

'''simple docstring'''
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, 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


_snake_case         =  get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
    from transformers.models.plbart.modeling_plbart import shift_tokens_right

_snake_case         =  50_003
_snake_case         =  50_002


@require_sentencepiece
@require_tokenizers
class        a__  (							lowerCamelCase_  ,				unittest.TestCase  ):
   _SCREAMING_SNAKE_CASE   :					Optional[int]     	=							PLBartTokenizer
   _SCREAMING_SNAKE_CASE   :					Optional[int]     	=							None
   _SCREAMING_SNAKE_CASE   :					int     	=							False


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      super().setUp()

      # We have a SentencePiece fixture for testing
      _lowercase      :				Optional[Any]      					=       PLBartTokenizer(_UpperCamelCase      ,    language_codes="base"      ,    keep_accents=_UpperCamelCase  )
      tokenizer.save_pretrained(self.tmpdirname  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Any      					=       PLBartTokenizer(_UpperCamelCase      ,    language_codes="base"      ,    keep_accents=_UpperCamelCase  )

      _lowercase      :				int      					=       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]]      ,    )

      _lowercase      :				List[str]      					=       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",
              ".",
          ]      ,    )
      _lowercase      :				Dict      					=       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]
          ]      ,    )

      _lowercase      :				List[str]      					=       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>",
              ".",
          ]      ,    )

      _lowercase      :				int      					=       tokenizer.vocab_size
      _lowercase      :				int      					=       [tokenizer.convert_ids_to_tokens(_UpperCamelCase  ) for x in range(end - 4      ,    _UpperCamelCase  )]

      self.assertListEqual(_UpperCamelCase      ,    ["__java__", "__python__", "__en_XX__", "<mask>"]  )

      _lowercase      :				Optional[Any]      					=       "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
      _lowercase      :				Union[str, Any]      					=       tokenizer(_UpperCamelCase  ).input_ids
      self.assertEqual(
          tokenizer.decode(_UpperCamelCase      ,    skip_special_tokens=_UpperCamelCase      ,    clean_up_tokenization_spaces=_UpperCamelCase  )      ,    _UpperCamelCase      ,    )






   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				int      					=       PLBartTokenizer(_UpperCamelCase      ,    language_codes="multi"      ,    keep_accents=_UpperCamelCase  )

      _lowercase      :				List[Any]      					=       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]]      ,    )

      _lowercase      :				Tuple      					=       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",
              ".",
          ]      ,    )
      _lowercase      :				Any      					=       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]
          ]      ,    )

      _lowercase      :				Any      					=       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>",
              ".",
          ]      ,    )
      _lowercase      :				Any      					=       tokenizer.vocab_size
      _lowercase      :				List[str]      					=       [tokenizer.convert_ids_to_tokens(_UpperCamelCase  ) for x in range(end - 7      ,    _UpperCamelCase  )]

      self.assertListEqual(
          _UpperCamelCase      ,    ["__java__", "__python__", "__en_XX__", "__javascript__", "__php__", "__ruby__", "__go__"]  )
      _lowercase      :				List[Any]      					=       "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
      _lowercase      :				Optional[Any]      					=       tokenizer(_UpperCamelCase  ).input_ids
      self.assertEqual(
          tokenizer.decode(_UpperCamelCase      ,    skip_special_tokens=_UpperCamelCase      ,    clean_up_tokenization_spaces=_UpperCamelCase  )      ,    _UpperCamelCase      ,    )




@require_torch
@require_sentencepiece
@require_tokenizers
class        a__  (							unittest.TestCase  ):
   _SCREAMING_SNAKE_CASE   :					List[str]     	=							'uclanlp/plbart-python-en_XX'
   _SCREAMING_SNAKE_CASE   :					Optional[Any]     	=							[
       'def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])',
       'def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])',
   ]
   _SCREAMING_SNAKE_CASE   :					Dict     	=							[
       'Returns the maximum value of a b c.',
       'Sums the values of a b c.',
   ]
   _SCREAMING_SNAKE_CASE   :					Union[str, Any]     	=							[
       134,
       5452,
       3_3460,
       3_3441,
       3_3463,
       3_3465,
       3_3463,
       3_3449,
       988,
       20,
       3_3456,
       19,
       3_3456,
       771,
       39,
       4258,
       889,
       3318,
       3_3441,
       3_3463,
       3_3465,
       3_3463,
       3_3449,
       2471,
       2,
       PYTHON_CODE,
   ]


   @classmethod
   def 						_lowerCamelCase       (			cls  ):





      """simple docstring"""





      _lowercase      :				PLBartTokenizer      					=       PLBartTokenizer.from_pretrained(
          cls.checkpoint_name      ,    language_codes="base"      ,    src_lang="python"      ,    tgt_lang="en_XX"  )
      _lowercase      :				int      					=       1
      return cls


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__java__"]      ,    50001  )
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__python__"]      ,    50002  )
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__en_XX__"]      ,    50003  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				int      					=       self.tokenizer.batch_encode_plus(self.src_text  ).input_ids[0]
      self.assertListEqual(self.expected_src_tokens      ,    _UpperCamelCase  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      self.assertIn(_UpperCamelCase      ,    self.tokenizer.all_special_ids  )
      _lowercase      :				Tuple      					=       [EN_CODE, 9037, 33442, 57, 752, 153, 14, 56, 18, 9, 2]
      _lowercase      :				List[str]      					=       self.tokenizer.decode(_UpperCamelCase      ,    skip_special_tokens=_UpperCamelCase  )
      _lowercase      :				Optional[int]      					=       self.tokenizer.decode(generated_ids[1:]      ,    skip_special_tokens=_UpperCamelCase  )
      self.assertEqual(_UpperCamelCase      ,    _UpperCamelCase  )
      self.assertNotIn(self.tokenizer.eos_token      ,    _UpperCamelCase  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				str      					=       ["def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])" * 20]
      self.assertIsInstance(src_text[0]      ,    _UpperCamelCase  )
      _lowercase      :				List[Any]      					=       10
      _lowercase      :				List[str]      					=       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 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "__java__"]  )      ,    [50004, 50001]  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				int      					=       tempfile.mkdtemp()
      _lowercase      :				Tuple      					=       self.tokenizer.fairseq_tokens_to_ids
      self.tokenizer.save_pretrained(_UpperCamelCase  )
      _lowercase      :				int      					=       PLBartTokenizer.from_pretrained(_UpperCamelCase  )
      self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,    _UpperCamelCase  )


   @require_torch
   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				List[Any]      					=       self.tokenizer(self.src_text      ,    text_target=self.tgt_text      ,    padding=_UpperCamelCase      ,    return_tensors="pt"  )
      _lowercase      :				Optional[int]      					=       shift_tokens_right(batch["labels"]      ,    self.tokenizer.pad_token_id  )

      # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
      self.assertEqual(batch.input_ids[1][-2:].tolist()      ,    [2, PYTHON_CODE]  )
      self.assertEqual(batch.decoder_input_ids[1][0]      ,    _UpperCamelCase  )
      self.assertEqual(batch.decoder_input_ids[1][-1]      ,    2  )
      self.assertEqual(batch.labels[1][-2:].tolist()      ,    [2, EN_CODE]  )


   @require_torch
   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Any      					=       self.tokenizer(
          self.src_text      ,    text_target=self.tgt_text      ,    padding=_UpperCamelCase      ,    truncation=_UpperCamelCase      ,    max_length=len(self.expected_src_tokens  )      ,    return_tensors="pt"      ,    )
      _lowercase      :				Any      					=       shift_tokens_right(batch["labels"]      ,    self.tokenizer.pad_token_id  )

      self.assertIsInstance(_UpperCamelCase      ,    _UpperCamelCase  )

      self.assertEqual((2, 26)      ,    batch.input_ids.shape  )
      self.assertEqual((2, 26)      ,    batch.attention_mask.shape  )
      _lowercase      :				int      					=       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, PYTHON_CODE]  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





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





      """simple docstring"""





      _lowercase      :				Optional[Any]      					=       self.tokenizer._build_translation_inputs(
          "A test"      ,    return_tensors="pt"      ,    src_lang="en_XX"      ,    tgt_lang="java"  )

      self.assertEqual(
          nested_simplify(_UpperCamelCase  )      ,    {
              # A, test, EOS, en_XX
              "input_ids": [[150, 242, 2, 50003]],
              "attention_mask": [[1, 1, 1, 1]],
              # java
              "forced_bos_token_id": 50001,
          }      ,    )









'''simple docstring'''
import os
import re
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 logging


_snake_case         =  logging.get_logger(__name__)

_snake_case         =  {'vocab_file': 'spiece.model'}

_snake_case         =  {
    'vocab_file': {
        'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model',
        'google/bigbird-roberta-large': (
            'https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'
        ),
        'google/bigbird-base-trivia-itc': (
            'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'
        ),
    }
}

_snake_case         =  {
    'google/bigbird-roberta-base': 4_096,
    'google/bigbird-roberta-large': 4_096,
    'google/bigbird-base-trivia-itc': 4_096,
}


class        a__  (							lowerCamelCase_  ):
   _SCREAMING_SNAKE_CASE   :					List[Any]     	=							VOCAB_FILES_NAMES
   _SCREAMING_SNAKE_CASE   :					Any     	=							PRETRAINED_VOCAB_FILES_MAP
   _SCREAMING_SNAKE_CASE   :					Optional[Any]     	=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _SCREAMING_SNAKE_CASE   :					Optional[int]     	=							['input_ids', 'attention_mask']
   _SCREAMING_SNAKE_CASE   :					List[int]     	=							[]


   def __init__(			self      ,    _UpperCamelCase      ,    _UpperCamelCase="<unk>"      ,    _UpperCamelCase="<s>"      ,    _UpperCamelCase="</s>"      ,    _UpperCamelCase="<pad>"      ,    _UpperCamelCase="[SEP]"      ,    _UpperCamelCase="[MASK]"      ,    _UpperCamelCase="[CLS]"      ,    _UpperCamelCase = None      ,    **_UpperCamelCase      ,    ):





      """simple docstring"""





      _lowercase      :				Optional[int]      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else bos_token
      _lowercase      :				Optional[int]      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else eos_token
      _lowercase      :				Optional[Any]      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else unk_token
      _lowercase      :				Union[str, Any]      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else pad_token
      _lowercase      :				Any      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else cls_token
      _lowercase      :				str      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else sep_token

      # Mask token behave like a normal word, i.e. include the space before it
      _lowercase      :				Any      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else mask_token

      _lowercase      :				Dict      					=       {} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=_UpperCamelCase      ,    eos_token=_UpperCamelCase      ,    unk_token=_UpperCamelCase      ,    pad_token=_UpperCamelCase      ,    sep_token=_UpperCamelCase      ,    mask_token=_UpperCamelCase      ,    cls_token=_UpperCamelCase      ,    sp_model_kwargs=self.sp_model_kwargs      ,    **_UpperCamelCase      ,    )

      _lowercase      :				str      					=       vocab_file

      _lowercase      :				List[Any]      					=       spm.SentencePieceProcessor(**self.sp_model_kwargs  )
      self.sp_model.Load(_UpperCamelCase  )


   @property
   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      return self.sp_model.get_piece_size()


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Dict      					=       {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  ):





      """simple docstring"""





      _lowercase      :				str      					=       self.__dict__.copy()
      _lowercase      :				Union[str, Any]      					=       None
      return state


   def __setstate__(			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				Dict      					=       d

      # for backward compatibility
      if not hasattr(self      ,    "sp_model_kwargs"  ):
         _lowercase      :				Optional[Any]      					=       {}

      _lowercase      :				Optional[Any]      					=       spm.SentencePieceProcessor(**self.sp_model_kwargs  )
      self.sp_model.Load(self.vocab_file  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      return self.sp_model.encode(_UpperCamelCase      ,    out_type=_UpperCamelCase  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      return self.sp_model.piece_to_id(_UpperCamelCase  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				List[Any]      					=       self.sp_model.IdToPiece(_UpperCamelCase  )
      return token


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				Optional[int]      					=       []
      _lowercase      :				int      					=       ""
      _lowercase      :				Tuple      					=       False
      for token in tokens:
         # make sure that special tokens are not decoded using sentencepiece model
         if token in self.all_special_tokens:
            if not prev_is_special:
               out_string += " "
            out_string += self.sp_model.decode(_UpperCamelCase  ) + token
            _lowercase      :				Union[str, Any]      					=       True
            _lowercase      :				Optional[int]      					=       []
         else:
            current_sub_tokens.append(_UpperCamelCase  )
            _lowercase      :				str      					=       False
      out_string += self.sp_model.decode(_UpperCamelCase  )
      return out_string.strip()


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = False      ,    _UpperCamelCase = None      ,    _UpperCamelCase = True      ,    **_UpperCamelCase      ,    ):





      """simple docstring"""





      _lowercase      :				Any      					=       kwargs.pop("use_source_tokenizer"      ,    _UpperCamelCase  )

      _lowercase      :				Dict      					=       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
      _lowercase      :				Dict      					=       []
      _lowercase      :				Any      					=       []
      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  )  )
               _lowercase      :				Optional[Any]      					=       []
            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:
      # No space before [MASK] and [SEP]
      if spaces_between_special_tokens:
         _lowercase      :				List[str]      					=       re.sub(R" (\[(MASK|SEP)\])"      ,    R"\1"      ,    " ".join(_UpperCamelCase  )  )
      else:
         _lowercase      :				List[Any]      					=       "".join(_UpperCamelCase  )

      _lowercase      :				Optional[int]      					=       (
          clean_up_tokenization_spaces
          if clean_up_tokenization_spaces is not None
          else self.clean_up_tokenization_spaces
      )
      if clean_up_tokenization_spaces:
         _lowercase      :				Tuple      					=       self.clean_up_tokenization(_UpperCamelCase  )
         return clean_text
      else:
         return text


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None  ):





      """simple docstring"""





      if not os.path.isdir(_UpperCamelCase  ):
         logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
         return
      _lowercase      :				Optional[Any]      					=       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:
            _lowercase      :				List[str]      					=       self.sp_model.serialized_model_proto()
            fi.write(_UpperCamelCase  )

      return (out_vocab_file,)


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None  ):





      """simple docstring"""





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


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None      ,    _UpperCamelCase = False  ):





      """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 None:
         return [1] + ([0] * len(_UpperCamelCase  )) + [1]
      return [1] + ([0] * len(_UpperCamelCase  )) + [1] + ([0] * len(_UpperCamelCase  )) + [1]






   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None  ):





      """simple docstring"""





      _lowercase      :				str      					=       [self.sep_token_id]
      _lowercase      :				Union[str, Any]      					=       [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]






