





'''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_					(    snake_case_				,   unittest.TestCase	):

    '''simple docstring'''
    UpperCamelCase			   =			MPNetTokenizer
    UpperCamelCase			   =			MPNetTokenizerFast
    UpperCamelCase			   =			True
    UpperCamelCase			   =			True


    def       snake_case_(		self	)		->       Dict:
        super().setUp()

        _SCREAMING_SNAKE_CASE     =      [
            """[UNK]""",
            """[CLS]""",
            """[SEP]""",
            """[PAD]""",
            """[MASK]""",
            """want""",
            """##want""",
            """##ed""",
            """wa""",
            """un""",
            """runn""",
            """##ing""",
            """,""",
            """low""",
            """lowest""",
        ]
        _SCREAMING_SNAKE_CASE     =      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       snake_case_(		self			,		A	)		->       Tuple:
        _SCREAMING_SNAKE_CASE     =      """UNwant\u00E9d,running"""
        _SCREAMING_SNAKE_CASE     =      """unwanted, running"""
        return input_text, output_text


    def       snake_case_(		self	)		->       List[str]:
        _SCREAMING_SNAKE_CASE     =      self.tokenizer_class(self.vocab_file	)

        _SCREAMING_SNAKE_CASE     =      tokenizer.tokenize("""UNwant\u00E9d,running"""	)
        self.assertListEqual(A			,		["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]	)
        self.assertListEqual(tokenizer.convert_tokens_to_ids(A	)			,		[9, 6, 7, 12, 10, 11]	)





    @slow
    def       snake_case_(		self	)		->       Tuple:
        _SCREAMING_SNAKE_CASE     =      self.tokenizer_class.from_pretrained("""microsoft/mpnet-base"""	)

        _SCREAMING_SNAKE_CASE     =      tokenizer.encode("""sequence builders"""			,		add_special_tokens=A	)
        _SCREAMING_SNAKE_CASE     =      tokenizer.encode("""multi-sequence build"""			,		add_special_tokens=A	)

        _SCREAMING_SNAKE_CASE     =      tokenizer.build_inputs_with_special_tokens(A	)
        _SCREAMING_SNAKE_CASE     =      tokenizer.build_inputs_with_special_tokens(A			,		A	)

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










'''simple docstring'''

import timeit


class  a_					:

    '''simple docstring'''


    def __init__(		self			,		A	)		->       Optional[int]:
        if isinstance(A			,		A	):  # Initializes a matrix identical to the one provided.
            _SCREAMING_SNAKE_CASE     =      arg
            _SCREAMING_SNAKE_CASE     =      len(A	)
        else:  # Initializes a square matrix of the given size and set values to zero.
            _SCREAMING_SNAKE_CASE     =      arg
            _SCREAMING_SNAKE_CASE     =      [[0 for _ in range(self.n	)] for _ in range(self.n	)]





    def __mul__(		self			,		A	)		->       Optional[int]:
        _SCREAMING_SNAKE_CASE     =      Matrix(self.n	)
        for i in range(self.n	):
            for j in range(self.n	):
                for k in range(self.n	):
                    matrix.t[i][j] += self.t[i][k] * b.t[k][j]
        return matrix





def lowerCamelCase						(					__lowerCamelCase			:   List[str] ,	__lowerCamelCase			:   Optional[int]   )						->int:
    _SCREAMING_SNAKE_CASE     =      Matrix([[1, 0], [0, 1]]   )
    while b > 0:
        if b & 1:
            matrix *= a
        a *= a
        b >>= 1
    return matrix





def lowerCamelCase						(					__lowerCamelCase			:   List[Any] ,	__lowerCamelCase			:   int ,	__lowerCamelCase			:   Tuple   )						->Dict:
    # Trivial Cases
    if n == 1:
        return fa
    elif n == 2:
        return fa
    _SCREAMING_SNAKE_CASE     =      Matrix([[1, 1], [1, 0]]   )
    _SCREAMING_SNAKE_CASE     =      modular_exponentiation(__lowerCamelCase ,	n - 2   )
    return fa * matrix.t[0][0] + fa * matrix.t[0][1]





def lowerCamelCase						(					__lowerCamelCase			:   str ,	__lowerCamelCase			:   List[Any] ,	__lowerCamelCase			:   Tuple   )						->str:
    # Trivial Cases
    if n == 1:
        return fa
    elif n == 2:
        return fa

    _SCREAMING_SNAKE_CASE     =      fa
    _SCREAMING_SNAKE_CASE     =      fa
    n -= 2

    while n > 0:
        _SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE     =      fn_a + fn_a, fn_a
        n -= 1

    return fn_a





def lowerCamelCase						(					)						->str:
    _SCREAMING_SNAKE_CASE     =      """
from random import randint
from __main__ import fibonacci_with_matrix_exponentiation
"""
    _SCREAMING_SNAKE_CASE     =      """fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)"""
    _SCREAMING_SNAKE_CASE     =      timeit.timeit(setup=__lowerCamelCase ,	stmt=__lowerCamelCase ,	number=100   )
    print("""With matrix exponentiation the average execution time is """ ,	exec_time / 100   )
    return exec_time





def lowerCamelCase						(					)						->int:
    _SCREAMING_SNAKE_CASE     =      """
from random import randint
from __main__ import simple_fibonacci
"""
    _SCREAMING_SNAKE_CASE     =      """simple_fibonacci(randint(1,70000), 1, 1)"""
    _SCREAMING_SNAKE_CASE     =      timeit.timeit(setup=__lowerCamelCase ,	stmt=__lowerCamelCase ,	number=100   )
    print(
        """Without matrix exponentiation the average execution time is """ ,	exec_time / 100   )
    return exec_time





def lowerCamelCase						(					)						->List[str]:
    matrix_exponentiation_time()
    simple_fibonacci_time()


if __name__ == "__main__":
      main()



