

"""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


_A							=  get_tests_dir("""fixtures/test_sentencepiece.model""")

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

_A							=  25_00_04
_A							=  25_00_20

@require_sentencepiece
@require_tokenizers
class       lowerCamelCase	(       lowerCAmelCase__					,					unittest.TestCase   ):


  '''simple docstring'''







  SCREAMING_SNAKE_CASE					      =  MBartaaTokenizer
  SCREAMING_SNAKE_CASE					      =  MBartaaTokenizerFast
  SCREAMING_SNAKE_CASE					      =  True
  SCREAMING_SNAKE_CASE					      =  True



  def  _a      (self	):


        """simple docstring"""

        super().setUp()

        # We have a SentencePiece fixture for testing
        UpperCAmelCase__			:							Optional[int]							=    MBartaaTokenizer(_lowerCamelCase							,       src_lang="""en_XX"""							,       tgt_lang="""ro_RO"""							,       keep_accents=_lowerCamelCase	)
        tokenizer.save_pretrained(self.tmpdirname	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							int							=    """<s>"""
        UpperCAmelCase__			:							Tuple							=    0

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



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Union[str, Any]							=    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(_lowerCamelCase	)							,       1054	)



  def  _a      (self	):


        """simple docstring"""

        self.assertEqual(self.get_tokenizer().vocab_size							,       1054	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Tuple							=    MBartaaTokenizer(_lowerCamelCase							,       src_lang="""en_XX"""							,       tgt_lang="""ro_RO"""							,       keep_accents=_lowerCamelCase	)

        UpperCAmelCase__			:							List[Any]							=    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 [285, 46, 10, 170, 382]]							,       )

        UpperCAmelCase__			:							int							=    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""", """."""]							,       )
        UpperCAmelCase__			:							Tuple							=    tokenizer.convert_tokens_to_ids(_lowerCamelCase	)
        self.assertListEqual(
            _lowerCamelCase							,       [
                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]
            ]							,       )

        UpperCAmelCase__			:							List[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>""", """."""]							,       )



  @slow
  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							int							=    {"""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=_lowerCamelCase							,       model_name="""facebook/mbart-large-50"""							,       revision="""d3913889c59cd5c9e456b269c376325eabad57e2"""							,       )




  def  _a      (self	):


        """simple docstring"""

        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

        UpperCAmelCase__			:							Union[str, Any]							=    (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})"""	):
                    UpperCAmelCase__			:							Optional[Any]							=    self.rust_tokenizer_class.from_pretrained(_lowerCamelCase							,       **_lowerCamelCase	)
                    UpperCAmelCase__			:							Any							=    self.tokenizer_class.from_pretrained(_lowerCamelCase							,       **_lowerCamelCase	)

                    UpperCAmelCase__			:							Optional[int]							=    tempfile.mkdtemp()

                    UpperCAmelCase__			:							str							=    tokenizer_r.save_pretrained(_lowerCamelCase	)
                    UpperCAmelCase__			:							Tuple							=    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	)	)
                    UpperCAmelCase__			:							List[str]							=    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
                    UpperCAmelCase__			:							Dict							=    tokenizer_r.from_pretrained(_lowerCamelCase	)
                    UpperCAmelCase__			:							List[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
                    UpperCAmelCase__			:							Optional[int]							=    tempfile.mkdtemp()

                    UpperCAmelCase__			:							List[Any]							=    tokenizer_r.save_pretrained(_lowerCamelCase							,       legacy_format=_lowerCamelCase	)
                    UpperCAmelCase__			:							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
                    UpperCAmelCase__			:							Tuple							=    tokenizer_r.from_pretrained(_lowerCamelCase	)
                    UpperCAmelCase__			:							Optional[int]							=    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
                    UpperCAmelCase__			:							int							=    tempfile.mkdtemp()

                    UpperCAmelCase__			:							Dict							=    tokenizer_r.save_pretrained(_lowerCamelCase							,       legacy_format=_lowerCamelCase	)
                    UpperCAmelCase__			:							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
                    UpperCAmelCase__			:							Dict							=    tokenizer_r.from_pretrained(_lowerCamelCase	)
                    UpperCAmelCase__			:							Dict							=    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       lowerCamelCase	(       unittest.TestCase   ):


  '''simple docstring'''







  SCREAMING_SNAKE_CASE					      =  'facebook/mbart-large-50-one-to-many-mmt'
  SCREAMING_SNAKE_CASE					      =  [
      ' 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					      =  [
      '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					      =  [EN_CODE, 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]



  @classmethod
  def  _a      (cls	):


        """simple docstring"""

        UpperCAmelCase__			:							MBartaaTokenizer							=    MBartaaTokenizer.from_pretrained(
            cls.checkpoint_name							,       src_lang="""en_XX"""							,       tgt_lang="""ro_RO"""	)
        UpperCAmelCase__			:							Dict							=    1
        return cls



  def  _a      (self	):


        """simple docstring"""

        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  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Optional[Any]							=    self.tokenizer.batch_encode_plus(self.src_text	).input_ids[0]
        self.assertListEqual(self.expected_src_tokens							,       _lowerCamelCase	)



  def  _a      (self	):


        """simple docstring"""

        self.assertIn(_lowerCamelCase							,       self.tokenizer.all_special_ids	)
        UpperCAmelCase__			:							Any							=    [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
        UpperCAmelCase__			:							Dict							=    self.tokenizer.decode(_lowerCamelCase							,       skip_special_tokens=_lowerCamelCase	)
        UpperCAmelCase__			:							Any							=    self.tokenizer.decode(generated_ids[1:]							,       skip_special_tokens=_lowerCamelCase	)
        self.assertEqual(_lowerCamelCase							,       _lowerCamelCase	)
        self.assertNotIn(self.tokenizer.eos_token							,       _lowerCamelCase	)



  def  _a      (self	):


        """simple docstring"""

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



  def  _a      (self	):


        """simple docstring"""

        self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]	)							,       [250053, 250001]	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							int							=    tempfile.mkdtemp()
        UpperCAmelCase__			:							str							=    self.tokenizer.fairseq_tokens_to_ids
        self.tokenizer.save_pretrained(_lowerCamelCase	)
        UpperCAmelCase__			:							int							=    MBartaaTokenizer.from_pretrained(_lowerCamelCase	)
        self.assertDictEqual(new_tok.fairseq_tokens_to_ids							,       _lowerCamelCase	)



  @require_torch
  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Union[str, Any]							=    self.tokenizer(self.src_text							,       text_target=self.tgt_text							,       padding=_lowerCamelCase							,       return_tensors="""pt"""	)
        UpperCAmelCase__			:							Optional[int]							=    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  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							List[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"""							,       )
        UpperCAmelCase__			:							Optional[int]							=    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	)
        UpperCAmelCase__			:							str							=    batch.input_ids.tolist()[0]
        self.assertListEqual(self.expected_src_tokens							,       _lowerCamelCase	)
        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  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Optional[Any]							=    self.tokenizer(self.src_text							,       padding=_lowerCamelCase							,       truncation=_lowerCamelCase							,       max_length=3							,       return_tensors="""pt"""	)
        UpperCAmelCase__			:							str							=    self.tokenizer(
            text_target=self.tgt_text							,       padding=_lowerCamelCase							,       truncation=_lowerCamelCase							,       max_length=10							,       return_tensors="""pt"""	)
        UpperCAmelCase__			:							Union[str, Any]							=    targets["""input_ids"""]
        UpperCAmelCase__			:							Optional[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  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Tuple							=    self.tokenizer._build_translation_inputs(
            """A test"""							,       return_tensors="""pt"""							,       src_lang="""en_XX"""							,       tgt_lang="""ar_AR"""	)

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




"""simple docstring"""
import requests




def 					a__						(						lowerCAmelCase			,	lowerCAmelCase    )	-> None:
      UpperCAmelCase__			:							List[str]							=    {"""Content-Type""": """application/json"""}
      UpperCAmelCase__			:							List[str]							=    requests.post(lowerCAmelCase			,	json={"""text""": message_body}			,	headers=lowerCAmelCase    )
      if response.status_code != 2_00:
            UpperCAmelCase__			:							str							=    (
                """Request to slack returned an error """
                F"""{response.status_code}, the response is:\n{response.text}"""
            )
            raise ValueError(lowerCAmelCase    )


if __name__ == "__main__":
    # Set the slack url to the one provided by Slack when you create the webhook at
    # https://my.slack.com/services/new/incoming-webhook/
    send_slack_message("""<YOUR MESSAGE BODY>""", """<SLACK CHANNEL URL>""")

