


'''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


__A   :    Tuple											= get_tests_dir("fixtures/test_sentencepiece.model")


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

__A   :    Union[str, Any]											= 25_0004
__A   :    Optional[Any]											= 25_0020






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







    """simple docstring"""



    lowercase  					=   MBartTokenizer
    lowercase  					=   MBartTokenizerFast
    lowercase  					=   True
    lowercase  					=   True

    def __lowercase  (  self       :    Optional[int]						)  ->    str:
      super().setUp()

      # We have a SentencePiece fixture for testing
      lowerCAmelCase_     : str     =  MBartTokenizer(lowerCamelCase       ,		keep_accents=lowerCamelCase						)
      tokenizer.save_pretrained(self.tmpdirname						)

    def __lowercase  (  self       :    str						)  ->    Union[str, Any]:
      lowerCAmelCase_     : int     =  MBartTokenizer(lowerCamelCase       ,		keep_accents=lowerCamelCase						)

      lowerCAmelCase_     : str     =  tokenizer.tokenize("""This is a test"""						)
      self.assertListEqual(lowerCamelCase       ,		["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]						)

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

      lowerCAmelCase_     : Any     =  tokenizer.tokenize("""I was born in 92000, and this is falsé."""						)
      self.assertListEqual(
          lowerCamelCase       ,		[
              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_     : List[str]     =  tokenizer.convert_tokens_to_ids(lowerCamelCase						)
      self.assertListEqual(
          lowerCamelCase       ,		[
              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]
              #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
          ]       ,		)

      lowerCAmelCase_     : Optional[Any]     =  tokenizer.convert_ids_to_tokens(lowerCamelCase						)
      self.assertListEqual(
          lowerCamelCase       ,		[
              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       :    Optional[int]						)  ->    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_     : Optional[int]     =  (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_     : Tuple     =  self.rust_tokenizer_class.from_pretrained(lowerCamelCase       ,		**lowerCamelCase						)
          lowerCAmelCase_     : Optional[Any]     =  self.tokenizer_class.from_pretrained(lowerCamelCase       ,		**lowerCamelCase						)

          lowerCAmelCase_     : Any     =  tempfile.mkdtemp()

          lowerCAmelCase_     : str     =  tokenizer_r.save_pretrained(lowerCamelCase						)
          lowerCAmelCase_     : Optional[int]     =  tokenizer_p.save_pretrained(lowerCamelCase						)

          # 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_     : int     =  tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f						)
          self.assertSequenceEqual(lowerCamelCase       ,		lowerCamelCase						)

          # Checks everything loads correctly in the same way
          lowerCAmelCase_     : Dict     =  tokenizer_r.from_pretrained(lowerCamelCase						)
          lowerCAmelCase_     : Optional[Any]     =  tokenizer_p.from_pretrained(lowerCamelCase						)

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

          shutil.rmtree(lowerCamelCase						)

          # Save tokenizer rust, legacy_format=True
          lowerCAmelCase_     : Union[str, Any]     =  tempfile.mkdtemp()

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

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

          # Checks everything loads correctly in the same way
          lowerCAmelCase_     : int     =  tokenizer_r.from_pretrained(lowerCamelCase						)
          lowerCAmelCase_     : Any     =  tokenizer_p.from_pretrained(lowerCamelCase						)

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

          shutil.rmtree(lowerCamelCase						)

          # Save tokenizer rust, legacy_format=False
          lowerCAmelCase_     : Any     =  tempfile.mkdtemp()

          lowerCAmelCase_     : Tuple     =  tokenizer_r.save_pretrained(lowerCamelCase       ,		legacy_format=lowerCamelCase						)
          lowerCAmelCase_     : int     =  tokenizer_p.save_pretrained(lowerCamelCase						)

          # 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_     : Optional[Any]     =  tokenizer_r.from_pretrained(lowerCamelCase						)
          lowerCAmelCase_     : Any     =  tokenizer_p.from_pretrained(lowerCamelCase						)

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

          shutil.rmtree(lowerCamelCase						)







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







    """simple docstring"""



    lowercase  					=   'facebook/mbart-large-en-ro'
    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  					=   [82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2, EN_CODE]

    @classmethod
    def __lowercase  (  cls       :    List[Any]						)  ->    str:
      lowerCAmelCase_     : MBartTokenizer     =  MBartTokenizer.from_pretrained(
          cls.checkpoint_name       ,		src_lang="""en_XX"""       ,		tgt_lang="""ro_RO"""						)
      lowerCAmelCase_     : List[Any]     =  1
      return cls

    def __lowercase  (  self       :    Union[str, Any]						)  ->    Union[str, Any]:
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ar_AR"""]       ,		25_00_01						)
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""en_EN"""]       ,		25_00_04						)
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ro_RO"""]       ,		25_00_20						)

    def __lowercase  (  self       :    Optional[Any]						)  ->    Any:
      lowerCAmelCase_     : Dict     =  self.tokenizer.batch_encode_plus(self.src_text						).input_ids[0]
      self.assertListEqual(self.expected_src_tokens       ,		lowerCamelCase						)

    def __lowercase  (  self       :    Any						)  ->    List[Any]:
      self.assertIn(lowerCamelCase       ,		self.tokenizer.all_special_ids						)
      lowerCAmelCase_     : List[str]     =  [RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
      lowerCAmelCase_     : Tuple     =  self.tokenizer.decode(lowerCamelCase       ,		skip_special_tokens=lowerCamelCase						)
      lowerCAmelCase_     : Any     =  self.tokenizer.decode(generated_ids[1:]       ,		skip_special_tokens=lowerCamelCase						)
      self.assertEqual(lowerCamelCase       ,		lowerCamelCase						)
      self.assertNotIn(self.tokenizer.eos_token       ,		lowerCamelCase						)

    def __lowercase  (  self       :    str						)  ->    Tuple:
      lowerCAmelCase_     : List[Any]     =  ["""this is gunna be a long sentence """ * 20]
      assert isinstance(src_text[0]       ,		lowerCamelCase						)
      lowerCAmelCase_     : str     =  10
      lowerCAmelCase_     : Optional[int]     =  self.tokenizer(lowerCamelCase       ,		max_length=lowerCamelCase       ,		truncation=lowerCamelCase						).input_ids[0]
      self.assertEqual(ids[-2]       ,		2						)
      self.assertEqual(ids[-1]       ,		lowerCamelCase						)
      self.assertEqual(len(lowerCamelCase						)       ,		lowerCamelCase						)

    def __lowercase  (  self       :    Optional[Any]						)  ->    List[Any]:
      self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]						)       ,		[25_00_26, 25_00_01]						)

    def __lowercase  (  self       :    Optional[int]						)  ->    Tuple:
      lowerCAmelCase_     : List[str]     =  tempfile.mkdtemp()
      lowerCAmelCase_     : int     =  self.tokenizer.fairseq_tokens_to_ids
      self.tokenizer.save_pretrained(lowerCamelCase						)
      lowerCAmelCase_     : List[str]     =  MBartTokenizer.from_pretrained(lowerCamelCase						)
      self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,		lowerCamelCase						)

    @require_torch
    def __lowercase  (  self       :    Union[str, Any]						)  ->    Tuple:
      lowerCAmelCase_     : Optional[Any]     =  self.tokenizer(self.src_text       ,		text_target=self.tgt_text       ,		padding=lowerCamelCase       ,		return_tensors="""pt"""						)
      lowerCAmelCase_     : Any     =  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 __lowercase  (  self       :    Optional[Any]						)  ->    Tuple:
      lowerCAmelCase_     : str     =  self.tokenizer(
          self.src_text       ,		text_target=self.tgt_text       ,		padding=lowerCamelCase       ,		truncation=lowerCamelCase       ,		max_length=len(self.expected_src_tokens						)       ,		return_tensors="""pt"""       ,		)

      lowerCAmelCase_     : List[str]     =  shift_tokens_right(batch["""labels"""]       ,		self.tokenizer.pad_token_id						)

      self.assertIsInstance(lowerCamelCase       ,		lowerCamelCase						)

      self.assertEqual((2, 14)       ,		batch.input_ids.shape						)
      self.assertEqual((2, 14)       ,		batch.attention_mask.shape						)
      lowerCAmelCase_     : str     =  batch.input_ids.tolist()[0]
      self.assertListEqual(self.expected_src_tokens       ,		lowerCamelCase						)
      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 __lowercase  (  self       :    int						)  ->    int:
      lowerCAmelCase_     : Optional[Any]     =  self.tokenizer(self.src_text       ,		padding=lowerCamelCase       ,		truncation=lowerCamelCase       ,		max_length=3       ,		return_tensors="""pt"""						)
      lowerCAmelCase_     : List[Any]     =  self.tokenizer(
          text_target=self.tgt_text       ,		padding=lowerCamelCase       ,		truncation=lowerCamelCase       ,		max_length=10       ,		return_tensors="""pt"""						)
      lowerCAmelCase_     : Dict     =  targets["""input_ids"""]
      lowerCAmelCase_     : int     =  shift_tokens_right(lowerCamelCase       ,		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 __lowercase  (  self       :    str						)  ->    Union[str, Any]:
      lowerCAmelCase_     : int     =  self.tokenizer._build_translation_inputs(
          """A test"""       ,		return_tensors="""pt"""       ,		src_lang="""en_XX"""       ,		tgt_lang="""ar_AR"""						)

      self.assertEqual(
          nested_simplify(lowerCamelCase						)       ,		{
              # A, test, EOS, en_XX
              """input_ids""": [[62, 30_34, 2, 25_00_04]],
              """attention_mask""": [[1, 1, 1, 1]],
              # ar_AR
              """forced_bos_token_id""": 25_00_01,
          }       ,		)







'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__A   :    str											= {
    "configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
    "tokenization_roc_bert": ["RoCBertTokenizer"],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  pass

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A   :    Optional[int]											= [
      "ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
      "RoCBertForCausalLM",
      "RoCBertForMaskedLM",
      "RoCBertForMultipleChoice",
      "RoCBertForPreTraining",
      "RoCBertForQuestionAnswering",
      "RoCBertForSequenceClassification",
      "RoCBertForTokenClassification",
      "RoCBertLayer",
      "RoCBertModel",
      "RoCBertPreTrainedModel",
      "load_tf_weights_in_roc_bert",
  ]

if TYPE_CHECKING:
  from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
  from .tokenization_roc_bert import RoCBertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    raise OptionalDependencyNotAvailable()

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_roc_bert import (
        ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        RoCBertForCausalLM,
        RoCBertForMaskedLM,
        RoCBertForMultipleChoice,
        RoCBertForPreTraining,
        RoCBertForQuestionAnswering,
        RoCBertForSequenceClassification,
        RoCBertForTokenClassification,
        RoCBertLayer,
        RoCBertModel,
        RoCBertPreTrainedModel,
        load_tf_weights_in_roc_bert,
    )


else:
  import sys

  __A   :    Optional[int]											= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



