





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

from ..bert.test_tokenization_bert import BertTokenizationTest






@require_tokenizers
class        _a(    __A    ):
		lowerCamelCase__     :int   				=		DistilBertTokenizer
		lowerCamelCase__     :Optional[Any]   				=		DistilBertTokenizerFast
		lowerCamelCase__     :Dict   				=		True







		@slow
		def        lowercase       (    self				)      ->      List[str]:


							'''simple docstring'''

							_snake_case       :					List[str]				       =   DistilBertTokenizer.from_pretrained("distilbert-base-uncased"				)

							_snake_case       :					str				       =   tokenizer.encode("sequence builders" ,						add_special_tokens=__snake_case				)
							_snake_case       :					Union[str, Any]				       =   tokenizer.encode("multi-sequence build" ,						add_special_tokens=__snake_case				)

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

							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
							]






import numpy as np

__lowerCAmelCase :Dict     =    [
    ['a', 'b', 'c', 'd', 'e'],
    ['f', 'g', 'h', 'i', 'k'],
    ['l', 'm', 'n', 'o', 'p'],
    ['q', 'r', 's', 't', 'u'],
    ['v', 'w', 'x', 'y', 'z'],
]






class        _a:







		def __init__(    self				)      ->      None:


							'''simple docstring'''

							_snake_case       :					Optional[Any]				       =   np.array(__snake_case				)







		def        lowercase       (    self ,						__snake_case				)      ->      np.ndarray:


							'''simple docstring'''

							_snake_case       , _snake_case       :					List[Any]				       =   np.where(letter == self.SQUARE				)
							_snake_case       :					Any				       =   np.concatenate([indexa + 1, indexa + 1]				)
							return indexes







		def        lowercase       (    self ,						__snake_case ,						__snake_case				)      ->      str:


							'''simple docstring'''

							_snake_case       :					int				       =   self.SQUARE[indexa - 1, indexa - 1]
							return letter







		def        lowercase       (    self ,						__snake_case				)      ->      str:


							'''simple docstring'''

							_snake_case       :					Optional[Any]				       =   message.lower()
							_snake_case       :					List[Any]				       =   message.replace(" " ,						""				)
							_snake_case       :					Any				       =   message.replace("j" ,						"i"				)

							_snake_case       :					Tuple				       =   np.empty((2, len(__snake_case				))				)
							for letter_index in range(len(__snake_case				)				):
												_snake_case       :					Dict				       =   self.letter_to_numbers(message[letter_index]				)

												_snake_case       :					Tuple				       =   numbers[0]
												_snake_case       :					List[Any]				       =   numbers[1]

							_snake_case       :					Any				       =   first_step.reshape(2 * len(__snake_case				)				)
							_snake_case       :					Optional[Any]				       =   ""
							for numbers_index in range(len(__snake_case				)				):
												_snake_case       :					Optional[int]				       =   int(second_step[numbers_index * 2]				)
												_snake_case       :					List[str]				       =   int(second_step[(numbers_index * 2) + 1]				)
												_snake_case       :					Any				       =   self.numbers_to_letter(__snake_case ,						__snake_case				)
												_snake_case       :					Any				       =   encoded_message + letter

							return encoded_message







		def        lowercase       (    self ,						__snake_case				)      ->      str:


							'''simple docstring'''

							_snake_case       :					Union[str, Any]				       =   message.lower()
							message.replace(" " ,						""				)
							_snake_case       :					Tuple				       =   np.empty(2 * len(__snake_case				)				)
							for letter_index in range(len(__snake_case				)				):
												_snake_case       :					Union[str, Any]				       =   self.letter_to_numbers(message[letter_index]				)
												_snake_case       :					Tuple				       =   numbers[0]
												_snake_case       :					Any				       =   numbers[1]

							_snake_case       :					Optional[Any]				       =   first_step.reshape((2, len(__snake_case				))				)
							_snake_case       :					Union[str, Any]				       =   ""
							for numbers_index in range(len(__snake_case				)				):
												_snake_case       :					Dict				       =   int(second_step[0, numbers_index]				)
												_snake_case       :					Optional[Any]				       =   int(second_step[1, numbers_index]				)
												_snake_case       :					Union[str, Any]				       =   self.numbers_to_letter(__snake_case ,						__snake_case				)
												_snake_case       :					str				       =   decoded_message + letter

							return decoded_message