




import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
		from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
		__lowerCAmelCase	:       Union[str, Any]     =	get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
		from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

__lowerCAmelCase	:       List[str]     =	12_8022
__lowerCAmelCase	:       Tuple     =	12_8028




@require_sentencepiece
class 					snake_case__							(_UpperCamelCase					, unittest.TestCase     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							List[str]											=      MaMaaaTokenizer
				SCREAMING_SNAKE_CASE_ :							Tuple											=      False
				SCREAMING_SNAKE_CASE_ :							str											=      False
				SCREAMING_SNAKE_CASE_ :							str											=      True





				def 							__UpperCAmelCase							(   self       :  List[Any]							)      ->  Optional[int]:
							super().setUp()

							a					=    ["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
							a					=    dict(zip(__lowerCamelCase      ,   range(len(__lowerCamelCase							)							)							)							)
							a					=    Path(self.tmpdirname							)
							save_json(__lowerCamelCase      ,   save_dir / VOCAB_FILES_NAMES["vocab_file"]							)
							if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
										copyfile(__lowerCamelCase      ,   save_dir / VOCAB_FILES_NAMES["spm_file"]							)

							a					=    MaMaaaTokenizer.from_pretrained(self.tmpdirname							)
							tokenizer.save_pretrained(self.tmpdirname							)





				def 							__UpperCAmelCase							(   self       :  str      ,   **__lowerCamelCase       :  int							)      ->  int:
							return MaMaaaTokenizer.from_pretrained(self.tmpdirname      ,   **__lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  List[Any]      ,   __lowerCamelCase       :  Optional[Any]							)      ->  str:
							return (
							    "This is a test",
							    "This is a test",
							)





				def 							__UpperCAmelCase							(   self       :  Optional[Any]							)      ->  str:
							a					=    "</s>"
							a					=    0

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowerCamelCase							)      ,   __lowerCamelCase							)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowerCamelCase							)      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  Any							)      ->  Any:
							a					=    self.get_tokenizer()
							a					=    list(tokenizer.get_vocab().keys()							)

							self.assertEqual(vocab_keys[0]      ,   "</s>"							)
							self.assertEqual(vocab_keys[1]      ,   "<unk>"							)
							self.assertEqual(vocab_keys[-1]      ,   "<s>"							)
							self.assertEqual(len(__lowerCamelCase							)      ,   tokenizer.vocab_size + len(tokenizer.get_added_vocab()							)							)





				@unittest.skip("Skip this test while all models are still to be uploaded."							)
				def 							__UpperCAmelCase							(   self       :  Optional[int]							)      ->  Optional[Any]:
							pass





				def 							__UpperCAmelCase							(   self       :  int							)      ->  Tuple:
							a					=    self.get_tokenizer()

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

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(__lowerCamelCase							)      ,   [2, 3, 4, 5, 6]      ,   )

							a					=    tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]							)
							self.assertListEqual(__lowerCamelCase      ,   ["▁This", "▁is", "▁a", "▁t", "est"]							)

							a					=    tokenizer.convert_tokens_to_string(__lowerCamelCase							)
							self.assertEqual(__lowerCamelCase      ,   "This is a test"							)





				@slow
				def 							__UpperCAmelCase							(   self       :  List[Any]							)      ->  List[Any]:
							# fmt: off
							a					=    {"input_ids": [[12_80_22, 11_01_08, 3_97, 11, 3_82_72, 22_47, 12_48_11, 2_85, 1_81_05, 15_86, 2_07, 7, 3_95_34, 44_28, 3_97, 10_19, 1_81_05, 15_86, 2_07, 7, 4_13_37, 1_67_86, 2_41, 7, 2_02_14, 17, 12_56_90, 1_03_98, 7, 4_43_78, 5_80_69, 6_83_42, 77_98, 73_43, 11, 2_99, 3_33_10, 4, 1_58, 3_73_50, 9_40_77, 45_69, 2_99, 3_33_10, 90, 4, 5_28_40, 2_90, 4, 3_12_70, 1_12, 2_99, 6_82, 4, 5_28_40, 3_99_53, 1_40_79, 1_93, 5_25_19, 9_08_94, 1_78_94, 12_06_97, 11, 4_04_45, 5_51, 17, 10_19, 5_25_19, 9_08_94, 1_77_56, 9_63, 11, 4_04_45, 4_80, 17, 97_92, 11_20, 51_73, 13_93, 62_40, 1_67_86, 2_41, 12_09_96, 28, 12_45, 13_93, 11_82_40, 1_11_23, 10_19, 9_36_12, 26_91, 1_06_18, 9_80_58, 12_04_09, 19_28, 2_79, 4, 4_06_83, 3_67, 1_78, 2_07, 10_19, 1_03, 10_31_21, 5_06, 6_52_96, 5, 2], [12_80_22, 2_12_17, 3_67, 1_17, 12_54_50, 1_28, 7_19, 7, 73_08, 40, 9_36_12, 1_26_69, 11_16, 1_67_04, 71, 1_77_85, 36_99, 1_55_92, 35, 1_44, 95_84, 2_41, 1_19_43, 7_13, 9_50, 7_99, 22_47, 8_84_27, 1_50, 1_49, 11_88_13, 12_07_06, 10_19, 10_69_06, 8_15_18, 28, 12_24, 2_27_99, 3_97, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [12_80_22, 16_58, 12_33_11, 51_55, 55_78, 47_22, 2_79, 1_49_47, 23_66, 11_20, 11_97, 14, 13_48, 92_32, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=__lowerCamelCase      ,   model_name="facebook/m2m100_418M"      ,   revision="c168bae485c864188cf9aa0e4108b0b6934dc91e"      ,   )




@require_torch
@require_sentencepiece
@require_tokenizers
class 					snake_case__							(unittest.TestCase     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							Dict											=      """facebook/m2m100_418M"""
				SCREAMING_SNAKE_CASE_ :							List[str]											=      [
				    """In my opinion, there are two levels of response from the French government.""",
				    """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
				]
				SCREAMING_SNAKE_CASE_ :							Union[str, Any]											=      [
				    """Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.""",
				    """L'affaire NSA souligne l'absence totale de débat sur le renseignement""",
				]

				# fmt: off
				SCREAMING_SNAKE_CASE_ :							Tuple											=      [EN_CODE, 5_93, 19_49, 11_57_81, 4, 7_15_86, 42_34, 6_06_33, 12_62_33, 4_32, 12_38_08, 1_55_92, 11_97, 11_71_32, 12_06_18, 5, 2]





				@classmethod
				def 							__UpperCAmelCase							(   cls       :  int							)      ->  Any:
							a					=    MaMaaaTokenizer.from_pretrained(
							    cls.checkpoint_name      ,   src_lang="en"      ,   tgt_lang="fr"							)
							a					=    1
							return cls





				def 							__UpperCAmelCase							(   self       :  Any							)      ->  str:
							self.assertEqual(self.tokenizer.get_lang_id("ar"							)      ,   12_80_06							)
							self.assertEqual(self.tokenizer.get_lang_id("en"							)      ,   12_80_22							)
							self.assertEqual(self.tokenizer.get_lang_id("ro"							)      ,   12_80_76							)
							self.assertEqual(self.tokenizer.get_lang_id("mr"							)      ,   12_80_63							)





				def 							__UpperCAmelCase							(   self       :  Any							)      ->  List[Any]:
							a					=    self.tokenizer.get_vocab()
							self.assertEqual(len(__lowerCamelCase							)      ,   self.tokenizer.vocab_size							)
							self.assertEqual(vocab["<unk>"]      ,   3							)
							self.assertIn(self.tokenizer.get_lang_token("en"							)      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  Dict							)      ->  Union[str, Any]:
							a					=    "en"
							a					=    self.tokenizer.batch_encode_plus(self.src_text							).input_ids[0]
							self.assertListEqual(self.expected_src_tokens      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  Union[str, Any]							)      ->  Optional[int]:
							self.assertIn(__lowerCamelCase      ,   self.tokenizer.all_special_ids							)
							# fmt: off
							a					=    [FR_CODE, 53_64, 82, 86_42, 4, 2_94, 47, 8, 1_40_28, 1_36, 32_86, 97_06, 6, 9_07_97, 6, 14_40_12, 1_62, 8_81_28, 3_00_61, 5, 2]
							# fmt: on
							a					=    self.tokenizer.decode(__lowerCamelCase      ,   skip_special_tokens=__lowerCamelCase							)
							a					=    self.tokenizer.decode(generated_ids[1:]      ,   skip_special_tokens=__lowerCamelCase							)
							self.assertEqual(__lowerCamelCase      ,   __lowerCamelCase							)
							self.assertNotIn(self.tokenizer.eos_token      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  Dict							)      ->  Union[str, Any]:
							a					=    tempfile.mkdtemp()
							a					=    self.tokenizer.lang_token_to_id
							self.tokenizer.save_pretrained(__lowerCamelCase							)
							a					=    MaMaaaTokenizer.from_pretrained(__lowerCamelCase							)
							self.assertDictEqual(new_tok.lang_token_to_id      ,   __lowerCamelCase							)





				@require_torch
				def 							__UpperCAmelCase							(   self       :  int							)      ->  List[str]:
							a					=    "en"
							a					=    "fr"

							a					=    self.tokenizer(self.src_text      ,   text_target=self.tgt_text      ,   padding=__lowerCamelCase      ,   return_tensors="pt"							)

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

							for k in batch:
										a					=    batch[k].tolist()
							# batch = {k: v.tolist() for k,v in batch.items()}
							# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
							# batch.decoder_inputs_ids[0][0] ==
							assert batch.input_ids[1][0] == EN_CODE
							assert batch.input_ids[1][-1] == 2
							assert batch.labels[1][0] == FR_CODE
							assert batch.labels[1][-1] == 2
							assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]





				@require_torch
				def 							__UpperCAmelCase							(   self       :  int							)      ->  Optional[Any]:
							a					=    "mr"
							self.assertListEqual(self.tokenizer.prefix_tokens      ,   [self.tokenizer.get_lang_id("mr"							)]							)
							self.assertListEqual(self.tokenizer.suffix_tokens      ,   [self.tokenizer.eos_token_id]							)

							a					=    "zh"
							self.assertListEqual(self.tokenizer.prefix_tokens      ,   [self.tokenizer.get_lang_id("zh"							)]							)
							self.assertListEqual(self.tokenizer.suffix_tokens      ,   [self.tokenizer.eos_token_id]							)





				@require_torch
				def 							__UpperCAmelCase							(   self       :  Optional[int]							)      ->  Optional[int]:
							a					=    "mr"
							self.tokenizer._switch_to_target_mode()
							self.assertListEqual(self.tokenizer.prefix_tokens      ,   [self.tokenizer.get_lang_id("mr"							)]							)
							self.assertListEqual(self.tokenizer.suffix_tokens      ,   [self.tokenizer.eos_token_id]							)
							self.tokenizer._switch_to_input_mode()
							self.assertListEqual(self.tokenizer.prefix_tokens      ,   [self.tokenizer.get_lang_id(self.tokenizer.src_lang							)]							)

							a					=    "zh"
							self.tokenizer._switch_to_target_mode()
							self.assertListEqual(self.tokenizer.prefix_tokens      ,   [self.tokenizer.get_lang_id("zh"							)]							)
							self.assertListEqual(self.tokenizer.suffix_tokens      ,   [self.tokenizer.eos_token_id]							)
							self.tokenizer._switch_to_input_mode()
							self.assertListEqual(self.tokenizer.prefix_tokens      ,   [self.tokenizer.get_lang_id(self.tokenizer.src_lang							)]							)





				@require_torch
				def 							__UpperCAmelCase							(   self       :  Union[str, Any]							)      ->  Tuple:
							a					=    self.tokenizer._build_translation_inputs("A test"      ,   return_tensors="pt"      ,   src_lang="en"      ,   tgt_lang="ar"							)

							self.assertEqual(
							    nested_simplify(__lowerCamelCase							)      ,   {
							        # en_XX, A, test, EOS
							        "input_ids": [[12_80_22, 58, 41_83, 2]],
							        "attention_mask": [[1, 1, 1, 1]],
							        # ar_AR
							        "forced_bos_token_id": 12_80_06,
							    }      ,   )












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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_big_bird import BigBirdTokenizer
else:
		__lowerCAmelCase	:       Optional[int]     =	None

__lowerCAmelCase	:       Optional[Any]     =	logging.get_logger(__name__)
__lowerCAmelCase	:       Optional[int]     =	{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

__lowerCAmelCase	:       List[Any]     =	{
    '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'
        ),
    },
    'tokenizer_file': {
        'google/bigbird-roberta-base': (
            'https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json'
        ),
        'google/bigbird-roberta-large': (
            'https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json'
        ),
        'google/bigbird-base-trivia-itc': (
            'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json'
        ),
    },
}

__lowerCAmelCase	:       List[str]     =	{
    'google/bigbird-roberta-base': 4096,
    'google/bigbird-roberta-large': 4096,
    'google/bigbird-base-trivia-itc': 4096,
}


__lowerCAmelCase	:       Any     =	'▁'




class 					snake_case__							(_UpperCamelCase     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							Any											=      VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_ :							List[Any]											=      PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_ :							Dict											=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_ :							str											=      BigBirdTokenizer
				SCREAMING_SNAKE_CASE_ :							str											=      ["""input_ids""", """attention_mask"""]
				SCREAMING_SNAKE_CASE_ :							List[int]											=      []





				def __init__(   self       :  int      ,   __lowerCamelCase       :  Any=None      ,   __lowerCamelCase       :  List[str]=None      ,   __lowerCamelCase       :  Optional[int]="<unk>"      ,   __lowerCamelCase       :  int="<s>"      ,   __lowerCamelCase       :  Optional[Any]="</s>"      ,   __lowerCamelCase       :  Tuple="<pad>"      ,   __lowerCamelCase       :  Tuple="[SEP]"      ,   __lowerCamelCase       :  Dict="[MASK]"      ,   __lowerCamelCase       :  Tuple="[CLS]"      ,   **__lowerCamelCase       :  Optional[Any]      ,   )      ->  List[Any]:
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else bos_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else eos_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else unk_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else pad_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else cls_token
							a					=    AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase							) if isinstance(__lowerCamelCase      ,   __lowerCamelCase							) else sep_token

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

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

							a					=    vocab_file
							a					=    False if not self.vocab_file else True





				def 							__UpperCAmelCase							(   self       :  str      ,   __lowerCamelCase       :  List[int]      ,   __lowerCamelCase       :  Optional[List[int]] = None							)      ->  List[int]:
							a					=    [self.sep_token_id]
							a					=    [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							)      ->  List[int]:

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





				def 							__UpperCAmelCase							(   self       :  Optional[int]      ,   __lowerCamelCase       :  List[int]      ,   __lowerCamelCase       :  Optional[List[int]] = None							)      ->  List[int]:
							a					=    [self.sep_token_id]
							a					=    [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       :  Tuple      ,   __lowerCamelCase       :  str      ,   __lowerCamelCase       :  Optional[str] = None							)      ->  Tuple[str]:
							if not self.can_save_slow_tokenizer:
										raise ValueError(
										    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
										    "tokenizer."							)

							if not os.path.isdir(__lowerCamelCase							):
										logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
										return
							a					=    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,)






