






'''simple docstring'''
import gc
import unittest

from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device

from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
 import torch

 from transformers import (
     CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
     CTRLForSequenceClassification,
     CTRLLMHeadModel,
     CTRLModel,
 )


class 							_UpperCAmelCase    :




    def __init__(      self	:							Any	,  a	:							Any	,  a	:							List[Any]=1_4	,  a	:							Union[str, Any]=7	,  a	:							Dict=True	,  a	:							Optional[int]=True	,  a	:							int=True	,  a	:							Optional[Any]=True	,  a	:							Any=True	,  a	:							List[str]=9_9	,  a	:							List[Any]=3_2	,  a	:							List[str]=5	,  a	:							Tuple=4	,  a	:							Dict=3_7	,  a	:							List[Any]="gelu"	,  a	:							Optional[Any]=0.1	,  a	:							int=0.1	,  a	:							Dict=5_1_2	,  a	:							str=1_6	,  a	:							Union[str, Any]=2	,  a	:							Union[str, Any]=0.02	,  a	:							Optional[int]=3	,  a	:							Tuple=4	,  a	:							str=None	,  ):






       '''simple docstring'''






       lowercase_						:     List[Any]							     =  parent
       lowercase_						:     int							     =  batch_size
       lowercase_						:     Tuple							     =  seq_length
       lowercase_						:     Optional[Any]							     =  is_training
       lowercase_						:     int							     =  use_token_type_ids
       lowercase_						:     Dict							     =  use_input_mask
       lowercase_						:     Optional[int]							     =  use_labels
       lowercase_						:     Optional[Any]							     =  use_mc_token_ids
       lowercase_						:     Any							     =  vocab_size
       lowercase_						:     Union[str, Any]							     =  hidden_size
       lowercase_						:     Union[str, Any]							     =  num_hidden_layers
       lowercase_						:     Any							     =  num_attention_heads
       lowercase_						:     Optional[int]							     =  intermediate_size
       lowercase_						:     Tuple							     =  hidden_act
       lowercase_						:     List[str]							     =  hidden_dropout_prob
       lowercase_						:     Optional[Any]							     =  attention_probs_dropout_prob
       lowercase_						:     Tuple							     =  max_position_embeddings
       lowercase_						:     Optional[int]							     =  type_vocab_size
       lowercase_						:     List[str]							     =  type_sequence_label_size
       lowercase_						:     str							     =  initializer_range
       lowercase_						:     List[Any]							     =  num_labels
       lowercase_						:     Union[str, Any]							     =  num_choices
       lowercase_						:     Union[str, Any]							     =  scope
       lowercase_						:     int							     =  self.vocab_size - 1




    def 					lowerCAmelCase__					(      self	:							List[str]      ):






       '''simple docstring'''






       lowercase_						:     List[Any]							     =  ids_tensor([self.batch_size, self.seq_length]	,  self.vocab_size      )

       lowercase_						:     Optional[Any]							     =  None
       if self.use_input_mask:
          lowercase_						:     Tuple							     =  random_attention_mask([self.batch_size, self.seq_length]      )

       lowercase_						:     Any							     =  None
       if self.use_token_type_ids:
          lowercase_						:     Tuple							     =  ids_tensor([self.batch_size, self.seq_length]	,  self.type_vocab_size      )

       lowercase_						:     int							     =  None
       if self.use_mc_token_ids:
          lowercase_						:     Optional[int]							     =  ids_tensor([self.batch_size, self.num_choices]	,  self.seq_length      )

       lowercase_						:     int							     =  None
       lowercase_						:     str							     =  None
       lowercase_						:     Dict							     =  None
       if self.use_labels:
          lowercase_						:     List[str]							     =  ids_tensor([self.batch_size]	,  self.type_sequence_label_size      )
          lowercase_						:     Tuple							     =  ids_tensor([self.batch_size, self.seq_length]	,  self.num_labels      )
          lowercase_						:     List[str]							     =  ids_tensor([self.batch_size]	,  self.num_choices      )

       lowercase_						:     List[Any]							     =  self.get_config()

       lowercase_						:     Optional[Any]							     =  ids_tensor([self.num_hidden_layers, self.num_attention_heads]	,  2      )

       return (
           config,
           input_ids,
           input_mask,
           head_mask,
           token_type_ids,
           mc_token_ids,
           sequence_labels,
           token_labels,
           choice_labels,
       )




    def 					lowerCAmelCase__					(      self	:							Optional[Any]      ):






       '''simple docstring'''






       return CTRLConfig(
           vocab_size=self.vocab_size	,  n_embd=self.hidden_size	,  n_layer=self.num_hidden_layers	,  n_head=self.num_attention_heads	,  n_positions=self.max_position_embeddings	,  pad_token_id=self.pad_token_id	,  )




    def 					lowerCAmelCase__					(      self	:							Union[str, Any]	,  a	:							Tuple	,  a	:							Optional[int]	,  a	:							Union[str, Any]	,  a	:							List[Any]	,  a	:							Optional[int]	,  *a	:							List[Any]      ):






       '''simple docstring'''






       lowercase_						:     List[str]							     =  CTRLModel(config=a      )
       model.to(a      )
       model.eval()

       model(a	,  token_type_ids=a	,  head_mask=a      )
       model(a	,  token_type_ids=a      )
       lowercase_						:     Tuple							     =  model(a      )
       self.parent.assertEqual(result.last_hidden_state.shape	,  (self.batch_size, self.seq_length, self.hidden_size)      )
       self.parent.assertEqual(len(result.past_key_values      )	,  config.n_layer      )




    def 					lowerCAmelCase__					(      self	:							Dict	,  a	:							Any	,  a	:							Any	,  a	:							List[Any]	,  a	:							List[str]	,  a	:							Union[str, Any]	,  *a	:							List[Any]      ):






       '''simple docstring'''






       lowercase_						:     Dict							     =  CTRLLMHeadModel(a      )
       model.to(a      )
       model.eval()

       lowercase_						:     List[Any]							     =  model(a	,  token_type_ids=a	,  labels=a      )
       self.parent.assertEqual(result.loss.shape	,  ()      )
       self.parent.assertEqual(result.logits.shape	,  (self.batch_size, self.seq_length, self.vocab_size)      )




    def 					lowerCAmelCase__					(      self	:							List[Any]      ):






       '''simple docstring'''






       lowercase_						:     Union[str, Any]							     =  self.prepare_config_and_inputs()

       (
           (
           lowercase_
       )     ,		(
           lowercase_
       )     ,		(
           lowercase_
       )     ,		(
           lowercase_
       )     ,		(
           lowercase_
       )     ,		(
           lowercase_
       )     ,		(
           lowercase_
       )     ,		(
           lowercase_
       )     ,		(
           lowercase_
       )     ,		
       )						:     int							     =  config_and_inputs

       lowercase_						:     Optional[int]							     =  {"input_ids": input_ids, "token_type_ids": token_type_ids, "head_mask": head_mask}

       return config, inputs_dict





    def 					lowerCAmelCase__					(      self	:							Optional[int]	,  a	:							Dict	,  a	:							Dict	,  a	:							Optional[int]	,  a	:							Any	,  *a	:							Optional[int]      ):






       '''simple docstring'''






       lowercase_						:     List[str]							     =  self.num_labels
       lowercase_						:     Union[str, Any]							     =  CTRLForSequenceClassification(a      )
       model.to(a      )
       model.eval()
       lowercase_						:     Tuple							     =  ids_tensor([self.batch_size]	,  self.type_sequence_label_size      )
       lowercase_						:     Union[str, Any]							     =  model(a	,  token_type_ids=a	,  labels=a      )
       self.parent.assertEqual(result.logits.shape	,  (self.batch_size, self.num_labels)      )


@require_torch
class 							_UpperCAmelCase    (		snake_case					,       snake_case					,       snake_case					,       unittest.TestCase      ):
    __lowerCamelCase: List[str]									=     (CTRLModel, CTRLLMHeadModel, CTRLForSequenceClassification) if is_torch_available() else ()
    __lowerCamelCase: int									=     (CTRLLMHeadModel,) if is_torch_available() else ()
    __lowerCamelCase: List[Any]									=     (
        {
            'feature-extraction': CTRLModel,
            'text-classification': CTRLForSequenceClassification,
            'text-generation': CTRLLMHeadModel,
            'zero-shot': CTRLForSequenceClassification,
        }
        if is_torch_available()
        else {}
    )
    __lowerCamelCase: Dict									=     True
    __lowerCamelCase: Union[str, Any]									=     False
    __lowerCamelCase: Union[str, Any]									=     False




    def 					lowerCAmelCase__					(      self	:							Union[str, Any]	,  a	:							str	,  a	:							str	,  a	:							Any	,  a	:							Union[str, Any]	,  a	:							List[str]      ):






       '''simple docstring'''






       if pipeline_test_casse_name == "ZeroShotClassificationPipelineTests":
          # Get `tokenizer does not have a padding token` error for both fast/slow tokenizers.
          # `CTRLConfig` was never used in pipeline tests, either because of a missing checkpoint or because a tiny
          # config could not be created.
          return True

       return False




    def 					lowerCAmelCase__					(      self	:							Dict      ):






       '''simple docstring'''






       lowercase_						:     List[str]							     =  CTRLModelTester(self      )
       lowercase_						:     Optional[Any]							     =  ConfigTester(self	,  config_class=a	,  n_embd=3_7      )




    def 					lowerCAmelCase__					(      self	:							Tuple      ):






       '''simple docstring'''






       super().tearDown()
       # clean-up as much as possible GPU memory occupied by PyTorch
       gc.collect()
       torch.cuda.empty_cache()




    def 					lowerCAmelCase__					(      self	:							Optional[int]      ):






       '''simple docstring'''






       self.config_tester.run_common_tests()




    def 					lowerCAmelCase__					(      self	:							List[str]      ):






       '''simple docstring'''






       lowercase_						:     Union[str, Any]							     =  self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_ctrl_model(*a      )




    def 					lowerCAmelCase__					(      self	:							Any      ):






       '''simple docstring'''






       lowercase_						:     Any							     =  self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_lm_head_model(*a      )




    @unittest.skip("Will be fixed soon by reducing the size of the model used for common tests."      )
    def 					lowerCAmelCase__					(      self	:							str      ):






       '''simple docstring'''






       pass




    @slow
    def 					lowerCAmelCase__					(      self	:							Tuple      ):






       '''simple docstring'''






       for model_name in CTRL_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
          lowercase_						:     Optional[int]							     =  CTRLModel.from_pretrained(a      )
          self.assertIsNotNone(a      )





    @unittest.skip("The model doesn't support left padding"      )  # and it's not used enough to be worth fixing :)
    def 					lowerCAmelCase__					(      self	:							Dict      ):






       '''simple docstring'''






       pass


@require_torch
class 							_UpperCAmelCase    (		unittest.TestCase      ):




    def 					lowerCAmelCase__					(      self	:							List[Any]      ):






       '''simple docstring'''






       super().tearDown()
       # clean-up as much as possible GPU memory occupied by PyTorch
       gc.collect()
       torch.cuda.empty_cache()





    @slow
    def 					lowerCAmelCase__					(      self	:							Optional[int]      ):






       '''simple docstring'''






       lowercase_						:     str							     =  CTRLLMHeadModel.from_pretrained("ctrl"      )
       model.to(a      )
       lowercase_						:     List[str]							     =  torch.tensor(
           [[1_1_8_5_9, 0, 1_6_1_1, 8]]	,  dtype=torch.long	,  device=a      )  # Legal the president is
       lowercase_						:     Tuple							     =  [
           1_1_8_5_9,
           0,
           1_6_1_1,
           8,
           5,
           1_5_0,
           2_6_4_4_9,
           2,
           1_9,
           3_4_8,
           4_6_9,
           3,
           2_5_9_5,
           4_8,
           2_0_7_4_0,
           2_4_6_5_3_3,
           2_4_6_5_3_3,
           1_9,
           3_0,
           5,
       ]  # Legal the president is a good guy and I don't want to lose my job. \n \n I have a

       lowercase_						:     Dict							     =  model.generate(a	,  do_sample=a      )
       self.assertListEqual(output_ids[0].tolist()	,  a      )












'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


UpperCamelCase__			=      logging.get_logger(__name__)


UpperCamelCase__			=      {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all BART models at https://huggingface.co/models?filter=bart
UpperCamelCase__			=      {
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
}

UpperCamelCase__			=      {
    'facebook/bart-base': 1024,
    'facebook/bart-large': 1024,
    'facebook/bart-large-mnli': 1024,
    'facebook/bart-large-cnn': 1024,
    'facebook/bart-large-xsum': 1024,
    'yjernite/bart_eli5': 1024,
}




@lru_cache()
def 		__SCREAMING_SNAKE_CASE       (	):


   """simple docstring"""




   lowercase_						:     List[Any]							     =  (
       list(range(ord("!"				)    ,		ord("~"				) + 1				)				) + list(range(ord("¡"				)    ,		ord("¬"				) + 1				)				) + list(range(ord("®"				)    ,		ord("ÿ"				) + 1				)				)
   )
   lowercase_						:     str							     =  bs[:]
   lowercase_						:     Dict							     =  0
   for b in range(2**8				):
      if b not in bs:
         bs.append(_UpperCamelCase				)
         cs.append(2**8 + n				)
         n += 1
   lowercase_						:     Optional[int]							     =  [chr(_UpperCamelCase				) for n in cs]
   return dict(zip(_UpperCamelCase    ,		_UpperCamelCase				)				)




def 		__SCREAMING_SNAKE_CASE       (	_UpperCamelCase				):


   """simple docstring"""




   lowercase_						:     Optional[int]							     =  set()
   lowercase_						:     Union[str, Any]							     =  word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)				)
      lowercase_						:     Dict							     =  char
   return pairs





class 							_UpperCAmelCase    (		snake_case      ):
    __lowerCamelCase: Dict									=     VOCAB_FILES_NAMES
    __lowerCamelCase: int									=     PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase: Dict									=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __lowerCamelCase: str									=     ['input_ids', 'attention_mask']




    def __init__(      self	:							Tuple	,  a	:							Tuple	,  a	:							Tuple	,  a	:							int="replace"	,  a	:							Optional[int]="<s>"	,  a	:							Tuple="</s>"	,  a	:							Tuple="</s>"	,  a	:							Tuple="<s>"	,  a	:							Optional[Any]="<unk>"	,  a	:							Dict="<pad>"	,  a	:							List[str]="<mask>"	,  a	:							Tuple=False	,  **a	:							Optional[int]	,  ):






       '''simple docstring'''






       lowercase_						:     List[Any]							     =  AddedToken(a	,  lstrip=a	,  rstrip=a      ) if isinstance(a	,  a      ) else bos_token
       lowercase_						:     str							     =  AddedToken(a	,  lstrip=a	,  rstrip=a      ) if isinstance(a	,  a      ) else eos_token
       lowercase_						:     str							     =  AddedToken(a	,  lstrip=a	,  rstrip=a      ) if isinstance(a	,  a      ) else sep_token
       lowercase_						:     Any							     =  AddedToken(a	,  lstrip=a	,  rstrip=a      ) if isinstance(a	,  a      ) else cls_token
       lowercase_						:     Dict							     =  AddedToken(a	,  lstrip=a	,  rstrip=a      ) if isinstance(a	,  a      ) else unk_token
       lowercase_						:     List[Any]							     =  AddedToken(a	,  lstrip=a	,  rstrip=a      ) if isinstance(a	,  a      ) else pad_token

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

       super().__init__(
           errors=a	,  bos_token=a	,  eos_token=a	,  unk_token=a	,  sep_token=a	,  cls_token=a	,  pad_token=a	,  mask_token=a	,  add_prefix_space=a	,  **a	,  )

       with open(a	,  encoding="utf-8"      ) as vocab_handle:
          lowercase_						:     Any							     =  json.load(a      )
       lowercase_						:     Union[str, Any]							     =  {v: k for k, v in self.encoder.items()}
       lowercase_						:     Dict							     =  errors  # how to handle errors in decoding
       lowercase_						:     Any							     =  bytes_to_unicode()
       lowercase_						:     List[Any]							     =  {v: k for k, v in self.byte_encoder.items()}
       with open(a	,  encoding="utf-8"      ) as merges_handle:
          lowercase_						:     Optional[Any]							     =  merges_handle.read().split("\n"      )[1:-1]
       lowercase_						:     Any							     =  [tuple(merge.split()      ) for merge in bpe_merges]
       lowercase_						:     List[str]							     =  dict(zip(a	,  range(len(a      )      )      )      )
       lowercase_						:     Optional[Any]							     =  {}
       lowercase_						:     Union[str, Any]							     =  add_prefix_space

       # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
       lowercase_						:     str							     =  re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"      )




    @property
    def 					lowerCAmelCase__					(      self	:							Tuple      ):






       '''simple docstring'''






       return len(self.encoder      )




    def 					lowerCAmelCase__					(      self	:							Dict      ):






       '''simple docstring'''






       return dict(self.encoder	,  **self.added_tokens_encoder      )




    def 					lowerCAmelCase__					(      self	:							Any	,  a	:							int      ):






       '''simple docstring'''






       if token in self.cache:
          return self.cache[token]
       lowercase_						:     Optional[Any]							     =  tuple(a      )
       lowercase_						:     Tuple							     =  get_pairs(a      )

       if not pairs:
          return token

       while True:
          lowercase_						:     Any							     =  min(a	,  key=lambda a      : self.bpe_ranks.get(a	,  float("inf"      )      )      )
          if bigram not in self.bpe_ranks:
             break
          lowercase_     ,		lowercase_						:     Dict							     =  bigram
          lowercase_						:     List[Any]							     =  []
          lowercase_						:     Optional[Any]							     =  0
          while i < len(a      ):
             try:
                lowercase_						:     Union[str, Any]							     =  word.index(a	,  a      )
             except ValueError:
                new_word.extend(word[i:]      )
                break
             else:
                new_word.extend(word[i:j]      )
                lowercase_						:     Any							     =  j

             if word[i] == first and i < len(a      ) - 1 and word[i + 1] == second:
                new_word.append(first + second      )
                i += 2
             else:
                new_word.append(word[i]      )
                i += 1
          lowercase_						:     Any							     =  tuple(a      )
          lowercase_						:     List[str]							     =  new_word
          if len(a      ) == 1:
             break
          else:
             lowercase_						:     Union[str, Any]							     =  get_pairs(a      )
       lowercase_						:     List[str]							     =  " ".join(a      )
       lowercase_						:     Optional[int]							     =  word
       return word




    def 					lowerCAmelCase__					(      self	:							Any	,  a	:							str      ):






       '''simple docstring'''






       lowercase_						:     Dict							     =  []
       for token in re.findall(self.pat	,  a      ):
          lowercase_						:     Tuple							     =  "".join(
              self.byte_encoder[b] for b in token.encode("utf-8"      )      )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
          bpe_tokens.extend(bpe_token for bpe_token in self.bpe(a      ).split(" "      )      )
       return bpe_tokens




    def 					lowerCAmelCase__					(      self	:							Tuple	,  a	:							Dict      ):






       '''simple docstring'''






       return self.encoder.get(a	,  self.encoder.get(self.unk_token      )      )




    def 					lowerCAmelCase__					(      self	:							Tuple	,  a	:							str      ):






       '''simple docstring'''






       return self.decoder.get(a      )




    def 					lowerCAmelCase__					(      self	:							int	,  a	:							Optional[Any]      ):






       '''simple docstring'''






       lowercase_						:     int							     =  "".join(a      )
       lowercase_						:     str							     =  bytearray([self.byte_decoder[c] for c in text]      ).decode("utf-8"	,  errors=self.errors      )
       return text




    def 					lowerCAmelCase__					(      self	:							List[str]	,  a	:							str	,  a	:							Optional[str] = None      ):






       '''simple docstring'''






       if not os.path.isdir(a      ):
          logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""      )
          return
       lowercase_						:     Any							     =  os.path.join(
           a	,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]      )
       lowercase_						:     Optional[int]							     =  os.path.join(
           a	,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]      )

       with open(a	,  "w"	,  encoding="utf-8"      ) as f:
          f.write(json.dumps(self.encoder	,  indent=2	,  sort_keys=a	,  ensure_ascii=a      ) + "\n"      )

       lowercase_						:     Dict							     =  0
       with open(a	,  "w"	,  encoding="utf-8"      ) as writer:
          writer.write("#version: 0.2\n"      )
          for bpe_tokens, token_index in sorted(self.bpe_ranks.items()	,  key=lambda a      : kv[1]      ):
             if index != token_index:
                logger.warning(
                    f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
                    " Please check that the tokenizer is not corrupted!"      )
                lowercase_						:     Optional[Any]							     =  token_index
             writer.write(" ".join(a      ) + "\n"      )
             index += 1

       return vocab_file, merge_file




    def 					lowerCAmelCase__					(      self	:							List[str]	,  a	:							List[int]	,  a	:							Optional[List[int]] = None      ):






       '''simple docstring'''






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




    def 					lowerCAmelCase__					(      self	:							int	,  a	:							List[int]	,  a	:							Optional[List[int]] = None	,  a	:							bool = False      ):






       '''simple docstring'''






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

       if token_ids_a is None:
          return [1] + ([0] * len(a      )) + [1]
       return [1] + ([0] * len(a      )) + [1, 1] + ([0] * len(a      )) + [1]




    def 					lowerCAmelCase__					(      self	:							Optional[int]	,  a	:							List[int]	,  a	:							Optional[List[int]] = None      ):






       '''simple docstring'''






       lowercase_						:     Union[str, Any]							     =  [self.sep_token_id]
       lowercase_						:     List[str]							     =  [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 + sep + token_ids_a + sep      ) * [0]





    def 					lowerCAmelCase__					(      self	:							str	,  a	:							Any	,  a	:							int=False	,  **a	:							List[Any]      ):






       '''simple docstring'''






       lowercase_						:     Any							     =  kwargs.pop("add_prefix_space"	,  self.add_prefix_space      )
       if (is_split_into_words or add_prefix_space) and (len(a      ) > 0 and not text[0].isspace()):
          lowercase_						:     str							     =  " " + text
       return (text, kwargs)




