





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__:    Optional[int]  	=	get_tests_dir('''fixtures/test_sentencepiece.model''')


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

A__:    Any  	=	25_0004
A__:    Tuple  	=	25_0020




@require_sentencepiece
@require_tokenizers
class        _a    (    UpperCamelCase__						,			unittest.TestCase):

      """simple docstring"""


      UpperCamelCase__  		=       MBartTokenizer
      UpperCamelCase__  		=       MBartTokenizerFast
      UpperCamelCase__  		=       True
      UpperCamelCase__  		=       True






      def 			UpperCAmelCase_       (		self:			Dict					):
          '''simple docstring'''


          super().setUp()

          # We have a SentencePiece fixture for testing
          UpperCamelCase__:	Union[str, Any]					=     MBartTokenizer(__lowerCamelCase	,    keep_accents=__lowerCamelCase					)
          tokenizer.save_pretrained(self.tmpdirname					)






      def 			UpperCAmelCase_       (		self:			Optional[int]					):
          '''simple docstring'''


          UpperCamelCase__:	Tuple					=     MBartTokenizer(__lowerCamelCase	,    keep_accents=__lowerCamelCase					)

          UpperCamelCase__:	Dict					=     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__:	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",
                  ".",
              ]	,    )
          UpperCamelCase__:	Union[str, Any]					=     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]
                  #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
              ]	,    )

          UpperCamelCase__:	Tuple					=     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 			UpperCAmelCase_       (		self:			Union[str, Any]					):
          '''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-mbart", {})
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"					):
                  UpperCamelCase__:	List[str]					=     self.rust_tokenizer_class.from_pretrained(__lowerCamelCase	,    **__lowerCamelCase					)
                  UpperCamelCase__:	Union[str, Any]					=     self.tokenizer_class.from_pretrained(__lowerCamelCase	,    **__lowerCamelCase					)

                  UpperCamelCase__:	str					=     tempfile.mkdtemp()

                  UpperCamelCase__:	Tuple					=     tokenizer_r.save_pretrained(__lowerCamelCase					)
                  UpperCamelCase__:	Union[str, Any]					=     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__:	List[str]					=     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					)					)
                      # 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__:	List[Any]					=     tempfile.mkdtemp()

                  UpperCamelCase__:	Any					=     tokenizer_r.save_pretrained(__lowerCamelCase	,    legacy_format=__lowerCamelCase					)
                  UpperCamelCase__:	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
                  UpperCamelCase__:	Dict					=     tokenizer_r.from_pretrained(__lowerCamelCase					)
                  UpperCamelCase__:	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
                  UpperCamelCase__:	Dict					=     tempfile.mkdtemp()

                  UpperCamelCase__:	int					=     tokenizer_r.save_pretrained(__lowerCamelCase	,    legacy_format=__lowerCamelCase					)
                  UpperCamelCase__:	List[Any]					=     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__:	Tuple					=     tokenizer_r.from_pretrained(__lowerCamelCase					)
                  UpperCamelCase__:	List[str]					=     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"""


      UpperCamelCase__  		=       """facebook/mbart-large-en-ro"""
      UpperCamelCase__  		=       [
          """ 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.""",
      ]
      UpperCamelCase__  		=       [
          """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.""",
      ]
      UpperCamelCase__  		=       [8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2, EN_CODE]






      @classmethod
      def 			UpperCAmelCase_       (		cls:			List[Any]					):
          '''simple docstring'''


          UpperCamelCase__:	MBartTokenizer					=     MBartTokenizer.from_pretrained(
              cls.checkpoint_name	,    src_lang="en_XX"	,    tgt_lang="ro_RO"					)
          UpperCamelCase__:	int					=     1
          return cls






      def 			UpperCAmelCase_       (		self:			Optional[Any]					):
          '''simple docstring'''


          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]	,    25_0001					)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]	,    25_0004					)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]	,    25_0020					)






      def 			UpperCAmelCase_       (		self:			List[str]					):
          '''simple docstring'''


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






      def 			UpperCAmelCase_       (		self:			str					):
          '''simple docstring'''


          self.assertIn(__lowerCamelCase	,    self.tokenizer.all_special_ids					)
          UpperCamelCase__:	List[Any]					=     [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
          UpperCamelCase__:	List[str]					=     self.tokenizer.decode(__lowerCamelCase	,    skip_special_tokens=__lowerCamelCase					)
          UpperCamelCase__:	Union[str, Any]					=     self.tokenizer.decode(generated_ids[1:]	,    skip_special_tokens=__lowerCamelCase					)
          self.assertEqual(__lowerCamelCase	,    __lowerCamelCase					)
          self.assertNotIn(self.tokenizer.eos_token	,    __lowerCamelCase					)






      def 			UpperCAmelCase_       (		self:			Any					):
          '''simple docstring'''


          UpperCamelCase__:	str					=     ["this is gunna be a long sentence " * 20]
          assert isinstance(src_text[0]	,    __lowerCamelCase					)
          UpperCamelCase__:	Optional[Any]					=     10
          UpperCamelCase__:	Tuple					=     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 			UpperCAmelCase_       (		self:			int					):
          '''simple docstring'''


          self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]					)	,    [25_0026, 25_0001]					)






      def 			UpperCAmelCase_       (		self:			int					):
          '''simple docstring'''


          UpperCamelCase__:	Optional[Any]					=     tempfile.mkdtemp()
          UpperCamelCase__:	Optional[Any]					=     self.tokenizer.fairseq_tokens_to_ids
          self.tokenizer.save_pretrained(__lowerCamelCase					)
          UpperCamelCase__:	Dict					=     MBartTokenizer.from_pretrained(__lowerCamelCase					)
          self.assertDictEqual(new_tok.fairseq_tokens_to_ids	,    __lowerCamelCase					)






      @require_torch
      def 			UpperCAmelCase_       (		self:			List[Any]					):
          '''simple docstring'''


          UpperCamelCase__:	int					=     self.tokenizer(self.src_text	,    text_target=self.tgt_text	,    padding=__lowerCamelCase	,    return_tensors="pt"					)
          UpperCamelCase__:	List[str]					=     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:			Union[str, Any]					):
          '''simple docstring'''


          UpperCamelCase__:	Tuple					=     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__:	List[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 			UpperCAmelCase_       (		self:			Tuple					):
          '''simple docstring'''


          UpperCamelCase__:	str					=     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__:	Optional[int]					=     targets["input_ids"]
          UpperCamelCase__:	Dict					=     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 			UpperCAmelCase_       (		self:			Optional[Any]					):
          '''simple docstring'''


          UpperCamelCase__:	List[Any]					=     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, 3034, 2, 25_0004]],
                  "attention_mask": [[1, 1, 1, 1]],
                  # ar_AR
                  "forced_bos_token_id": 25_0001,
              }	,    )








import os
from shutil import copyfile
from typing import List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A__:    Union[str, Any]  	=	logging.get_logger(__name__)

A__:    int  	=	{'''vocab_file''': '''sentencepiece.model'''}

A__:    Dict  	=	{
    '''vocab_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/sentencepiece.model''',
    },
}

A__:    Any  	=	{
    '''google/rembert''': 256,
}




class        _a    (    UpperCamelCase__):

      """simple docstring"""


      UpperCamelCase__  		=       VOCAB_FILES_NAMES
      UpperCamelCase__  		=       PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase__  		=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES






      def __init__(		self:			str	,    __lowerCamelCase:			Optional[Any]	,    __lowerCamelCase:			List[str]=False	,    __lowerCamelCase:			Optional[Any]=True	,    __lowerCamelCase:			Dict=True	,    __lowerCamelCase:			Tuple="[CLS]"	,    __lowerCamelCase:			List[str]="[SEP]"	,    __lowerCamelCase:			List[str]="[UNK]"	,    __lowerCamelCase:			Union[str, Any]="[SEP]"	,    __lowerCamelCase:			List[Any]="[PAD]"	,    __lowerCamelCase:			Optional[int]="[CLS]"	,    __lowerCamelCase:			str="[MASK]"	,    **__lowerCamelCase:			Union[str, Any]	,    ):
          '''simple docstring'''


          super().__init__(
              do_lower_case=__lowerCamelCase	,    remove_space=__lowerCamelCase	,    keep_accents=__lowerCamelCase	,    bos_token=__lowerCamelCase	,    eos_token=__lowerCamelCase	,    unk_token=__lowerCamelCase	,    sep_token=__lowerCamelCase	,    pad_token=__lowerCamelCase	,    cls_token=__lowerCamelCase	,    mask_token=__lowerCamelCase	,    **__lowerCamelCase	,    )

          UpperCamelCase__:	Optional[int]					=     do_lower_case
          UpperCamelCase__:	Optional[int]					=     remove_space
          UpperCamelCase__:	str					=     keep_accents
          UpperCamelCase__:	Union[str, Any]					=     vocab_file

          UpperCamelCase__:	Any					=     spm.SentencePieceProcessor()
          self.sp_model.Load(__lowerCamelCase					)






      @property
      def 			UpperCAmelCase_       (		self:			Any					):
          '''simple docstring'''


          return len(self.sp_model					)






      def 			UpperCAmelCase_       (		self:			Optional[Any]					):
          '''simple docstring'''


          UpperCamelCase__:	List[Any]					=     {self.convert_ids_to_tokens(__lowerCamelCase					): i for i in range(self.vocab_size					)}
          vocab.update(self.added_tokens_encoder					)
          return vocab






      def __getstate__(		self:			Optional[int]					):
          '''simple docstring'''


          UpperCamelCase__:	Any					=     self.__dict__.copy()
          UpperCamelCase__:	str					=     None
          return state






      def __setstate__(		self:			Optional[int]	,    __lowerCamelCase:			Union[str, Any]					):
          '''simple docstring'''


          UpperCamelCase__:	int					=     d
          UpperCamelCase__:	List[Any]					=     spm.SentencePieceProcessor()
          self.sp_model.Load(self.vocab_file					)






      def 			UpperCAmelCase_       (		self:			Tuple	,    __lowerCamelCase:			str	,    __lowerCamelCase:			Optional[Any]=False					):
          '''simple docstring'''


          UpperCamelCase__:	Union[str, Any]					=     self.sp_model.EncodeAsPieces(__lowerCamelCase					)
          return pieces






      def 			UpperCAmelCase_       (		self:			Tuple	,    __lowerCamelCase:			Union[str, Any]					):
          '''simple docstring'''


          return self.sp_model.PieceToId(__lowerCamelCase					)






      def 			UpperCAmelCase_       (		self:			Tuple	,    __lowerCamelCase:			Optional[int]					):
          '''simple docstring'''


          return self.sp_model.IdToPiece(__lowerCamelCase					)






      def 			UpperCAmelCase_       (		self:			Optional[Any]	,    __lowerCamelCase:			Any					):
          '''simple docstring'''


          UpperCamelCase__:	Optional[Any]					=     self.sp_model.decode_pieces(__lowerCamelCase					)
          return out_string






      def 			UpperCAmelCase_       (		self:			Any	,    __lowerCamelCase:			List[int]	,    __lowerCamelCase:			Optional[List[int]] = None					):
          '''simple docstring'''


          UpperCamelCase__:	int					=     [self.sep_token_id]
          UpperCamelCase__:	int					=     [self.cls_token_id]
          if token_ids_a is None:
              return cls + token_ids_a + sep
          return cls + token_ids_a + sep + token_ids_a + sep






      def 			UpperCAmelCase_       (		self:			List[str]	,    __lowerCamelCase:			List[int]	,    __lowerCamelCase:			Optional[List[int]] = None	,    __lowerCamelCase:			bool = False					):
          '''simple docstring'''


          if already_has_special_tokens:
              if token_ids_a is not None:
                  raise ValueError(
                      "You should not supply a second sequence if the provided sequence of "
                      "ids is already formatted with special tokens for the model."					)
              return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

          if token_ids_a is not None:
              return [1] + ([0] * len(__lowerCamelCase					)) + [1] + ([0] * len(__lowerCamelCase					)) + [1]
          return [1] + ([0] * len(__lowerCamelCase					)) + [1]






      def 			UpperCAmelCase_       (		self:			Any	,    __lowerCamelCase:			List[int]	,    __lowerCamelCase:			Optional[List[int]] = None					):
          '''simple docstring'''


          UpperCamelCase__:	Dict					=     [self.sep_token_id]
          UpperCamelCase__:	Dict					=     [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:			Optional[Any]	,    __lowerCamelCase:			str	,    __lowerCamelCase:			Optional[str] = None					):
          '''simple docstring'''


          if not os.path.isdir(__lowerCamelCase					):
              logger.error("Vocabulary path ({}) should be a directory".format(__lowerCamelCase					)					)
              return
          UpperCamelCase__:	Dict					=     os.path.join(
              __lowerCamelCase	,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)

          if os.path.abspath(self.vocab_file					) != os.path.abspath(__lowerCamelCase					):
              copyfile(self.vocab_file	,    __lowerCamelCase					)

          return (out_vocab_file,)

