






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 				_A			(     _SCREAMING_SNAKE_CASE					,					unittest.TestCase				):
    """simple docstring"""

    lowerCamelCase	:							Optional[int]				= MBartaaTokenizer
    lowerCamelCase	:							List[Any]				= MBartaaTokenizerFast
    lowerCamelCase	:							Any				= True
    lowerCamelCase	:							List[Any]				= True



    def _a							(				self      :     List[str]      )      ->							Any:
           super().setUp()

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



    def _a							(				self      :     Union[str, Any]      )      ->							Union[str, Any]:
           __UpperCAmelCase     				="""<s>"""
           __UpperCAmelCase     				=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      :     Tuple      )      ->							Dict:
           __UpperCAmelCase     				=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      :     List[str]      )      ->							Any:
           self.assertEqual(self.get_tokenizer().vocab_size ,     1054      )



    def _a							(				self      :     str      )      ->							Optional[int]:
           __UpperCAmelCase     				=MBartaaTokenizer(lowerCAmelCase_ ,     src_lang="""en_XX""" ,     tgt_lang="""ro_RO""" ,     keep_accents=lowerCAmelCase_      )

           __UpperCAmelCase     				=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     				=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     				=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     				=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      :     Dict      )      ->							Tuple:
           # fmt: off
           __UpperCAmelCase     				={"""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      :     Any      )      ->							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

           __UpperCAmelCase     				=(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     				=self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_ ,     **lowerCAmelCase_      )
                         __UpperCAmelCase     				=self.tokenizer_class.from_pretrained(lowerCAmelCase_ ,     **lowerCAmelCase_      )

                         __UpperCAmelCase     				=tempfile.mkdtemp()

                         __UpperCAmelCase     				=tokenizer_r.save_pretrained(lowerCAmelCase_      )
                         __UpperCAmelCase     				=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     				=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     				=tokenizer_r.from_pretrained(lowerCAmelCase_      )
                         __UpperCAmelCase     				=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     				=tempfile.mkdtemp()

                         __UpperCAmelCase     				=tokenizer_r.save_pretrained(lowerCAmelCase_ ,     legacy_format=lowerCAmelCase_      )
                         __UpperCAmelCase     				=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     				=tokenizer_r.from_pretrained(lowerCAmelCase_      )
                         __UpperCAmelCase     				=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     				=tempfile.mkdtemp()

                         __UpperCAmelCase     				=tokenizer_r.save_pretrained(lowerCAmelCase_ ,     legacy_format=lowerCAmelCase_      )
                         __UpperCAmelCase     				=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     				=tokenizer_r.from_pretrained(lowerCAmelCase_      )
                         __UpperCAmelCase     				=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 				_A			(     unittest.TestCase				):
    """simple docstring"""

    lowerCamelCase	:							Dict				= """facebook/mbart-large-50-one-to-many-mmt"""
    lowerCamelCase	:							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.""",
    ]
    lowerCamelCase	:							List[str]				= [
        """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.""",
    ]
    lowerCamelCase	:							Tuple				= [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 _a							(				cls      :     Dict      )      ->							Union[str, Any]:
           __UpperCAmelCase     				=MBartaaTokenizer.from_pretrained(
               cls.checkpoint_name ,     src_lang="""en_XX""" ,     tgt_lang="""ro_RO"""      )
           __UpperCAmelCase     				=1
           return cls



    def _a							(				self      :     Optional[Any]      )      ->							Optional[int]:
           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      :     List[Any]      )      ->							List[Any]:
           __UpperCAmelCase     				=self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
           self.assertListEqual(self.expected_src_tokens ,     lowerCAmelCase_      )



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



    def _a							(				self      :     List[str]      )      ->							Any:
           __UpperCAmelCase     				=["""this is gunna be a long sentence """ * 20]
           assert isinstance(src_text[0] ,     lowerCAmelCase_      )
           __UpperCAmelCase     				=10
           __UpperCAmelCase     				=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      :     Tuple      )      ->							Any:
           self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]      ) ,     [250053, 250001]      )



    def _a							(				self      :     Union[str, Any]      )      ->							Union[str, Any]:
           __UpperCAmelCase     				=tempfile.mkdtemp()
           __UpperCAmelCase     				=self.tokenizer.fairseq_tokens_to_ids
           self.tokenizer.save_pretrained(lowerCAmelCase_      )
           __UpperCAmelCase     				=MBartaaTokenizer.from_pretrained(lowerCAmelCase_      )
           self.assertDictEqual(new_tok.fairseq_tokens_to_ids ,     lowerCAmelCase_      )



    @require_torch
    def _a							(				self      :     Optional[Any]      )      ->							int:
           __UpperCAmelCase     				=self.tokenizer(self.src_text ,     text_target=self.tgt_text ,     padding=lowerCAmelCase_ ,     return_tensors="""pt"""      )
           __UpperCAmelCase     				=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      :     int      )      ->							Any:
           __UpperCAmelCase     				=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     				=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     				=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      :     Dict      )      ->							int:
           __UpperCAmelCase     				=self.tokenizer(self.src_text ,     padding=lowerCAmelCase_ ,     truncation=lowerCAmelCase_ ,     max_length=3 ,     return_tensors="""pt"""      )
           __UpperCAmelCase     				=self.tokenizer(
               text_target=self.tgt_text ,     padding=lowerCAmelCase_ ,     truncation=lowerCAmelCase_ ,     max_length=10 ,     return_tensors="""pt"""      )
           __UpperCAmelCase     				=targets["""input_ids"""]
           __UpperCAmelCase     				=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      :     Dict      )      ->							Optional[int]:
           __UpperCAmelCase     				=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"""
from __future__ import annotations






def       __UpperCamelCase						(		snake_case__ , snake_case__ = None , snake_case__ = None       ):
	if start is None:
		A_		:    Dict						     = 0

	if end is None:
		A_		:    Dict						     = len(snake_case__       ) - 1

	if start >= end:
		return

	A_		:    List[Any]						     = (start + end) // 2

	slowsort(snake_case__ , snake_case__ , snake_case__       )
	slowsort(snake_case__ , mid + 1 , snake_case__       )

	if sequence[end] < sequence[mid]:
		A_     ,  A_		:    Dict						     = sequence[mid], sequence[end]

	slowsort(snake_case__ , snake_case__ , end - 1       )


if __name__ == "__main__":
							from doctest import testmod

							testmod()

