lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			tokenizer.convert_ids_to_tokens(lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      int     					=			rust_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Tuple     					=			rust_tokenizer.tokenize(lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			rust_tokenizer.convert_ids_to_tokens(lowerCAmelCase__				)
													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Any				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      str     					=			DebertaVaTokenizer(lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      List[str]     					=			tokenizer.encode('''sequence builders'''				)
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			tokenizer.encode('''multi-sequence build'''				)

													SCREAMING_SNAKE_CASE					:      List[Any]     					=			tokenizer.build_inputs_with_special_tokens(lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Tuple     					=			tokenizer.build_inputs_with_special_tokens(lowerCAmelCase__				,    lowerCAmelCase__				)

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







						@slow
						def 					__lowercase    (  self   :      Optional[Any]				):

													"""simple docstring"""
													# fmt: off
													SCREAMING_SNAKE_CASE					:      str     					=			{'''input_ids''': [[1, 3_98_67, 36, 1_93_90, 4_86, 27, 3_50_52, 8_14_36, 18, 6_06_85, 12_25, 7, 3_50_52, 8_14_36, 18, 93_67, 1_68_99, 18, 1_59_37, 53, 5_94, 7_73, 18, 1_62_87, 3_04_65, 36, 1_59_37, 6, 4_11_39, 38, 3_69_79, 6_07_63, 1_91, 6, 3_41_32, 99, 6, 5_05_38, 3_90, 4_32_30, 6, 3_41_32, 27_79, 2_08_50, 14, 6_99, 10_72, 11_94, 36, 3_82, 1_09_01, 53, 7, 6_99, 10_72, 20_84, 36, 2_04_22, 6_30, 53, 19, 1_05, 30_49, 18_96, 10_53, 1_68_99, 15_06, 11, 3_79_78, 42_43, 7, 12_37, 3_18_69, 2_00, 1_65_66, 6_54, 6, 3_50_52, 8_14_36, 7, 5_56_30, 1_35_93, 4, 2], [1, 26, 1_50_11, 13, 6_67, 8, 10_53, 18, 2_36_11, 12_37, 7_23_56, 1_28_20, 34, 10_41_34, 12_09, 35, 1_33_13, 66_27, 21, 2_02, 3_47, 7, 1_64, 23_99, 11, 46, 44_85, 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, 12_32, 28_64, 1_57_85, 1_49_51, 1_05, 5, 85_81, 12_50, 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=lowerCAmelCase__				,    model_name='''microsoft/deberta-v2-xlarge'''				,    revision='''ad6e42c1532ddf3a15c39246b63f5559d558b670'''				,    )




