



import shutil
import tempfile
import unittest

from transformers import (
    SPIECE_UNDERLINE,
    AddedToken,
    BatchEncoding,
    NllbTokenizer,
    NllbTokenizerFast,
    is_torch_available,
)
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase:      Optional[Any]		 =		get_tests_dir('fixtures/test_sentencepiece.model')


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

lowerCAmelCase:      int		 =		2_5_6_0_4_7
lowerCAmelCase:      List[Any]		 =		2_5_6_1_4_5

@require_sentencepiece
@require_tokenizers
class 							a__(      lowerCamelCase__	,				unittest.TestCase			):
    lowercase__				=					NllbTokenizer
    lowercase__				=					NllbTokenizerFast
    lowercase__				=					True
    lowercase__				=					True
    lowercase__				=					{}







    def     lowercase_ (   self				:						str			):
      super().setUp()

      # We have a SentencePiece fixture for testing
      a		:      Optional[int]       =  NllbTokenizer(__snake_case		,    keep_accents=__snake_case			)
      tokenizer.save_pretrained(self.tmpdirname			)







    def     lowercase_ (   self				:						int			):
      a		:      List[Any]       =  NllbTokenizer(__snake_case		,    keep_accents=__snake_case			)

      a		:      List[Any]       =  tokenizer.tokenize('This is a test'			)
      self.assertListEqual(__snake_case		,    ['▁This', '▁is', '▁a', '▁t', 'est']			)

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(__snake_case			)		,    [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]		,    )

      a		:      List[Any]       =  tokenizer.tokenize('I was born in 92000, and this is falsé.'			)
      self.assertListEqual(
          __snake_case		,    [
              SPIECE_UNDERLINE + 'I',
              SPIECE_UNDERLINE + 'was',
              SPIECE_UNDERLINE + 'b',
              'or',
              'n',
              SPIECE_UNDERLINE + 'in',
              SPIECE_UNDERLINE + '',
              '9',
              '2',
              '0',
              '0',
              '0',
              ',',
              SPIECE_UNDERLINE + 'and',
              SPIECE_UNDERLINE + 'this',
              SPIECE_UNDERLINE + 'is',
              SPIECE_UNDERLINE + 'f',
              'al',
              's',
              'é',
              '.',
          ]		,    )
      a		:      Union[str, Any]       =  tokenizer.convert_tokens_to_ids(__snake_case			)
      self.assertListEqual(
          __snake_case		,    [
              value + tokenizer.fairseq_offset
              for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
          ]		,    )

      a		:      Union[str, Any]       =  tokenizer.convert_ids_to_tokens(__snake_case			)
      self.assertListEqual(
          __snake_case		,    [
              SPIECE_UNDERLINE + 'I',
              SPIECE_UNDERLINE + 'was',
              SPIECE_UNDERLINE + 'b',
              'or',
              'n',
              SPIECE_UNDERLINE + 'in',
              SPIECE_UNDERLINE + '',
              '<unk>',
              '2',
              '0',
              '0',
              '0',
              ',',
              SPIECE_UNDERLINE + 'and',
              SPIECE_UNDERLINE + 'this',
              SPIECE_UNDERLINE + 'is',
              SPIECE_UNDERLINE + 'f',
              'al',
              's',
              '<unk>',
              '.',
          ]		,    )







    def     lowercase_ (   self				:						int			):
      a		:      Optional[int]       =  (self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-nllb', {})
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""			):
          a		:      Any       =  self.rust_tokenizer_class.from_pretrained(__snake_case		,    **__snake_case			)
          a		:      str       =  self.tokenizer_class.from_pretrained(__snake_case		,    **__snake_case			)

          a		:      Dict       =  tempfile.mkdtemp()

          a		:      Union[str, Any]       =  tokenizer_r.save_pretrained(__snake_case			)
          a		:      Optional[Any]       =  tokenizer_p.save_pretrained(__snake_case			)

          # Checks it save with the same files + the tokenizer.json file for the fast one
          self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files			)			)
          a		:      List[str]       =  tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f			)
          self.assertSequenceEqual(__snake_case		,    __snake_case			)

          # Checks everything loads correctly in the same way
          a		:      Tuple       =  tokenizer_r.from_pretrained(__snake_case			)
          a		:      str       =  tokenizer_p.from_pretrained(__snake_case			)

          # Check special tokens are set accordingly on Rust and Python
          for key in tokenizer_pp.special_tokens_map:
            self.assertTrue(hasattr(__snake_case		,    __snake_case			)			)

          shutil.rmtree(__snake_case			)

          # Save tokenizer rust, legacy_format=True
          a		:      int       =  tempfile.mkdtemp()

          a		:      List[str]       =  tokenizer_r.save_pretrained(__snake_case		,    legacy_format=__snake_case			)
          a		:      Optional[int]       =  tokenizer_p.save_pretrained(__snake_case			)

          # Checks it save with the same files
          self.assertSequenceEqual(__snake_case		,    __snake_case			)

          # Checks everything loads correctly in the same way
          a		:      int       =  tokenizer_r.from_pretrained(__snake_case			)
          a		:      Optional[Any]       =  tokenizer_p.from_pretrained(__snake_case			)

          # Check special tokens are set accordingly on Rust and Python
          for key in tokenizer_pp.special_tokens_map:
            self.assertTrue(hasattr(__snake_case		,    __snake_case			)			)

          shutil.rmtree(__snake_case			)

          # Save tokenizer rust, legacy_format=False
          a		:      Dict       =  tempfile.mkdtemp()

          a		:      Union[str, Any]       =  tokenizer_r.save_pretrained(__snake_case		,    legacy_format=__snake_case			)
          a		:      str       =  tokenizer_p.save_pretrained(__snake_case			)

          # Checks it saved the tokenizer.json file
          self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files			)			)

          # Checks everything loads correctly in the same way
          a		:      Optional[int]       =  tokenizer_r.from_pretrained(__snake_case			)
          a		:      Optional[int]       =  tokenizer_p.from_pretrained(__snake_case			)

          # Check special tokens are set accordingly on Rust and Python
          for key in tokenizer_pp.special_tokens_map:
            self.assertTrue(hasattr(__snake_case		,    __snake_case			)			)

          shutil.rmtree(__snake_case			)







    @require_torch
    def     lowercase_ (   self				:						List[str]			):
      if not self.test_seqaseq:
        return

      a		:      Any       =  self.get_tokenizers()
      for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""			):
          # Longer text that will definitely require truncation.
          a		:      List[str]       =  [
              ' UN Chief Says There Is No Military Solution in Syria',
              ' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for'
              ' Syria is that \'there is no military solution\' to the nearly five-year conflict and more weapons'
              ' will only worsen the violence and misery for millions of people.',
          ]
          a		:      Union[str, Any]       =  [
              'Şeful ONU declară că nu există o soluţie militară în Siria',
              'Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al'
              ' Rusiei pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi'
              ' că noi arme nu vor face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.',
          ]
          try:
            a		:      str       =  tokenizer.prepare_seqaseq_batch(
                src_texts=__snake_case		,    tgt_texts=__snake_case		,    max_length=3		,    max_target_length=10		,    return_tensors='pt'		,    src_lang='eng_Latn'		,    tgt_lang='ron_Latn'		,    )
          except NotImplementedError:
            return
          self.assertEqual(batch.input_ids.shape[1]		,    3			)
          self.assertEqual(batch.labels.shape[1]		,    10			)
          # max_target_length will default to max_length if not specified
          a		:      List[str]       =  tokenizer.prepare_seqaseq_batch(
              __snake_case		,    tgt_texts=__snake_case		,    max_length=3		,    return_tensors='pt'			)
          self.assertEqual(batch.input_ids.shape[1]		,    3			)
          self.assertEqual(batch.labels.shape[1]		,    3			)

          a		:      Union[str, Any]       =  tokenizer.prepare_seqaseq_batch(
              src_texts=__snake_case		,    max_length=3		,    max_target_length=10		,    return_tensors='pt'			)
          self.assertEqual(batch_encoder_only.input_ids.shape[1]		,    3			)
          self.assertEqual(batch_encoder_only.attention_mask.shape[1]		,    3			)
          self.assertNotIn('decoder_input_ids'		,    __snake_case			)







    @unittest.skip('Unfortunately way too slow to build a BPE with SentencePiece.'			)
    def     lowercase_ (   self				:						str			):
      pass







    def     lowercase_ (   self				:						int			):
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""			):
          a		:      Optional[int]       =  [AddedToken('<special>'		,    lstrip=__snake_case			)]

          a		:      str       =  self.rust_tokenizer_class.from_pretrained(
              __snake_case		,    additional_special_tokens=__snake_case		,    **__snake_case			)
          a		:      Optional[Any]       =  tokenizer_r.encode('Hey this is a <special> token'			)

          a		:      Dict       =  tokenizer_r.encode('<special>'		,    add_special_tokens=__snake_case			)[0]

          self.assertTrue(special_token_id in r_output			)

          if self.test_slow_tokenizer:
            a		:      Optional[Any]       =  self.rust_tokenizer_class.from_pretrained(
                __snake_case		,    additional_special_tokens=__snake_case		,    **__snake_case		,    )
            a		:      Optional[int]       =  self.tokenizer_class.from_pretrained(
                __snake_case		,    additional_special_tokens=__snake_case		,    **__snake_case			)

            a		:      Dict       =  tokenizer_p.encode('Hey this is a <special> token'			)

            a		:      Dict       =  tokenizer_cr.encode('Hey this is a <special> token'			)

            self.assertEqual(__snake_case		,    __snake_case			)
            self.assertEqual(__snake_case		,    __snake_case			)
            self.assertTrue(special_token_id in p_output			)
            self.assertTrue(special_token_id in cr_output			)

@require_torch
@require_sentencepiece
@require_tokenizers
class 							a__(      unittest.TestCase			):
    lowercase__				=					"""facebook/nllb-200-distilled-600M"""
    lowercase__				=					[
        """ UN Chief Says There Is No Military Solution in Syria""",
        """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
    ]
    lowercase__				=					[
        """Şeful ONU declară că nu există o soluţie militară în Siria""",
        """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
        """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
        """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
    ]
    lowercase__				=					[
        25_60_47,
        1_62_97,
        13_44_08,
        81_65,
        24_80_66,
        1_47_34,
        9_50,
        11_35,
        10_57_21,
        35_73,
        83,
        2_73_52,
        1_08,
        4_94_86,
        2,
    ]







    @classmethod
    def     lowercase_ (   cls				:						List[str]			):
      a		:      NllbTokenizer       =  NllbTokenizer.from_pretrained(
          cls.checkpoint_name		,    src_lang='eng_Latn'		,    tgt_lang='ron_Latn'			)
      a		:      Optional[int]       =  1
      return cls







    def     lowercase_ (   self				:						Union[str, Any]			):
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ace_Arab']		,    25_60_01			)
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ace_Latn']		,    25_60_02			)
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['fra_Latn']		,    25_60_57			)







    def     lowercase_ (   self				:						Tuple			):
      a		:      Any       =  self.tokenizer.batch_encode_plus(self.src_text			).input_ids[0]
      self.assertListEqual(self.expected_src_tokens		,    __snake_case			)







    def     lowercase_ (   self				:						List[str]			):
      self.assertIn(__snake_case		,    self.tokenizer.all_special_ids			)
      # fmt: off
      a		:      Union[str, Any]       =  [RO_CODE, 42_54, 9_80_68, 11_29_23, 3_90_72, 39_09, 7_13, 10_27_67, 26, 1_73_14, 3_56_42, 1_46_83, 3_31_18, 20_22, 6_69_87, 2, 25_60_47]
      # fmt: on

      a		:      Dict       =  self.tokenizer.decode(__snake_case		,    skip_special_tokens=__snake_case			)
      a		:      Union[str, Any]       =  self.tokenizer.decode(generated_ids[1:]		,    skip_special_tokens=__snake_case			)
      self.assertEqual(__snake_case		,    __snake_case			)
      self.assertNotIn(self.tokenizer.eos_token		,    __snake_case			)







    def     lowercase_ (   self				:						Optional[int]			):
      a		:      Dict       =  ['this is gunna be a long sentence ' * 20]
      assert isinstance(src_text[0]		,    __snake_case			)
      a		:      Tuple       =  10
      a		:      Dict       =  self.tokenizer(__snake_case		,    max_length=__snake_case		,    truncation=__snake_case			).input_ids[0]
      self.assertEqual(ids[-1]		,    2			)
      self.assertEqual(ids[0]		,    __snake_case			)
      self.assertEqual(len(__snake_case			)		,    __snake_case			)







    def     lowercase_ (   self				:						str			):
      self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']			)		,    [25_62_03, 3]			)







    def     lowercase_ (   self				:						int			):
      a		:      Tuple       =  tempfile.mkdtemp()
      a		:      Optional[Any]       =  self.tokenizer.fairseq_tokens_to_ids
      self.tokenizer.save_pretrained(__snake_case			)
      a		:      Tuple       =  NllbTokenizer.from_pretrained(__snake_case			)
      self.assertDictEqual(new_tok.fairseq_tokens_to_ids		,    __snake_case			)







    @require_torch
    def     lowercase_ (   self				:						List[str]			):
      a		:      Dict       =  self.tokenizer(
          self.src_text		,    text_target=self.tgt_text		,    padding=__snake_case		,    truncation=__snake_case		,    max_length=len(self.expected_src_tokens			)		,    return_tensors='pt'		,    )
      a		:      Dict       =  shift_tokens_right(
          batch['labels']		,    self.tokenizer.pad_token_id		,    self.tokenizer.lang_code_to_id['ron_Latn']			)

      self.assertIsInstance(__snake_case		,    __snake_case			)

      self.assertEqual((2, 15)		,    batch.input_ids.shape			)
      self.assertEqual((2, 15)		,    batch.attention_mask.shape			)
      a		:      str       =  batch.input_ids.tolist()[0]
      self.assertListEqual(self.expected_src_tokens		,    __snake_case			)
      self.assertEqual(__snake_case		,    batch.decoder_input_ids[0, 0]			)  # EOS
      # Test that special tokens are reset
      self.assertEqual(self.tokenizer.prefix_tokens		,    [EN_CODE]			)
      self.assertEqual(self.tokenizer.suffix_tokens		,    [self.tokenizer.eos_token_id]			)







    def     lowercase_ (   self				:						Optional[int]			):
      a		:      List[str]       =  self.tokenizer(self.src_text		,    padding=__snake_case		,    truncation=__snake_case		,    max_length=3		,    return_tensors='pt'			)
      a		:      Union[str, Any]       =  self.tokenizer(
          text_target=self.tgt_text		,    padding=__snake_case		,    truncation=__snake_case		,    max_length=10		,    return_tensors='pt'			)
      a		:      Any       =  targets['input_ids']
      a		:      Union[str, Any]       =  shift_tokens_right(
          __snake_case		,    self.tokenizer.pad_token_id		,    decoder_start_token_id=self.tokenizer.lang_code_to_id[self.tokenizer.tgt_lang]		,    )

      self.assertEqual(batch.input_ids.shape[1]		,    3			)
      self.assertEqual(batch.decoder_input_ids.shape[1]		,    10			)







    @require_torch
    def     lowercase_ (   self				:						Dict			):
      a		:      Dict       =  self.tokenizer._build_translation_inputs(
          'A test'		,    return_tensors='pt'		,    src_lang='eng_Latn'		,    tgt_lang='fra_Latn'			)

      self.assertEqual(
          nested_simplify(__snake_case			)		,    {
              # A, test, EOS, en_XX
              'input_ids': [[25_60_47, 70, 73_56, 2]],
              'attention_mask': [[1, 1, 1, 1]],
              # ar_AR
              'forced_bos_token_id': 25_60_57,
          }		,    )







    @require_torch
    def     lowercase_ (   self				:						List[Any]			):
      a		:      Dict       =  True
      a		:      str       =  self.tokenizer(
          'UN Chief says there is no military solution in Syria'		,    src_lang='eng_Latn'		,    tgt_lang='fra_Latn'			)
      self.assertEqual(
          inputs.input_ids		,    [1_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2, 25_60_47]			)

      a		:      Optional[Any]       =  False
      a		:      Dict       =  self.tokenizer(
          'UN Chief says there is no military solution in Syria'		,    src_lang='eng_Latn'		,    tgt_lang='fra_Latn'			)
      self.assertEqual(
          inputs.input_ids		,    [25_60_47, 1_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2]			)




'''simple docstring'''






class 							a__:







    def __init__(   self				:						Dict		,    __snake_case				:						Optional[int]		,    __snake_case				:						Any		,    __snake_case				:						Tuple			):
      a		:      List[str]       =  name
      a		:      Dict       =  value
      a		:      List[str]       =  weight







    def __repr__(   self				:						int			):
      return F"""{self.__class__.__name__}({self.name}, {self.value}, {self.weight})"""







    def     lowercase_ (   self				:						Optional[int]			):
      return self.value







    def     lowercase_ (   self				:						List[str]			):
      return self.name







    def     lowercase_ (   self				:						int			):
      return self.weight







    def     lowercase_ (   self				:						List[str]			):
      return self.value / self.weight
def    lowerCamelCase__ (		_A				,    _A				,    _A       ):
  a		:      Optional[int]       =  []
  for i in range(len(_A       )       ):
    menu.append(Things(name[i]				,    value[i]				,    weight[i]       )       )
  return menu
def    lowerCamelCase__ (		_A				,    _A				,    _A       ):
  a		:      Optional[Any]       =  sorted(_A				,    key=_A				,    reverse=_A       )
  a		:      Optional[int]       =  []
  a     ,			a		:      str       =  0.0, 0.0
  for i in range(len(_A       )       ):
    if (total_cost + items_copy[i].get_weight()) <= max_cost:
      result.append(items_copy[i]       )
      total_cost += items_copy[i].get_weight()
      total_value += items_copy[i].get_value()
  return (result, total_value)
def    lowerCamelCase__ (		):
  pass


if __name__ == "__main__":
     import doctest

     doctest.testmod()