






"""simple docstring"""


def       snake_case  (A_				:list[list]				):







  '''simple docstring'''

  a					:      int    =       current_set.copy()
  for row_index, row in enumerate(A_				):
    a					:      Union[str, Any]    =       row[0]
    for column_index, column in enumerate(A_				):
      if magnitude == 0:
        a					:      Union[str, Any]    =       column
        continue
      a					:      str    =       column / magnitude
    # Subtract to cancel term
  a					:      Tuple    =       current_set[0]
  a					:      List[Any]    =       [first_row]
  a					:      Union[str, Any]    =       current_set[1::]
  for row in current_set:
    a					:      List[str]    =       []
    # If first term is 0, it is already in form we want, so we preserve it
    if row[0] == 0:
      final_set.append(A_				)
      continue
    for column_index in range(len(A_				)				):
      temp_row.append(first_row[column_index] - row[column_index]				)
    final_set.append(A_				)
  # Create next recursion iteration set
  if len(final_set[0]				) != 3:
    a					:      Tuple    =       final_set[0]
    a					:      str    =       []
    a					:      Tuple    =       []
    for row in final_set[1::]:
      current_first_column.append(row[0]				)
      next_iteration.append(row[1::]				)
    a					:      List[Any]    =       simplify(A_				)
    for i in range(len(A_				)				):
      resultant[i].insert(0     ,      current_first_column[i]				)
    resultant.insert(0     ,      A_				)
    a					:      List[Any]    =       resultant
  return final_set




def       snake_case  (A_				:list[list]				):







  '''simple docstring'''

  if len(A_				) == 0:
    raise IndexError('solve_simultaneous() requires n lists of length n+1'				)
  a					:      int    =       len(A_				) + 1
  if any(len(A_				) != _length for item in equations				):
    raise IndexError('solve_simultaneous() requires n lists of length n+1'				)
  for row in equations:
    if any(not isinstance(A_     ,      (int, float)				) for column in row				):
      raise ValueError('solve_simultaneous() requires lists of integers'				)
  if len(A_				) == 1:
    return [equations[0][-1] / equations[0][0]]
  a					:      Optional[int]    =       equations.copy()
  if any(0 in row for row in data_set				):
    a					:      Optional[int]    =       data_set.copy()
    a					:      List[str]    =       []
    for row_index, row in enumerate(A_				):
      if 0 not in row:
        a					:      int    =       data_set.pop(A_				)
        break
    if not full_row:
      raise ValueError('solve_simultaneous() requires at least 1 full equation'				)
    data_set.insert(0     ,      A_				)
  a					:      Optional[Any]    =       data_set.copy()
  a					:      Dict    =       simplify(A_				)
  a					:      str    =       simplified[::-1]
  a					:      list    =       []
  for row in simplified:
    a					:      List[Any]    =       row[-1]
    if not solutions:
      if row[-2] == 0:
        solutions.append(0				)
        continue
      solutions.append(current_solution / row[-2]				)
      continue
    a					:      str    =       row.copy()[: len(A_				) - 1 :]
    while temp_row[0] == 0:
      temp_row.pop(0				)
    if len(A_				) == 0:
      solutions.append(0				)
      continue
    a					:      Optional[int]    =       temp_row[1::]
    a					:      Tuple    =       temp_row[::-1]
    for column_index, column in enumerate(A_				):
      current_solution -= column * solutions[column_index]
    solutions.append(A_				)
  a					:      Optional[Any]    =       []
  for item in solutions:
    final.append(float(round(A_     ,      5				)				)				)
  return final[::-1]


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   _UpperCamelCase    :   int   			=						[
       [2, 1, 1, 1, 1, 4],
       [1, 2, 1, 1, 1, 5],
       [1, 1, 2, 1, 1, 6],
       [1, 1, 1, 2, 1, 7],
       [1, 1, 1, 1, 2, 8],
   ]
   print(solve_simultaneous(eq))
   print(solve_simultaneous([[4, 2]]))












"""simple docstring"""


import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCamelCase    :   int   			=						get_tests_dir('fixtures/test_sentencepiece_bpe.model')






class 						snake_case  (  UpperCAmelCase       ,			unittest.TestCase	):
    __magic_name__   					=					BartphoTokenizer
    __magic_name__   					=					False
    __magic_name__   					=					True





    def     lowerCamelCase__				(							self     : List[Any]      ):


      '''simple docstring'''




      super().setUp()

      a					:      Any    =       ['▁This', '▁is', '▁a', '▁t', 'est']
      a					:      List[Any]    =       dict(zip(A    ,		range(len(A      )      )      )      )
      a					:      int    =       {'unk_token': '<unk>'}

      a					:      Tuple    =       os.path.join(self.tmpdirname    ,		VOCAB_FILES_NAMES['monolingual_vocab_file']      )
      with open(self.monolingual_vocab_file    ,		'w'    ,		encoding='utf-8'      ) as fp:
        for token in vocab_tokens:
          fp.write(F'''{token} {vocab_tokens[token]}\n'''      )

      a					:      Optional[int]    =       BartphoTokenizer(A    ,		self.monolingual_vocab_file    ,		**self.special_tokens_map      )
      tokenizer.save_pretrained(self.tmpdirname      )





    def     lowerCamelCase__				(							self     : Dict    ,		**A     : str      ):


      '''simple docstring'''




      kwargs.update(self.special_tokens_map      )
      return BartphoTokenizer.from_pretrained(self.tmpdirname    ,		**A      )





    def     lowerCamelCase__				(							self     : Optional[int]    ,		A     : Dict      ):


      '''simple docstring'''




      a					:      Tuple    =       'This is a là test'
      a					:      List[Any]    =       'This is a<unk><unk> test'
      return input_text, output_text





    def     lowerCamelCase__				(							self     : Optional[Any]      ):


      '''simple docstring'''




      a					:      Tuple    =       BartphoTokenizer(A    ,		self.monolingual_vocab_file    ,		**self.special_tokens_map      )
      a					:      int    =       'This is a là test'
      a					:      int    =       '▁This ▁is ▁a ▁l à ▁t est'.split()
      a					:      str    =       tokenizer.tokenize(A      )
      self.assertListEqual(A    ,		A      )

      a					:      Union[str, Any]    =       tokens + [tokenizer.unk_token]
      a					:      Dict    =       [4, 5, 6, 3, 3, 7, 8, 3]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A      )    ,		A      )




