



'''simple docstring'''




from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest

@require_tokenizers
class     UpperCamelCase_				(							__magic_name__    ):
	lowercase    =				DistilBertTokenizer
	lowercase    =				DistilBertTokenizerFast
	lowercase    =				True





	@slow
	def 				_lowercase(						self					)    ->    Optional[Any]:
								UpperCAmelCase  :	Optional[Any]							  =	DistilBertTokenizer.from_pretrained("""distilbert-base-uncased"""					)

								UpperCAmelCase  :	List[Any]							  =	tokenizer.encode("""sequence builders"""	,	add_special_tokens=A					)
								UpperCAmelCase  :	Optional[int]							  =	tokenizer.encode("""multi-sequence build"""	,	add_special_tokens=A					)

								UpperCAmelCase  :	int							  =	tokenizer.build_inputs_with_special_tokens(A					)
								UpperCAmelCase  :	int							  =	tokenizer.build_inputs_with_special_tokens(A	,	A					)

								assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
								assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
								    tokenizer.sep_token_id
								]






'''simple docstring'''




from collections.abc import Callable

import numpy as np



def    __lowerCamelCase						(      _lowercase			,       _lowercase			,       _lowercase			,       _lowercase			,       _lowercase	)   ->    np.array:
							UpperCAmelCase  :	Optional[Any]							  =	int(np.ceil((x_end - xa) / step_size	)	)
							UpperCAmelCase  :	str							  =	np.zeros((n + 1,)	)
							UpperCAmelCase  :	Optional[Any]							  =	ya
							UpperCAmelCase  :	Union[str, Any]							  =	xa

							for k in range(_lowercase	):
														UpperCAmelCase  :	Dict							  =	y[k] + step_size * ode_func(_lowercase			,       y[k]	)
														UpperCAmelCase  :	Optional[int]							  =	y[k] + (
														    (step_size / 2) * (ode_func(_lowercase			,       y[k]	) + ode_func(x + step_size			,       _lowercase	))
														)
														x += step_size

							return y


if __name__ == "__main__":
							import doctest

							doctest.testmod()

