'''simple docstring'''




import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
     from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
     _UpperCamelCase					:		Optional[int]							      =		get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
     from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

_UpperCamelCase					:		Union[str, Any]							      =		12_80_22
_UpperCamelCase					:		Any							      =		12_80_28

@require_sentencepiece
class 	_lowercase(  SCREAMING_SNAKE_CASE_ ,unittest.TestCase					):



   """simple docstring"""





   __lowerCamelCase     =	MaMaaaTokenizer
   __lowerCamelCase     =	False
   __lowerCamelCase     =	False
   __lowerCamelCase     =	True





   def       snake_case						(				self:     Optional[Any]						):
    super().setUp()

    __UpperCAmelCase								=       ['</s>', '<unk>', '▁This', '▁is', '▁a', '▁t', 'est', '\u0120', '<pad>']
    __UpperCAmelCase								=       dict(zip(_a      ,range(len(_a						)						)						)						)
    __UpperCAmelCase								=       Path(self.tmpdirname						)
    save_json(_a      ,save_dir / VOCAB_FILES_NAMES['vocab_file']						)
    if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
     copyfile(_a      ,save_dir / VOCAB_FILES_NAMES['spm_file']						)

    __UpperCAmelCase								=       MaMaaaTokenizer.from_pretrained(self.tmpdirname						)
    tokenizer.save_pretrained(self.tmpdirname						)





   def       snake_case						(				self:     Optional[int]      ,**a:     Dict						):
    return MaMaaaTokenizer.from_pretrained(self.tmpdirname      ,**_a						)





   def       snake_case						(				self:     Union[str, Any]      ,a:     str						):
    return (
        "This is a test",
        "This is a test",
    )





   def       snake_case						(				self:     List[Any]						):
    __UpperCAmelCase								=       '</s>'
    __UpperCAmelCase								=       0

    self.assertEqual(self.get_tokenizer()._convert_token_to_id(_a						)      ,_a						)
    self.assertEqual(self.get_tokenizer()._convert_id_to_token(_a						)      ,_a						)





   def       snake_case						(				self:     Optional[Any]						):
    __UpperCAmelCase								=       self.get_tokenizer()
    __UpperCAmelCase								=       list(tokenizer.get_vocab().keys()						)

    self.assertEqual(vocab_keys[0]      ,'</s>'						)
    self.assertEqual(vocab_keys[1]      ,'<unk>'						)
    self.assertEqual(vocab_keys[-1]      ,'<s>'						)
    self.assertEqual(len(_a						)      ,tokenizer.vocab_size + len(tokenizer.get_added_vocab()						)						)





   @unittest.skip('Skip this test while all models are still to be uploaded.'						)
   def       snake_case						(				self:     Any						):
    pass





   def       snake_case						(				self:     Union[str, Any]						):
    __UpperCAmelCase								=       self.get_tokenizer()

    __UpperCAmelCase								=       tokenizer.tokenize('This is a test'						)
    self.assertListEqual(_a      ,['▁This', '▁is', '▁a', '▁t', 'est']						)

    self.assertListEqual(
        tokenizer.convert_tokens_to_ids(_a						)      ,[2, 3, 4, 5, 6]      ,)

    __UpperCAmelCase								=       tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]						)
    self.assertListEqual(_a      ,['▁This', '▁is', '▁a', '▁t', 'est']						)

    __UpperCAmelCase								=       tokenizer.convert_tokens_to_string(_a						)
    self.assertEqual(_a      ,'This is a test'						)





   @slow
   def       snake_case						(				self:     List[str]						):
    # fmt: off
    __UpperCAmelCase								=       {'input_ids': [[128022, 110108, 397, 11, 38272, 2247, 124811, 285, 18105, 1586, 207, 7, 39534, 4428, 397, 1019, 18105, 1586, 207, 7, 41337, 16786, 241, 7, 20214, 17, 125690, 10398, 7, 44378, 58069, 68342, 7798, 7343, 11, 299, 33310, 4, 158, 37350, 94077, 4569, 299, 33310, 90, 4, 52840, 290, 4, 31270, 112, 299, 682, 4, 52840, 39953, 14079, 193, 52519, 90894, 17894, 120697, 11, 40445, 551, 17, 1019, 52519, 90894, 17756, 963, 11, 40445, 480, 17, 9792, 1120, 5173, 1393, 6240, 16786, 241, 120996, 28, 1245, 1393, 118240, 11123, 1019, 93612, 2691, 10618, 98058, 120409, 1928, 279, 4, 40683, 367, 178, 207, 1019, 103, 103121, 506, 65296, 5, 2], [128022, 21217, 367, 117, 125450, 128, 719, 7, 7308, 40, 93612, 12669, 1116, 16704, 71, 17785, 3699, 15592, 35, 144, 9584, 241, 11943, 713, 950, 799, 2247, 88427, 150, 149, 118813, 120706, 1019, 106906, 81518, 28, 1224, 22799, 397, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [128022, 1658, 123311, 5155, 5578, 4722, 279, 14947, 2366, 1120, 1197, 14, 1348, 9232, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
    # fmt: on

    self.tokenizer_integration_test_util(
        expected_encoding=_a      ,model_name='facebook/m2m100_418M'      ,revision='c168bae485c864188cf9aa0e4108b0b6934dc91e'      ,)




@require_torch
@require_sentencepiece
@require_tokenizers
class 	_lowercase(  unittest.TestCase					):



   """simple docstring"""





   __lowerCamelCase     =	'''facebook/m2m100_418M'''
   __lowerCamelCase     =	[
       '''In my opinion, there are two levels of response from the French government.''',
       '''NSA Affair Emphasizes Complete Lack of Debate on Intelligence''',
   ]
   __lowerCamelCase     =	[
       '''Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.''',
       '''L\'affaire NSA souligne l\'absence totale de débat sur le renseignement''',
   ]

   # fmt: off
   __lowerCamelCase     =	[EN_CODE, 593, 1949, 115781, 4, 71586, 4234, 60633, 126233, 432, 123808, 15592, 1197, 117132, 120618, 5, 2]





   @classmethod
   def       snake_case						(				cls:     Optional[Any]						):
    __UpperCAmelCase								=       MaMaaaTokenizer.from_pretrained(
        cls.checkpoint_name      ,src_lang='en'      ,tgt_lang='fr'						)
    __UpperCAmelCase								=       1
    return cls





   def       snake_case						(				self:     Dict						):
    self.assertEqual(self.tokenizer.get_lang_id('ar'						)      ,128006						)
    self.assertEqual(self.tokenizer.get_lang_id('en'						)      ,128022						)
    self.assertEqual(self.tokenizer.get_lang_id('ro'						)      ,128076						)
    self.assertEqual(self.tokenizer.get_lang_id('mr'						)      ,128063						)





   def       snake_case						(				self:     Tuple						):
    __UpperCAmelCase								=       self.tokenizer.get_vocab()
    self.assertEqual(len(_a						)      ,self.tokenizer.vocab_size						)
    self.assertEqual(vocab['<unk>']      ,3						)
    self.assertIn(self.tokenizer.get_lang_token('en'						)      ,_a						)





   def       snake_case						(				self:     Union[str, Any]						):
    __UpperCAmelCase								=       'en'
    __UpperCAmelCase								=       self.tokenizer.batch_encode_plus(self.src_text						).input_ids[0]
    self.assertListEqual(self.expected_src_tokens      ,_a						)





   def       snake_case						(				self:     str						):
    self.assertIn(_a      ,self.tokenizer.all_special_ids						)
    # fmt: off
    __UpperCAmelCase								=       [FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 14028, 136, 3286, 9706, 6, 90797, 6, 144012, 162, 88128, 30061, 5, 2]
    # fmt: on
    __UpperCAmelCase								=       self.tokenizer.decode(_a      ,skip_special_tokens=_a						)
    __UpperCAmelCase								=       self.tokenizer.decode(generated_ids[1:]      ,skip_special_tokens=_a						)
    self.assertEqual(_a      ,_a						)
    self.assertNotIn(self.tokenizer.eos_token      ,_a						)





   def       snake_case						(				self:     int						):
    __UpperCAmelCase								=       tempfile.mkdtemp()
    __UpperCAmelCase								=       self.tokenizer.lang_token_to_id
    self.tokenizer.save_pretrained(_a						)
    __UpperCAmelCase								=       MaMaaaTokenizer.from_pretrained(_a						)
    self.assertDictEqual(new_tok.lang_token_to_id      ,_a						)





   @require_torch
   def       snake_case						(				self:     Optional[Any]						):
    __UpperCAmelCase								=       'en'
    __UpperCAmelCase								=       'fr'

    __UpperCAmelCase								=       self.tokenizer(self.src_text      ,text_target=self.tgt_text      ,padding=_a      ,return_tensors='pt'						)

    __UpperCAmelCase								=       shift_tokens_right(
        batch['labels']      ,self.tokenizer.pad_token_id      ,self.tokenizer.eos_token_id						)

    for k in batch:
     __UpperCAmelCase								=       batch[k].tolist()
    # batch = {k: v.tolist() for k,v in batch.items()}
    # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
    # batch.decoder_inputs_ids[0][0] ==
    assert batch.input_ids[1][0] == EN_CODE
    assert batch.input_ids[1][-1] == 2
    assert batch.labels[1][0] == FR_CODE
    assert batch.labels[1][-1] == 2
    assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]





   @require_torch
   def       snake_case						(				self:     Union[str, Any]						):
    __UpperCAmelCase								=       'mr'
    self.assertListEqual(self.tokenizer.prefix_tokens      ,[self.tokenizer.get_lang_id('mr'						)]						)
    self.assertListEqual(self.tokenizer.suffix_tokens      ,[self.tokenizer.eos_token_id]						)

    __UpperCAmelCase								=       'zh'
    self.assertListEqual(self.tokenizer.prefix_tokens      ,[self.tokenizer.get_lang_id('zh'						)]						)
    self.assertListEqual(self.tokenizer.suffix_tokens      ,[self.tokenizer.eos_token_id]						)





   @require_torch
   def       snake_case						(				self:     Any						):
    __UpperCAmelCase								=       'mr'
    self.tokenizer._switch_to_target_mode()
    self.assertListEqual(self.tokenizer.prefix_tokens      ,[self.tokenizer.get_lang_id('mr'						)]						)
    self.assertListEqual(self.tokenizer.suffix_tokens      ,[self.tokenizer.eos_token_id]						)
    self.tokenizer._switch_to_input_mode()
    self.assertListEqual(self.tokenizer.prefix_tokens      ,[self.tokenizer.get_lang_id(self.tokenizer.src_lang						)]						)

    __UpperCAmelCase								=       'zh'
    self.tokenizer._switch_to_target_mode()
    self.assertListEqual(self.tokenizer.prefix_tokens      ,[self.tokenizer.get_lang_id('zh'						)]						)
    self.assertListEqual(self.tokenizer.suffix_tokens      ,[self.tokenizer.eos_token_id]						)
    self.tokenizer._switch_to_input_mode()
    self.assertListEqual(self.tokenizer.prefix_tokens      ,[self.tokenizer.get_lang_id(self.tokenizer.src_lang						)]						)





   @require_torch
   def       snake_case						(				self:     Union[str, Any]						):
    __UpperCAmelCase								=       self.tokenizer._build_translation_inputs('A test'      ,return_tensors='pt'      ,src_lang='en'      ,tgt_lang='ar'						)

    self.assertEqual(
        nested_simplify(_a						)      ,{
            # en_XX, A, test, EOS
            'input_ids': [[128022, 58, 4183, 2]],
            'attention_mask': [[1, 1, 1, 1]],
            # ar_AR
            'forced_bos_token_id': 128006,
        }      ,)








'''simple docstring'''





def 			a_	(				_lowerCAmelCase			,_lowerCAmelCase			) -> tuple[float, float]:

  # Check if the input is valid
  if not len(_lowerCAmelCase			) == len(_lowerCAmelCase			) == 3:
    raise ValueError('Please enter a valid equation.'			)
  if equationa[0] == equationa[1] == equationa[0] == equationa[1] == 0:
    raise ValueError('Both a & b of two equations can\'t be zero.'			)

  # Extract the coefficients
  __lowerCamelCase			,__lowerCamelCase			,__lowerCamelCase			:			Union[str, Any]       			=					equationa
  __lowerCamelCase			,__lowerCamelCase			,__lowerCamelCase			:			Any       			=					equationa

  # Calculate the determinants of the matrices
  __lowerCamelCase			:			Union[str, Any]       			=					aa * ba - aa * ba
  __lowerCamelCase			:			Dict       			=					ca * ba - ca * ba
  __lowerCamelCase			:			List[str]       			=					aa * ca - aa * ca

  # Check if the system of linear equations has a solution (using Cramer's rule)
  if determinant == 0:
    if determinant_x == determinant_y == 0:
      raise ValueError('Infinite solutions. (Consistent system)'			)
    else:
      raise ValueError('No solution. (Inconsistent system)'			)
  else:
    if determinant_x == determinant_y == 0:
      # Trivial solution (Inconsistent system)
      return (0.0, 0.0)
    else:
      __lowerCamelCase			:			Tuple       			=					determinant_x / determinant
      __lowerCamelCase			:			Union[str, Any]       			=					determinant_y / determinant
      # Non-Trivial Solution (Consistent system)
      return (x, y)






