import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_rjieba
@require_tokenizers
class __snake_case				(						lowerCamelCase_   ,		unittest.TestCase		):
   lowerCAmelCase_														=							RoFormerTokenizer
   lowerCAmelCase_														=							RoFormerTokenizerFast
   lowerCAmelCase_														=							True
   lowerCAmelCase_														=							True




   def 	__a						(    self			:				Optional[int]      ):



     """simple docstring"""






     super().setUp()




   def 	__a						(    self			:				int       ,	**_lowercase			:				Optional[Any]      ):



     """simple docstring"""






     return self.tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""       ,	**_lowercase      )




   def 	__a						(    self			:				str       ,	**_lowercase			:				Optional[int]      ):



     """simple docstring"""






     return self.rust_tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""       ,	**_lowercase      )




   def 	__a						(    self			:				Optional[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      """永和服装饰品有限公司,今天天气非常好"""
     SCREAMING_SNAKE_CASE__										=      """永和 服装 饰品 有限公司 , 今 天 天 气 非常 好"""
     return input_text, output_text




   def 	__a						(    self			:				int      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_tokenizer()
     SCREAMING_SNAKE_CASE__							,     SCREAMING_SNAKE_CASE__										=      self.get_chinese_input_output_texts()
     SCREAMING_SNAKE_CASE__										=      tokenizer.tokenize(_lowercase      )

     self.assertListEqual(_lowercase       ,	output_text.split()      )

     SCREAMING_SNAKE_CASE__										=      tokens + [tokenizer.unk_token]
     SCREAMING_SNAKE_CASE__										=      [2_29_43, 2_13_32, 3_44_31, 4_59_04, 1_17, 3_06, 12_31, 12_31, 26_53, 3_39_94, 12_66, 1_00]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase      )       ,	_lowercase      )




   def 	__a						(    self			:				Dict      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.get_rust_tokenizer()
     SCREAMING_SNAKE_CASE__							,     SCREAMING_SNAKE_CASE__										=      self.get_chinese_input_output_texts()
     SCREAMING_SNAKE_CASE__										=      tokenizer.tokenize(_lowercase      )
     self.assertListEqual(_lowercase       ,	output_text.split()      )
     SCREAMING_SNAKE_CASE__										=      tokens + [tokenizer.unk_token]
     SCREAMING_SNAKE_CASE__										=      [2_29_43, 2_13_32, 3_44_31, 4_59_04, 1_17, 3_06, 12_31, 12_31, 26_53, 3_39_94, 12_66, 1_00]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase      )       ,	_lowercase      )




   def 	__a						(    self			:				Optional[int]      ):



     """simple docstring"""






     pass




   def 	__a						(    self			:				Dict      ):



     """simple docstring"""






     pass




   def 	__a						(    self			:				str      ):



     """simple docstring"""






     pass

import doctest
from collections import deque

import numpy as np







class __snake_case				:




   def __init__(    self			:				Dict      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      [2, 1, 2, -1]
     SCREAMING_SNAKE_CASE__										=      [1, 2, 3, 4]




   def 	__a						(    self			:				int      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      len(self.first_signal      )
     SCREAMING_SNAKE_CASE__										=      len(self.second_signal      )

     SCREAMING_SNAKE_CASE__										=      max(_lowercase       ,	_lowercase      )

     # create a zero matrix of max_length x max_length
     SCREAMING_SNAKE_CASE__										=      [[0] * max_length for i in range(_lowercase      )]

     # fills the smaller signal with zeros to make both signals of same length
     if length_first_signal < length_second_signal:
       self.first_signal += [0] * (max_length - length_first_signal)
     elif length_first_signal > length_second_signal:
       self.second_signal += [0] * (max_length - length_second_signal)
     for i in range(_lowercase      ):
       SCREAMING_SNAKE_CASE__										=      deque(self.second_signal      )
       rotated_signal.rotate(_lowercase      )
       for j, item in enumerate(_lowercase      ):
         matrix[i][j] += item

        # multiply the matrix with the first signal
     SCREAMING_SNAKE_CASE__										=      np.matmul(np.transpose(_lowercase      )       ,	np.transpose(self.first_signal      )      )

     # rounding-off to two decimal places
     return [round(_lowercase       ,	2      ) for i in final_signal]


if __name__ == "__main__":
   doctest.testmod()
