



"""simple docstring"""





import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging


lowerCamelCase       	=						logging.get_logger(__name__)

lowerCamelCase       	=						{"""vocab_file""": """spiece.model"""}

lowerCamelCase       	=						{
    """vocab_file""": {
        """xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model""",
        """xlnet-large-cased""": """https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model""",
    }
}

lowerCamelCase       	=						{
    """xlnet-base-cased""": None,
    """xlnet-large-cased""": None,
}

# Segments (not really needed)
lowerCamelCase       	=						0
lowerCamelCase       	=						1
lowerCamelCase       	=						2
lowerCamelCase       	=						3
lowerCamelCase       	=						4
class 				lowercase__       (   __lowercase				):







       '''simple docstring'''


       UpperCamelCase						=					VOCAB_FILES_NAMES
       UpperCamelCase						=					PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase						=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCamelCase						=					'''left'''



       def __init__(							self      :  int		,    _UpperCAmelCase      :  str		,    _UpperCAmelCase      :  int=False		,    _UpperCAmelCase      :  int=True		,    _UpperCAmelCase      :  List[str]=False		,    _UpperCAmelCase      :  Any="<s>"		,    _UpperCAmelCase      :  List[str]="</s>"		,    _UpperCAmelCase      :  int="<unk>"		,    _UpperCAmelCase      :  Dict="<sep>"		,    _UpperCAmelCase      :  str="<pad>"		,    _UpperCAmelCase      :  Tuple="<cls>"		,    _UpperCAmelCase      :  Optional[Any]="<mask>"		,    _UpperCAmelCase      :  List[str]=["<eop>", "<eod>"]		,    _UpperCAmelCase      :  Optional[Dict[str, Any]] = None		,    **_UpperCAmelCase      :  Dict		,    )			->						None:


             '''simple docstring'''




             UpperCAmelCase_      			=							AddedToken(_UpperCAmelCase		,    lstrip=_UpperCAmelCase		,    rstrip=_UpperCAmelCase   ) if isinstance(_UpperCAmelCase		,    _UpperCAmelCase   ) else mask_token

             UpperCAmelCase_      			=							{} if sp_model_kwargs is None else sp_model_kwargs

             super().__init__(
                 do_lower_case=_UpperCAmelCase		,    remove_space=_UpperCAmelCase		,    keep_accents=_UpperCAmelCase		,    bos_token=_UpperCAmelCase		,    eos_token=_UpperCAmelCase		,    unk_token=_UpperCAmelCase		,    sep_token=_UpperCAmelCase		,    pad_token=_UpperCAmelCase		,    cls_token=_UpperCAmelCase		,    mask_token=_UpperCAmelCase		,    additional_special_tokens=_UpperCAmelCase		,    sp_model_kwargs=self.sp_model_kwargs		,    **_UpperCAmelCase		,    )

             UpperCAmelCase_      			=							3

             UpperCAmelCase_      			=							do_lower_case
             UpperCAmelCase_      			=							remove_space
             UpperCAmelCase_      			=							keep_accents
             UpperCAmelCase_      			=							vocab_file

             UpperCAmelCase_      			=							spm.SentencePieceProcessor(**self.sp_model_kwargs   )
             self.sp_model.Load(_UpperCAmelCase   )



       @property
       def 					lowercase__    (							self      :  Tuple   )			->						str:


             '''simple docstring'''




             return len(self.sp_model   )



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


             '''simple docstring'''




             UpperCAmelCase_      			=							{self.convert_ids_to_tokens(_UpperCAmelCase   ): i for i in range(self.vocab_size   )}
             vocab.update(self.added_tokens_encoder   )
             return vocab



       def __getstate__(							self      :  Tuple   )			->						List[Any]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.__dict__.copy()
             UpperCAmelCase_      			=							None
             return state



       def __setstate__(							self      :  Union[str, Any]		,    _UpperCAmelCase      :  Optional[int]   )			->						Union[str, Any]:


             '''simple docstring'''




             UpperCAmelCase_      			=							d

             # for backward compatibility
             if not hasattr(self		,    "sp_model_kwargs"   ):
                   UpperCAmelCase_      			=							{}

             UpperCAmelCase_      			=							spm.SentencePieceProcessor(**self.sp_model_kwargs   )
             self.sp_model.Load(self.vocab_file   )



       def 					lowercase__    (							self      :  Dict		,    _UpperCAmelCase      :  str   )			->						List[str]:


             '''simple docstring'''




             if self.remove_space:
                   UpperCAmelCase_      			=							""" """.join(inputs.strip().split()   )
             else:
                   UpperCAmelCase_      			=							inputs
             UpperCAmelCase_      			=							outputs.replace("``"		,    "\""   ).replace("''"		,    "\""   )

             if not self.keep_accents:
                   UpperCAmelCase_      			=							unicodedata.normalize("NFKD"		,    _UpperCAmelCase   )
                   UpperCAmelCase_      			=							"""""".join([c for c in outputs if not unicodedata.combining(_UpperCAmelCase   )]   )
             if self.do_lower_case:
                   UpperCAmelCase_      			=							outputs.lower()

             return outputs



       def 					lowercase__    (							self      :  List[Any]		,    _UpperCAmelCase      :  str   )			->						List[str]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.preprocess_text(_UpperCAmelCase   )
             UpperCAmelCase_      			=							self.sp_model.encode(_UpperCAmelCase		,    out_type=_UpperCAmelCase   )
             UpperCAmelCase_      			=							[]
             for piece in pieces:
                   if len(_UpperCAmelCase   ) > 1 and piece[-1] == str(","   ) and piece[-2].isdigit():
                         UpperCAmelCase_      			=							self.sp_model.EncodeAsPieces(piece[:-1].replace(_UpperCAmelCase		,    ""   )   )
                         if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
                               if len(cur_pieces[0]   ) == 1:
                                     UpperCAmelCase_      			=							cur_pieces[1:]
                               else:
                                     UpperCAmelCase_      			=							cur_pieces[0][1:]
                         cur_pieces.append(piece[-1]   )
                         new_pieces.extend(_UpperCAmelCase   )
                   else:
                         new_pieces.append(_UpperCAmelCase   )

             return new_pieces



       def 					lowercase__    (							self      :  Tuple		,    _UpperCAmelCase      :  str   )			->						Any:


             '''simple docstring'''




             return self.sp_model.PieceToId(_UpperCAmelCase   )



       def 					lowercase__    (							self      :  Any		,    _UpperCAmelCase      :  Optional[int]   )			->						int:


             '''simple docstring'''




             return self.sp_model.IdToPiece(_UpperCAmelCase   )



       def 					lowercase__    (							self      :  str		,    _UpperCAmelCase      :  Optional[Any]   )			->						Dict:


             '''simple docstring'''




             UpperCAmelCase_      			=							"""""".join(_UpperCAmelCase   ).replace(_UpperCAmelCase		,    " "   ).strip()
             return out_string



       def 					lowercase__    (							self      :  List[Any]		,    _UpperCAmelCase      :  List[int]		,    _UpperCAmelCase      :  bool = False		,    _UpperCAmelCase      :  bool = None		,    _UpperCAmelCase      :  bool = True		,    **_UpperCAmelCase      :  Optional[int]		,    )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							kwargs.pop("use_source_tokenizer"		,    _UpperCAmelCase   )

             UpperCAmelCase_      			=							self.convert_ids_to_tokens(_UpperCAmelCase		,    skip_special_tokens=_UpperCAmelCase   )

             # To avoid mixing byte-level and unicode for byte-level BPT
             # we need to build string separately for added tokens and byte-level tokens
             # cf. https://github.com/huggingface/transformers/issues/1133
             UpperCAmelCase_      			=							[]
             UpperCAmelCase_      			=							[]
             for token in filtered_tokens:
                   if skip_special_tokens and token in self.all_special_ids:
                         continue
                   if token in self.added_tokens_encoder:
                         if current_sub_text:
                               sub_texts.append(self.convert_tokens_to_string(_UpperCAmelCase   )   )
                               UpperCAmelCase_      			=							[]
                         sub_texts.append(_UpperCAmelCase   )
                   else:
                         current_sub_text.append(_UpperCAmelCase   )
             if current_sub_text:
                   sub_texts.append(self.convert_tokens_to_string(_UpperCAmelCase   )   )

             # Mimic the behavior of the Rust tokenizer:
             # By default, there are no spaces between special tokens
             UpperCAmelCase_      			=							"""""".join(_UpperCAmelCase   )

             UpperCAmelCase_      			=							(
                 clean_up_tokenization_spaces
                 if clean_up_tokenization_spaces is not None
                 else self.clean_up_tokenization_spaces
             )
             if clean_up_tokenization_spaces:
                   UpperCAmelCase_      			=							self.clean_up_tokenization(_UpperCAmelCase   )
                   return clean_text
             else:
                   return text



       def 					lowercase__    (							self      :  List[Any]		,    _UpperCAmelCase      :  List[int]		,    _UpperCAmelCase      :  Optional[List[int]] = None   )			->						List[int]:


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  Union[str, Any]		,    _UpperCAmelCase      :  List[int]		,    _UpperCAmelCase      :  Optional[List[int]] = None		,    _UpperCAmelCase      :  bool = False   )			->						List[int]:


             '''simple docstring'''




             if already_has_special_tokens:
                   return super().get_special_tokens_mask(
                       token_ids_a=_UpperCAmelCase		,    token_ids_a=_UpperCAmelCase		,    already_has_special_tokens=_UpperCAmelCase   )

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



       def 					lowercase__    (							self      :  int		,    _UpperCAmelCase      :  List[int]		,    _UpperCAmelCase      :  Optional[List[int]] = None   )			->						List[int]:


             '''simple docstring'''




             UpperCAmelCase_      			=							[self.sep_token_id]
             UpperCAmelCase_      			=							[2]

             if token_ids_a is None:
                   return len(token_ids_a + sep   ) * [0] + cls_segment_id
             return len(token_ids_a + sep   ) * [0] + len(token_ids_a + sep   ) * [1] + cls_segment_id







       def 					lowercase__    (							self      :  Union[str, Any]		,    _UpperCAmelCase      :  str		,    _UpperCAmelCase      :  Optional[str] = None   )			->						Tuple[str]:


             '''simple docstring'''




             if not os.path.isdir(_UpperCAmelCase   ):
                   logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""   )
                   return
             UpperCAmelCase_      			=							os.path.join(
                 _UpperCAmelCase		,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )

             if os.path.abspath(self.vocab_file   ) != os.path.abspath(_UpperCAmelCase   ) and os.path.isfile(self.vocab_file   ):
                   copyfile(self.vocab_file		,    _UpperCAmelCase   )
             elif not os.path.isfile(self.vocab_file   ):
                   with open(_UpperCAmelCase		,    "wb"   ) as fi:
                         UpperCAmelCase_      			=							self.sp_model.serialized_model_proto()
                         fi.write(_UpperCAmelCase   )

             return (out_vocab_file,)









"""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


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


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

lowerCamelCase       	=						250_004
lowerCamelCase       	=						250_020
@require_sentencepiece
@require_tokenizers
class 				lowercase__       (   SCREAMING_SNAKE_CASE    , unittest.TestCase				):







       '''simple docstring'''


       UpperCamelCase						=					MBartTokenizer
       UpperCamelCase						=					MBartTokenizerFast
       UpperCamelCase						=					True
       UpperCamelCase						=					True



       def 					lowercase__    (							self      :  int   )			->						Union[str, Any]:


             '''simple docstring'''




             super().setUp()

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



       def 					lowercase__    (							self      :  Any   )			->						int:


             '''simple docstring'''




             UpperCAmelCase_      			=							MBartTokenizer(_UpperCAmelCase		,    keep_accents=_UpperCAmelCase   )

             UpperCAmelCase_      			=							tokenizer.tokenize("This is a test"   )
             self.assertListEqual(_UpperCAmelCase		,    ["▁This", "▁is", "▁a", "▁t", "est"]   )

             self.assertListEqual(
                 tokenizer.convert_tokens_to_ids(_UpperCAmelCase   )		,    [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(
                 _UpperCAmelCase		,    [
                     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(_UpperCAmelCase   )
             self.assertListEqual(
                 _UpperCAmelCase		,    [
                     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_      			=							tokenizer.convert_ids_to_tokens(_UpperCAmelCase   )
             self.assertListEqual(
                 _UpperCAmelCase		,    [
                     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[Any]   )			->						Dict:


             '''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_      			=							(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_      			=							self.rust_tokenizer_class.from_pretrained(_UpperCAmelCase		,    **_UpperCAmelCase   )
                         UpperCAmelCase_      			=							self.tokenizer_class.from_pretrained(_UpperCAmelCase		,    **_UpperCAmelCase   )

                         UpperCAmelCase_      			=							tempfile.mkdtemp()

                         UpperCAmelCase_      			=							tokenizer_r.save_pretrained(_UpperCAmelCase   )
                         UpperCAmelCase_      			=							tokenizer_p.save_pretrained(_UpperCAmelCase   )

                         # 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(_UpperCAmelCase		,    _UpperCAmelCase   )

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

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

                         shutil.rmtree(_UpperCAmelCase   )

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

                         UpperCAmelCase_      			=							tokenizer_r.save_pretrained(_UpperCAmelCase		,    legacy_format=_UpperCAmelCase   )
                         UpperCAmelCase_      			=							tokenizer_p.save_pretrained(_UpperCAmelCase   )

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

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

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

                         shutil.rmtree(_UpperCAmelCase   )

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

                         UpperCAmelCase_      			=							tokenizer_r.save_pretrained(_UpperCAmelCase		,    legacy_format=_UpperCAmelCase   )
                         UpperCAmelCase_      			=							tokenizer_p.save_pretrained(_UpperCAmelCase   )

                         # 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(_UpperCAmelCase   )
                         UpperCAmelCase_      			=							tokenizer_p.from_pretrained(_UpperCAmelCase   )

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

                         shutil.rmtree(_UpperCAmelCase   )



@require_torch
@require_sentencepiece
@require_tokenizers
class 				lowercase__       (   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						=					[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      :  Optional[Any]   )			->						List[Any]:


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  List[Any]   )			->						Union[str, Any]:


             '''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   )



       def 					lowercase__    (							self      :  Any   )			->						Tuple:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.tokenizer.batch_encode_plus(self.src_text   ).input_ids[0]
             self.assertListEqual(self.expected_src_tokens		,    _UpperCAmelCase   )



       def 					lowercase__    (							self      :  Any   )			->						str:


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  Tuple   )			->						Any:


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  int   )			->						int:


             '''simple docstring'''




             self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]   )		,    [250026, 250001]   )



       def 					lowercase__    (							self      :  Any   )			->						Any:


             '''simple docstring'''




             UpperCAmelCase_      			=							tempfile.mkdtemp()
             UpperCAmelCase_      			=							self.tokenizer.fairseq_tokens_to_ids
             self.tokenizer.save_pretrained(_UpperCAmelCase   )
             UpperCAmelCase_      			=							MBartTokenizer.from_pretrained(_UpperCAmelCase   )
             self.assertDictEqual(new_tok.fairseq_tokens_to_ids		,    _UpperCAmelCase   )



       @require_torch
       def 					lowercase__    (							self      :  List[Any]   )			->						int:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.tokenizer(self.src_text		,    text_target=self.tgt_text		,    padding=_UpperCAmelCase		,    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][-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      :  Any   )			->						Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.tokenizer(
                 self.src_text		,    text_target=self.tgt_text		,    padding=_UpperCAmelCase		,    truncation=_UpperCAmelCase		,    max_length=len(self.expected_src_tokens   )		,    return_tensors="pt"		,    )

             UpperCAmelCase_      			=							shift_tokens_right(batch["labels"]		,    self.tokenizer.pad_token_id   )

             self.assertIsInstance(_UpperCAmelCase		,    _UpperCAmelCase   )

             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		,    _UpperCAmelCase   )
             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      :  Union[str, Any]   )			->						Union[str, Any]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.tokenizer(self.src_text		,    padding=_UpperCAmelCase		,    truncation=_UpperCAmelCase		,    max_length=3		,    return_tensors="pt"   )
             UpperCAmelCase_      			=							self.tokenizer(
                 text_target=self.tgt_text		,    padding=_UpperCAmelCase		,    truncation=_UpperCAmelCase		,    max_length=10		,    return_tensors="pt"   )
             UpperCAmelCase_      			=							targets["input_ids"]
             UpperCAmelCase_      			=							shift_tokens_right(_UpperCAmelCase		,    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      :  Optional[int]   )			->						Any:


             '''simple docstring'''




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

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




