



'''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											=		get_tests_dir('fixtures/test_sentencepiece.model')


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

_UpperCamelCase											=		128022
_UpperCamelCase											=		128028






@require_sentencepiece
class    lowerCamelCase_       (							SCREAMING_SNAKE_CASE_  ,  unittest.TestCase	):
  """simple docstring"""




  a_				   =MaMaaaTokenizer
  a_				   =False
  a_				   =False
  a_				   =True




  def 		_lowercase	(					self :      Optional[Any]  )   ->   Any:
    super().setUp()

    __lowerCamelCase			:			Tuple       			=					['</s>', '<unk>', '▁This', '▁is', '▁a', '▁t', 'est', '\u0120', '<pad>']
    __lowerCamelCase			:			Tuple       			=					dict(zip(_a     ,      range(len(_a  )  )  )  )
    __lowerCamelCase			:			int       			=					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']  )

    __lowerCamelCase			:			Optional[int]       			=					MaMaaaTokenizer.from_pretrained(self.tmpdirname  )
    tokenizer.save_pretrained(self.tmpdirname  )




  def 		_lowercase	(					self :      Optional[int]     ,      **_a :      Dict  )   ->   int:
    return MaMaaaTokenizer.from_pretrained(self.tmpdirname     ,      **_a  )




  def 		_lowercase	(					self :      Union[str, Any]     ,      _a :      str  )   ->   Tuple:
    return (
        "This is a test",
        "This is a test",
    )




  def 		_lowercase	(					self :      List[Any]  )   ->   str:
    __lowerCamelCase			:			Optional[int]       			=					'</s>'
    __lowerCamelCase			:			int       			=					0

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




  def 		_lowercase	(					self :      Optional[Any]  )   ->   Optional[Any]:
    __lowerCamelCase			:			int       			=					self.get_tokenizer()
    __lowerCamelCase			:			List[str]       			=					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 		_lowercase	(					self :      Any  )   ->   Optional[Any]:
    pass




  def 		_lowercase	(					self :      Union[str, Any]  )   ->   List[Any]:
    __lowerCamelCase			:			Optional[int]       			=					self.get_tokenizer()

    __lowerCamelCase			:			List[Any]       			=					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]     ,      )

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

    __lowerCamelCase			:			Dict       			=					tokenizer.convert_tokens_to_string(_a  )
    self.assertEqual(_a     ,      'This is a test'  )




  @slow
  def 		_lowercase	(					self :      List[str]  )   ->   Any:
    # fmt: off
    __lowerCamelCase			:			List[str]       			=					{'input_ids': [[12_8022, 11_0108, 397, 11, 3_8272, 2247, 12_4811, 285, 1_8105, 1586, 207, 7, 3_9534, 4428, 397, 1019, 1_8105, 1586, 207, 7, 4_1337, 1_6786, 241, 7, 2_0214, 17, 12_5690, 1_0398, 7, 4_4378, 5_8069, 6_8342, 7798, 7343, 11, 299, 3_3310, 4, 158, 3_7350, 9_4077, 4569, 299, 3_3310, 90, 4, 5_2840, 290, 4, 3_1270, 112, 299, 682, 4, 5_2840, 3_9953, 1_4079, 193, 5_2519, 9_0894, 1_7894, 12_0697, 11, 4_0445, 551, 17, 1019, 5_2519, 9_0894, 1_7756, 963, 11, 4_0445, 480, 17, 9792, 1120, 5173, 1393, 6240, 1_6786, 241, 12_0996, 28, 1245, 1393, 11_8240, 1_1123, 1019, 9_3612, 2691, 1_0618, 9_8058, 12_0409, 1928, 279, 4, 4_0683, 367, 178, 207, 1019, 103, 10_3121, 506, 6_5296, 5, 2], [12_8022, 2_1217, 367, 117, 12_5450, 128, 719, 7, 7308, 40, 9_3612, 1_2669, 1116, 1_6704, 71, 1_7785, 3699, 1_5592, 35, 144, 9584, 241, 1_1943, 713, 950, 799, 2247, 8_8427, 150, 149, 11_8813, 12_0706, 1019, 10_6906, 8_1518, 28, 1224, 2_2799, 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], [12_8022, 1658, 12_3311, 5155, 5578, 4722, 279, 1_4947, 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    lowerCamelCase_       (							unittest.TestCase	):
  """simple docstring"""




  a_				   ="""facebook/m2m100_418M"""
  a_				   =[
      """In my opinion, there are two levels of response from the French government.""",
      """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
  ]
  a_				   =[
      """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
  a_				   =[EN_CODE, 593, 1949, 11_5781, 4, 7_1586, 4234, 6_0633, 12_6233, 432, 12_3808, 1_5592, 1197, 11_7132, 12_0618, 5, 2]




  @classmethod
  def 		_lowercase	(					cls :      Optional[Any]  )   ->   Tuple:
    __lowerCamelCase			:			MaMaaaTokenizer       			=					MaMaaaTokenizer.from_pretrained(
        cls.checkpoint_name     ,      src_lang='en'     ,      tgt_lang='fr'  )
    __lowerCamelCase			:			Dict       			=					1
    return cls




  def 		_lowercase	(					self :      Dict  )   ->   List[Any]:
    self.assertEqual(self.tokenizer.get_lang_id('ar'  )     ,      12_8006  )
    self.assertEqual(self.tokenizer.get_lang_id('en'  )     ,      12_8022  )
    self.assertEqual(self.tokenizer.get_lang_id('ro'  )     ,      12_8076  )
    self.assertEqual(self.tokenizer.get_lang_id('mr'  )     ,      12_8063  )




  def 		_lowercase	(					self :      Tuple  )   ->   str:
    __lowerCamelCase			:			Any       			=					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 		_lowercase	(					self :      Union[str, Any]  )   ->   int:
    __lowerCamelCase			:			List[str]       			=					'en'
    __lowerCamelCase			:			str       			=					self.tokenizer.batch_encode_plus(self.src_text  ).input_ids[0]
    self.assertListEqual(self.expected_src_tokens     ,      _a  )




  def 		_lowercase	(					self :      str  )   ->   List[str]:
    self.assertIn(_a     ,      self.tokenizer.all_special_ids  )
    # fmt: off
    __lowerCamelCase			:			str       			=					[FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 1_4028, 136, 3286, 9706, 6, 9_0797, 6, 14_4012, 162, 8_8128, 3_0061, 5, 2]
    # fmt: on
    __lowerCamelCase			:			Any       			=					self.tokenizer.decode(_a     ,      skip_special_tokens=_a  )
    __lowerCamelCase			:			int       			=					self.tokenizer.decode(generated_ids[1:]     ,      skip_special_tokens=_a  )
    self.assertEqual(_a     ,      _a  )
    self.assertNotIn(self.tokenizer.eos_token     ,      _a  )




  def 		_lowercase	(					self :      int  )   ->   List[Any]:
    __lowerCamelCase			:			Tuple       			=					tempfile.mkdtemp()
    __lowerCamelCase			:			Optional[int]       			=					self.tokenizer.lang_token_to_id
    self.tokenizer.save_pretrained(_a  )
    __lowerCamelCase			:			Union[str, Any]       			=					MaMaaaTokenizer.from_pretrained(_a  )
    self.assertDictEqual(new_tok.lang_token_to_id     ,      _a  )




  @require_torch
  def 		_lowercase	(					self :      Optional[Any]  )   ->   List[str]:
    __lowerCamelCase			:			int       			=					'en'
    __lowerCamelCase			:			Dict       			=					'fr'

    __lowerCamelCase			:			Any       			=					self.tokenizer(self.src_text     ,      text_target=self.tgt_text     ,      padding=_a     ,      return_tensors='pt'  )

    __lowerCamelCase			:			Dict       			=					shift_tokens_right(
        batch['labels']     ,      self.tokenizer.pad_token_id     ,      self.tokenizer.eos_token_id  )

    for k in batch:
      __lowerCamelCase			:			Optional[Any]       			=					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 		_lowercase	(					self :      Union[str, Any]  )   ->   int:
    __lowerCamelCase			:			List[Any]       			=					'mr'
    self.assertListEqual(self.tokenizer.prefix_tokens     ,      [self.tokenizer.get_lang_id('mr'  )]  )
    self.assertListEqual(self.tokenizer.suffix_tokens     ,      [self.tokenizer.eos_token_id]  )

    __lowerCamelCase			:			Optional[int]       			=					'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 		_lowercase	(					self :      Any  )   ->   Dict:
    __lowerCamelCase			:			Union[str, Any]       			=					'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  )]  )

    __lowerCamelCase			:			int       			=					'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 		_lowercase	(					self :      Union[str, Any]  )   ->   str:
    __lowerCamelCase			:			Optional[Any]       			=					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': [[12_8022, 58, 4183, 2]],
            'attention_mask': [[1, 1, 1, 1]],
            # ar_AR
            'forced_bos_token_id': 12_8006,
        }     ,      )











'''simple docstring'''





import functools

def 			a_	(				_lowerCAmelCase			,_lowerCAmelCase			) -> int:

  # Validation
  if not isinstance(_lowerCAmelCase			,_lowerCAmelCase			) or not all(isinstance(_lowerCAmelCase			,_lowerCAmelCase			) for day in days			):
    raise ValueError('The parameter days should be a list of integers'			)

  if len(_lowerCAmelCase			) != 3 or not all(isinstance(_lowerCAmelCase			,_lowerCAmelCase			) for cost in costs			):
    raise ValueError('The parameter costs should be a list of three integers'			)

  if len(_lowerCAmelCase			) == 0:
    return 0

  if min(_lowerCAmelCase			) <= 0:
    raise ValueError('All days elements should be greater than 0'			)

  if max(_lowerCAmelCase			) >= 366:
    raise ValueError('All days elements should be less than 366'			)

  __lowerCamelCase			:			int       			=					set(_lowerCAmelCase			)

  @functools.cache
  def dynamic_programming(_lowerCAmelCase			) -> int:
    if index > 365:
      return 0

    if index not in days_set:
      return dynamic_programming(index + 1			)

    return min(
        costs[0] + dynamic_programming(index + 1			)			,costs[1] + dynamic_programming(index + 7			)			,costs[2] + dynamic_programming(index + 30			)			,)

  return dynamic_programming(1			)


if __name__ == "__main__":
   import doctest

   doctest.testmod()






