
"""simple docstring"""





import numpy as np

_a									=				[
    ['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_      :




  '''simple docstring'''







  def __init__(						self    ):

     """simple docstring"""
     UpperCAmelCase_   :   int     	=       np.array(lowercase_    )







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_	,  UpperCAmelCase_   :   int     	=       np.where(letter == self.SQUARE    )
     UpperCAmelCase_   :   Optional[Any]     	=       np.concatenate([indexa + 1, indexa + 1]    )
     return indexes







  def 			UpperCamelCase__   (						self							,  lowercase_							,  lowercase_    ):

     """simple docstring"""
     return self.SQUARE[indexa - 1, indexa - 1]







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   Union[str, Any]     	=       message.lower()
     UpperCAmelCase_   :   int     	=       message.replace("j"							,  "i"    )

     UpperCAmelCase_   :   Union[str, Any]     	=       ""
     for letter_index in range(len(lowercase_    )    ):
        if message[letter_index] != " ":
           UpperCAmelCase_   :   List[Any]     	=       self.letter_to_numbers(message[letter_index]    )
           UpperCAmelCase_   :   Dict     	=       encoded_message + str(numbers[0]    ) + str(numbers[1]    )
        elif message[letter_index] == " ":
           UpperCAmelCase_   :   int     	=       encoded_message + " "

     return encoded_message







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   Any     	=       message.replace(" "							,  "  "    )
     UpperCAmelCase_   :   List[Any]     	=       ""
     for numbers_index in range(int(len(lowercase_    ) / 2    )    ):
        if message[numbers_index * 2] != " ":
           UpperCAmelCase_   :   List[Any]     	=       message[numbers_index * 2]
           UpperCAmelCase_   :   Dict     	=       message[numbers_index * 2 + 1]

           UpperCAmelCase_   :   Tuple     	=       self.numbers_to_letter(int(lowercase_    )							,  int(lowercase_    )    )
           UpperCAmelCase_   :   List[Any]     	=       decoded_message + letter
        elif message[numbers_index * 2] == " ":
           UpperCAmelCase_   :   Optional[Any]     	=       decoded_message + " "

     return decoded_message




'''simple docstring'''

import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 		_a     (							SCREAMING_SNAKE_CASE			,    unittest.TestCase  ):







   """simple docstring"""




   A		= MPNetTokenizer
   A		= MPNetTokenizerFast
   A		= True
   A		= True






   def 					__a			(       self      ):
    super().setUp()

    SCREAMING_SNAKE_CASE  :  Tuple								=		[
        '[UNK]',
        '[CLS]',
        '[SEP]',
        '[PAD]',
        '[MASK]',
        'want',
        '##want',
        '##ed',
        'wa',
        'un',
        'runn',
        '##ing',
        ',',
        'low',
        'lowest',
    ]
    SCREAMING_SNAKE_CASE  :  Optional[Any]								=		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 					__a			(       self    ,__SCREAMING_SNAKE_CASE      ):
    SCREAMING_SNAKE_CASE  :  List[str]								=		'UNwant\u00E9d,running'
    SCREAMING_SNAKE_CASE  :  Any								=		'unwanted, running'
    return input_text, output_text






   def 					__a			(       self      ):
    SCREAMING_SNAKE_CASE  :  int								=		self.tokenizer_class(self.vocab_file      )

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






   @slow
   def 					__a			(       self      ):
    SCREAMING_SNAKE_CASE  :  Tuple								=		self.tokenizer_class.from_pretrained('microsoft/mpnet-base'      )

    SCREAMING_SNAKE_CASE  :  Dict								=		tokenizer.encode('sequence builders'    ,add_special_tokens=__SCREAMING_SNAKE_CASE      )
    SCREAMING_SNAKE_CASE  :  List[Any]								=		tokenizer.encode('multi-sequence build'    ,add_special_tokens=__SCREAMING_SNAKE_CASE      )

    SCREAMING_SNAKE_CASE  :  Tuple								=		tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE      )
    SCREAMING_SNAKE_CASE  :  Union[str, Any]								=		tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE    ,__SCREAMING_SNAKE_CASE      )

    assert encoded_sentence == [0] + text + [2]
    assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]


