






"""simple docstring"""





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, 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


_SCREAMING_SNAKE_CASE					:				Dict					    =						get_tests_dir('''fixtures/test_sentencepiece.model''')


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

_SCREAMING_SNAKE_CASE					:				int					    =						25_0004
_SCREAMING_SNAKE_CASE					:				Union[str, Any]					    =						25_0020






@require_sentencepiece
@require_tokenizers
class      a						(					__snake_case  ,      unittest.TestCase		):
    SCREAMING_SNAKE_CASE						:     Any						= MBartTokenizer
    SCREAMING_SNAKE_CASE						:     List[Any]						= MBartTokenizerFast
    SCREAMING_SNAKE_CASE						:     Tuple						= True
    SCREAMING_SNAKE_CASE						:     Optional[int]						= True






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

      # We have a SentencePiece fixture for testing
      lowerCamelCase_         =						MBartTokenizer(__SCREAMING_SNAKE_CASE       ,						keep_accents=__SCREAMING_SNAKE_CASE					)
      tokenizer.save_pretrained(self.tmpdirname					)






    def    UpperCamelCase       (       self     :							Dict					)     ->		Any:
      lowerCamelCase_         =						MBartTokenizer(__SCREAMING_SNAKE_CASE       ,						keep_accents=__SCREAMING_SNAKE_CASE					)

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

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

      lowerCamelCase_         =						tokenizer.tokenize('I was born in 92000, and this is falsé.'					)
      self.assertListEqual(
          __SCREAMING_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',
              '.',
          ]       ,						)
      lowerCamelCase_         =						tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE					)
      self.assertListEqual(
          __SCREAMING_SNAKE_CASE       ,						[
              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]
              #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
          ]       ,						)

      lowerCamelCase_         =						tokenizer.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE					)
      self.assertListEqual(
          __SCREAMING_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    UpperCamelCase       (       self     :							Union[str, Any]					)     ->		List[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

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

          lowerCamelCase_         =						tempfile.mkdtemp()

          lowerCamelCase_         =						tokenizer_r.save_pretrained(__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						tokenizer_p.save_pretrained(__SCREAMING_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					)					)
          lowerCamelCase_         =						tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f					)
          self.assertSequenceEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)

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

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

          shutil.rmtree(__SCREAMING_SNAKE_CASE					)

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

          lowerCamelCase_         =						tokenizer_r.save_pretrained(__SCREAMING_SNAKE_CASE       ,						legacy_format=__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						tokenizer_p.save_pretrained(__SCREAMING_SNAKE_CASE					)

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

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

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

          shutil.rmtree(__SCREAMING_SNAKE_CASE					)

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

          lowerCamelCase_         =						tokenizer_r.save_pretrained(__SCREAMING_SNAKE_CASE       ,						legacy_format=__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						tokenizer_p.save_pretrained(__SCREAMING_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
          lowerCamelCase_         =						tokenizer_r.from_pretrained(__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						tokenizer_p.from_pretrained(__SCREAMING_SNAKE_CASE					)

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

          shutil.rmtree(__SCREAMING_SNAKE_CASE					)






@require_torch
@require_sentencepiece
@require_tokenizers
class      a						(					unittest.TestCase		):
    SCREAMING_SNAKE_CASE						:     Optional[int]						= """facebook/mbart-large-en-ro"""
    SCREAMING_SNAKE_CASE						:     Tuple						= [
        """ 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.""",
    ]
    SCREAMING_SNAKE_CASE						:     Optional[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.""",
    ]
    SCREAMING_SNAKE_CASE						:     List[Any]						= [8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2, EN_CODE]






    @classmethod
    def    UpperCamelCase       (       cls     :							Union[str, Any]					)     ->		Tuple:
      lowerCamelCase_         =						MBartTokenizer.from_pretrained(
          cls.checkpoint_name       ,						src_lang='en_XX'       ,						tgt_lang='ro_RO'					)
      lowerCamelCase_         =						1
      return cls






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		List[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					)






    def    UpperCamelCase       (       self     :							List[str]					)     ->		List[Any]:
      lowerCamelCase_         =						self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
      self.assertListEqual(self.expected_src_tokens       ,						__SCREAMING_SNAKE_CASE					)






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






    def    UpperCamelCase       (       self     :							str					)     ->		Union[str, Any]:
      lowerCamelCase_         =						['this is gunna be a long sentence ' * 20]
      assert isinstance(src_text[0]       ,						__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						10
      lowerCamelCase_         =						self.tokenizer(__SCREAMING_SNAKE_CASE       ,						max_length=__SCREAMING_SNAKE_CASE       ,						truncation=__SCREAMING_SNAKE_CASE					).input_ids[0]
      self.assertEqual(ids[-2]       ,						2					)
      self.assertEqual(ids[-1]       ,						__SCREAMING_SNAKE_CASE					)
      self.assertEqual(len(__SCREAMING_SNAKE_CASE					)       ,						__SCREAMING_SNAKE_CASE					)






    def    UpperCamelCase       (       self     :							Optional[int]					)     ->		Tuple:
      self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']					)       ,						[250026, 250001]					)






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		List[str]:
      lowerCamelCase_         =						tempfile.mkdtemp()
      lowerCamelCase_         =						self.tokenizer.fairseq_tokens_to_ids
      self.tokenizer.save_pretrained(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						MBartTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE					)
      self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,						__SCREAMING_SNAKE_CASE					)






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

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






    @require_torch
    def    UpperCamelCase       (       self     :							int					)     ->		Optional[int]:
      lowerCamelCase_         =						self.tokenizer(
          self.src_text       ,						text_target=self.tgt_text       ,						padding=__SCREAMING_SNAKE_CASE       ,						truncation=__SCREAMING_SNAKE_CASE       ,						max_length=len(self.expected_src_tokens					)       ,						return_tensors='pt'       ,						)

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

      self.assertIsInstance(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)

      self.assertEqual((2, 14)       ,						batch.input_ids.shape					)
      self.assertEqual((2, 14)       ,						batch.attention_mask.shape					)
      lowerCamelCase_         =						batch.input_ids.tolist()[0]
      self.assertListEqual(self.expected_src_tokens       ,						__SCREAMING_SNAKE_CASE					)
      self.assertEqual(2       ,						batch.decoder_input_ids[0, -1]					)  # EOS
      # Test that special tokens are reset
      self.assertEqual(self.tokenizer.prefix_tokens       ,						[]					)
      self.assertEqual(self.tokenizer.suffix_tokens       ,						[self.tokenizer.eos_token_id, EN_CODE]					)






    def    UpperCamelCase       (       self     :							Union[str, Any]					)     ->		Any:
      lowerCamelCase_         =						self.tokenizer(self.src_text       ,						padding=__SCREAMING_SNAKE_CASE       ,						truncation=__SCREAMING_SNAKE_CASE       ,						max_length=3       ,						return_tensors='pt'					)
      lowerCamelCase_         =						self.tokenizer(
          text_target=self.tgt_text       ,						padding=__SCREAMING_SNAKE_CASE       ,						truncation=__SCREAMING_SNAKE_CASE       ,						max_length=10       ,						return_tensors='pt'					)
      lowerCamelCase_         =						targets['input_ids']
      lowerCamelCase_         =						shift_tokens_right(__SCREAMING_SNAKE_CASE       ,						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     :							Union[str, Any]					)     ->		List[str]:
      lowerCamelCase_         =						self.tokenizer._build_translation_inputs(
          'A test'       ,						return_tensors='pt'       ,						src_lang='en_XX'       ,						tgt_lang='ar_AR'					)

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












"""simple docstring"""





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


_SCREAMING_SNAKE_CASE					:				Union[str, Any]					    =						{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

_SCREAMING_SNAKE_CASE					:				Union[str, Any]					    =						{
    '''vocab_file''': {
        '''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt''',
    },
    '''tokenizer_file''': {
        '''unc-nlp/lxmert-base-uncased''': (
            '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json'''
        ),
    },
}

_SCREAMING_SNAKE_CASE					:				Any					    =						{
    '''unc-nlp/lxmert-base-uncased''': 512,
}

_SCREAMING_SNAKE_CASE					:				int					    =						{
    '''unc-nlp/lxmert-base-uncased''': {'''do_lower_case''': True},
}






class      a						(					__snake_case		):
    SCREAMING_SNAKE_CASE						:     int						= VOCAB_FILES_NAMES
    SCREAMING_SNAKE_CASE						:     Optional[Any]						= PRETRAINED_VOCAB_FILES_MAP
    SCREAMING_SNAKE_CASE						:     Any						= PRETRAINED_INIT_CONFIGURATION
    SCREAMING_SNAKE_CASE						:     Any						= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    SCREAMING_SNAKE_CASE						:     Optional[Any]						= LxmertTokenizer






    def __init__(       self     :							str       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=None       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=None       ,						__SCREAMING_SNAKE_CASE     :							str=True       ,						__SCREAMING_SNAKE_CASE     :							List[Any]="[UNK]"       ,						__SCREAMING_SNAKE_CASE     :							int="[SEP]"       ,						__SCREAMING_SNAKE_CASE     :							int="[PAD]"       ,						__SCREAMING_SNAKE_CASE     :							List[Any]="[CLS]"       ,						__SCREAMING_SNAKE_CASE     :							Any="[MASK]"       ,						__SCREAMING_SNAKE_CASE     :							List[str]=True       ,						__SCREAMING_SNAKE_CASE     :							List[str]=None       ,						**__SCREAMING_SNAKE_CASE     :							Any       ,						)     ->		Any:
      super().__init__(
          __SCREAMING_SNAKE_CASE       ,						tokenizer_file=__SCREAMING_SNAKE_CASE       ,						do_lower_case=__SCREAMING_SNAKE_CASE       ,						unk_token=__SCREAMING_SNAKE_CASE       ,						sep_token=__SCREAMING_SNAKE_CASE       ,						pad_token=__SCREAMING_SNAKE_CASE       ,						cls_token=__SCREAMING_SNAKE_CASE       ,						mask_token=__SCREAMING_SNAKE_CASE       ,						tokenize_chinese_chars=__SCREAMING_SNAKE_CASE       ,						strip_accents=__SCREAMING_SNAKE_CASE       ,						**__SCREAMING_SNAKE_CASE       ,						)

      lowerCamelCase_         =						json.loads(self.backend_tokenizer.normalizer.__getstate__()					)
      if (
          normalizer_state.get('lowercase'       ,						__SCREAMING_SNAKE_CASE					) != do_lower_case
          or normalizer_state.get('strip_accents'       ,						__SCREAMING_SNAKE_CASE					) != strip_accents
          or normalizer_state.get('handle_chinese_chars'       ,						__SCREAMING_SNAKE_CASE					) != tokenize_chinese_chars
      ):
        lowerCamelCase_         =						getattr(__SCREAMING_SNAKE_CASE       ,						normalizer_state.pop('type'					)					)
        lowerCamelCase_         =						do_lower_case
        lowerCamelCase_         =						strip_accents
        lowerCamelCase_         =						tokenize_chinese_chars
        lowerCamelCase_         =						normalizer_class(**__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						do_lower_case






    def    UpperCamelCase       (       self     :							Tuple       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]       ,						__SCREAMING_SNAKE_CASE     :							Tuple=None					)     ->		Dict:
      lowerCamelCase_         =						[self.cls_token_id] + token_ids_a + [self.sep_token_id]

      if token_ids_a:
        output += token_ids_a + [self.sep_token_id]

      return output






    def    UpperCamelCase       (       self     :							str       ,						__SCREAMING_SNAKE_CASE     :							List[int]       ,						__SCREAMING_SNAKE_CASE     :							Optional[List[int]] = None					)     ->		List[int]:
      lowerCamelCase_         =						[self.sep_token_id]
      lowerCamelCase_         =						[self.cls_token_id]
      if token_ids_a is None:
        return len(cls + token_ids_a + sep					) * [0]
      return len(cls + token_ids_a + sep					) * [0] + len(token_ids_a + sep					) * [1]






    def    UpperCamelCase       (       self     :							List[str]       ,						__SCREAMING_SNAKE_CASE     :							str       ,						__SCREAMING_SNAKE_CASE     :							Optional[str] = None					)     ->		Tuple[str]:
      lowerCamelCase_         =						self._tokenizer.model.save(__SCREAMING_SNAKE_CASE       ,						name=__SCREAMING_SNAKE_CASE					)
      return tuple(__SCREAMING_SNAKE_CASE					)




