


"""simple docstring"""






import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


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

if is_torch_available():
   from transformers.models.mbart.modeling_mbart import shift_tokens_right

__snake_case				=				250004
__snake_case				=				250020


@require_sentencepiece
@require_tokenizers
class 			__lowerCamelCase     (    __snake_case     ,    unittest.TestCase ):

     '''simple docstring'''
     A_				:		Optional[int]			=						MBartaaTokenizer
     A_				:		Optional[Any]			=						MBartaaTokenizerFast
     A_				:		List[Any]			=						True
     A_				:		Union[str, Any]			=						True


     def 							_UpperCAmelCase					(					self							)				->							Any:
          super().setUp()

          # We have a SentencePiece fixture for testing
          _a					= MBartaaTokenizer(__UpperCAmelCase			, src_lang='''en_XX'''			, tgt_lang='''ro_RO'''			, keep_accents=__UpperCAmelCase							)
          tokenizer.save_pretrained(self.tmpdirname							)


     def 							_UpperCAmelCase					(					self							)				->							Optional[Any]:
          _a					= '<s>'
          _a					= 0

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


     def 							_UpperCAmelCase					(					self							)				->							int:
          _a					= list(self.get_tokenizer().get_vocab().keys()							)

          self.assertEqual(vocab_keys[0]			, '''<s>'''							)
          self.assertEqual(vocab_keys[1]			, '''<pad>'''							)
          self.assertEqual(vocab_keys[-1]			, '''<mask>'''							)
          self.assertEqual(len(__UpperCAmelCase							)			, 1054							)


     def 							_UpperCAmelCase					(					self							)				->							int:
          self.assertEqual(self.get_tokenizer().vocab_size			, 1054							)


     def 							_UpperCAmelCase					(					self							)				->							int:
          _a					= MBartaaTokenizer(__UpperCAmelCase			, src_lang='''en_XX'''			, tgt_lang='''ro_RO'''			, keep_accents=__UpperCAmelCase							)

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

          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(__UpperCAmelCase							)			, [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]			, )

          _a					= tokenizer.tokenize('''I was born in 92000, and this is falsé.'''							)
          self.assertListEqual(
              __UpperCAmelCase			, [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					= tokenizer.convert_tokens_to_ids(__UpperCAmelCase							)
          self.assertListEqual(
              __UpperCAmelCase			, [
                  value + tokenizer.fairseq_offset
                  for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
              ]			, )

          _a					= tokenizer.convert_ids_to_tokens(__UpperCAmelCase							)
          self.assertListEqual(
              __UpperCAmelCase			, [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>''', '''.''']			, )


     @slow
     def 							_UpperCAmelCase					(					self							)				->							List[str]:
          # fmt: off
          _a					= {'input_ids': [[250004, 11062, 82772, 7, 15, 82772, 538, 51529, 237, 17198, 1290, 206, 9, 215175, 1314, 136, 17198, 1290, 206, 9, 56359, 42, 122009, 9, 16466, 16, 87344, 4537, 9, 4717, 78381, 6, 159958, 7, 15, 24480, 618, 4, 527, 22693, 5428, 4, 2777, 24480, 9874, 4, 43523, 594, 4, 803, 18392, 33189, 18, 4, 43523, 24447, 12399, 100, 24955, 83658, 9626, 144057, 15, 839, 22335, 16, 136, 24955, 83658, 83479, 15, 39102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 122009, 115774, 23, 805, 1328, 46876, 7, 136, 53894, 1940, 42227, 41159, 17721, 823, 425, 4, 27512, 98722, 206, 136, 5531, 4970, 919, 17336, 5, 2], [250004, 20080, 618, 83, 82775, 47, 479, 9, 1517, 73, 53894, 333, 80581, 110117, 18811, 5256, 1295, 51, 152526, 297, 7986, 390, 124416, 538, 35431, 214, 98, 15044, 25737, 136, 7108, 43701, 23, 756, 135355, 7, 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], [250004, 581, 63773, 119455, 6, 147797, 88203, 7, 645, 70, 21, 3285, 10269, 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]], '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, 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], [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]]}  # noqa: E501
          # fmt: on

          self.tokenizer_integration_test_util(
              expected_encoding=__UpperCAmelCase			, model_name='''facebook/mbart-large-50'''			, revision='''d3913889c59cd5c9e456b269c376325eabad57e2'''			, )





     def 							_UpperCAmelCase					(					self							)				->							Optional[Any]:
          if not self.test_slow_tokenizer:
               # as we don't have a slow version, we can't compare the outputs between slow and fast versions
               return

          _a					= (self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
               with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'							):
                    _a					= self.rust_tokenizer_class.from_pretrained(__UpperCAmelCase			, **__UpperCAmelCase							)
                    _a					= self.tokenizer_class.from_pretrained(__UpperCAmelCase			, **__UpperCAmelCase							)

                    _a					= tempfile.mkdtemp()

                    _a					= tokenizer_r.save_pretrained(__UpperCAmelCase							)
                    _a					= tokenizer_p.save_pretrained(__UpperCAmelCase							)

                    # 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					= tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f							)
                    self.assertSequenceEqual(__UpperCAmelCase			, __UpperCAmelCase							)

                    # Checks everything loads correctly in the same way
                    _a					= tokenizer_r.from_pretrained(__UpperCAmelCase							)
                    _a					= tokenizer_p.from_pretrained(__UpperCAmelCase							)

                    # Check special tokens are set accordingly on Rust and Python
                    for key in tokenizer_pp.special_tokens_map:
                         self.assertTrue(hasattr(__UpperCAmelCase			, __UpperCAmelCase							)							)
                         # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                         # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                    shutil.rmtree(__UpperCAmelCase							)

                    # Save tokenizer rust, legacy_format=True
                    _a					= tempfile.mkdtemp()

                    _a					= tokenizer_r.save_pretrained(__UpperCAmelCase			, legacy_format=__UpperCAmelCase							)
                    _a					= tokenizer_p.save_pretrained(__UpperCAmelCase							)

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

                    # Checks everything loads correctly in the same way
                    _a					= tokenizer_r.from_pretrained(__UpperCAmelCase							)
                    _a					= tokenizer_p.from_pretrained(__UpperCAmelCase							)

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

                    shutil.rmtree(__UpperCAmelCase							)

                    # Save tokenizer rust, legacy_format=False
                    _a					= tempfile.mkdtemp()

                    _a					= tokenizer_r.save_pretrained(__UpperCAmelCase			, legacy_format=__UpperCAmelCase							)
                    _a					= tokenizer_p.save_pretrained(__UpperCAmelCase							)

                    # 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					= tokenizer_r.from_pretrained(__UpperCAmelCase							)
                    _a					= tokenizer_p.from_pretrained(__UpperCAmelCase							)

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

                    shutil.rmtree(__UpperCAmelCase							)







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

     '''simple docstring'''
     A_				:		int			=						"""facebook/mbart-large-50-one-to-many-mmt"""
     A_				:		Optional[Any]			=						[
         """ 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.""",
     ]
     A_				:		Union[str, Any]			=						[EN_CODE, 8_274, 127_873, 25_916, 7, 8_622, 2_071, 438, 67_485, 53, 187_895, 23, 51_712, 2]


     @classmethod
     def 							_UpperCAmelCase					(					cls							)				->							Tuple:
          _a					= MBartaaTokenizer.from_pretrained(
              cls.checkpoint_name			, src_lang='''en_XX'''			, tgt_lang='''ro_RO'''							)
          _a					= 1
          return cls


     def 							_UpperCAmelCase					(					self							)				->							Optional[Any]:
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ar_AR''']			, 250001							)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''en_EN''']			, 250004							)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ro_RO''']			, 250020							)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''mr_IN''']			, 250038							)


     def 							_UpperCAmelCase					(					self							)				->							Tuple:
          _a					= self.tokenizer.batch_encode_plus(self.src_text							).input_ids[0]
          self.assertListEqual(self.expected_src_tokens			, __UpperCAmelCase							)


     def 							_UpperCAmelCase					(					self							)				->							Optional[int]:
          self.assertIn(__UpperCAmelCase			, self.tokenizer.all_special_ids							)
          _a					= [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
          _a					= self.tokenizer.decode(__UpperCAmelCase			, skip_special_tokens=__UpperCAmelCase							)
          _a					= self.tokenizer.decode(generated_ids[1:]			, skip_special_tokens=__UpperCAmelCase							)
          self.assertEqual(__UpperCAmelCase			, __UpperCAmelCase							)
          self.assertNotIn(self.tokenizer.eos_token			, __UpperCAmelCase							)


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


     def 							_UpperCAmelCase					(					self							)				->							Dict:
          self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['''<mask>''', '''ar_AR''']							)			, [250053, 250001]							)


     def 							_UpperCAmelCase					(					self							)				->							Optional[int]:
          _a					= tempfile.mkdtemp()
          _a					= self.tokenizer.fairseq_tokens_to_ids
          self.tokenizer.save_pretrained(__UpperCAmelCase							)
          _a					= MBartaaTokenizer.from_pretrained(__UpperCAmelCase							)
          self.assertDictEqual(new_tok.fairseq_tokens_to_ids			, __UpperCAmelCase							)


     @require_torch
     def 							_UpperCAmelCase					(					self							)				->							List[Any]:
          _a					= self.tokenizer(self.src_text			, text_target=self.tgt_text			, padding=__UpperCAmelCase			, return_tensors='''pt'''							)
          _a					= shift_tokens_right(batch['''labels''']			, self.tokenizer.pad_token_id							)

          # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
          assert batch.input_ids[1][0] == EN_CODE
          assert batch.input_ids[1][-1] == 2
          assert batch.labels[1][0] == RO_CODE
          assert batch.labels[1][-1] == 2
          assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]


     @require_torch
     def 							_UpperCAmelCase					(					self							)				->							List[str]:
          _a					= self.tokenizer(
              self.src_text			, text_target=self.tgt_text			, padding=__UpperCAmelCase			, truncation=__UpperCAmelCase			, max_length=len(self.expected_src_tokens							)			, return_tensors='''pt'''			, )
          _a					= shift_tokens_right(batch['''labels''']			, self.tokenizer.pad_token_id							)

          self.assertIsInstance(__UpperCAmelCase			, __UpperCAmelCase							)

          self.assertEqual((2, 14)			, batch.input_ids.shape							)
          self.assertEqual((2, 14)			, batch.attention_mask.shape							)
          _a					= batch.input_ids.tolist()[0]
          self.assertListEqual(self.expected_src_tokens			, __UpperCAmelCase							)
          self.assertEqual(2			, batch.decoder_input_ids[0, 0]							)  # decoder_start_token_id
          # 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 							_UpperCAmelCase					(					self							)				->							List[Any]:
          _a					= self.tokenizer(self.src_text			, padding=__UpperCAmelCase			, truncation=__UpperCAmelCase			, max_length=3			, return_tensors='''pt'''							)
          _a					= self.tokenizer(
              text_target=self.tgt_text			, padding=__UpperCAmelCase			, truncation=__UpperCAmelCase			, max_length=10			, return_tensors='''pt'''							)
          _a					= targets['input_ids']
          _a					= shift_tokens_right(__UpperCAmelCase			, self.tokenizer.pad_token_id							)

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





     @require_torch
     def 							_UpperCAmelCase					(					self							)				->							Tuple:
          _a					= self.tokenizer._build_translation_inputs(
              '''A test'''			, return_tensors='''pt'''			, src_lang='''en_XX'''			, tgt_lang='''ar_AR'''							)

          self.assertEqual(
              nested_simplify(__UpperCAmelCase							)			, {
                  # en_XX, A, test, EOS
                  '''input_ids''': [[250004, 62, 3034, 2]],
                  '''attention_mask''': [[1, 1, 1, 1]],
                  # ar_AR
                  '''forced_bos_token_id''': 250001,
              }			, )


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case_			  = {
    '''configuration_instructblip''': [
        '''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InstructBlipConfig''',
        '''InstructBlipQFormerConfig''',
        '''InstructBlipVisionConfig''',
    ],
    '''processing_instructblip''': ['''InstructBlipProcessor'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       snake_case_			  = [
           '''INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''InstructBlipQFormerModel''',
           '''InstructBlipPreTrainedModel''',
           '''InstructBlipForConditionalGeneration''',
           '''InstructBlipVisionModel''',
       ]

if TYPE_CHECKING:
       from .configuration_instructblip import (
           INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
           InstructBlipConfig,
           InstructBlipQFormerConfig,
           InstructBlipVisionConfig,
       )
       from .processing_instructblip import InstructBlipProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_instructblip import (
                  INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  InstructBlipForConditionalGeneration,
                  InstructBlipPreTrainedModel,
                  InstructBlipQFormerModel,
                  InstructBlipVisionModel,
              )

else:
       import sys

       snake_case_			  = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

