

import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


_lowerCamelCase						    =  logging.get_logger(__name__)

_lowerCamelCase						    =  {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

_lowerCamelCase						    =  {
    """vocab_file""": {
        """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt""",
        """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt""",
        """junnyu/roformer_chinese_char_small""": (
            """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_chinese_char_base""": (
            """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_small_discriminator""": (
            """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_small_generator""": (
            """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt"""
        ),
    }
}

_lowerCamelCase						    =  {
    """junnyu/roformer_chinese_small""": 1536,
    """junnyu/roformer_chinese_base""": 1536,
    """junnyu/roformer_chinese_char_small""": 512,
    """junnyu/roformer_chinese_char_base""": 512,
    """junnyu/roformer_small_discriminator""": 128,
    """junnyu/roformer_small_generator""": 128,
}


_lowerCamelCase						    =  {
    """junnyu/roformer_chinese_small""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_base""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_char_small""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_char_base""": {"""do_lower_case""": True},
    """junnyu/roformer_small_discriminator""": {"""do_lower_case""": True},
    """junnyu/roformer_small_generator""": {"""do_lower_case""": True},
}

class       _SCREAMING_SNAKE_CASE	(UpperCamelCase ):
     lowerCAmelCase					=			VOCAB_FILES_NAMES
     lowerCAmelCase					=			PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase					=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase					=			PRETRAINED_INIT_CONFIGURATION
     lowerCAmelCase					=			RoFormerTokenizer





     def __init__(       self :							Tuple     ,  UpperCamelCase :							int=None     ,  UpperCamelCase :							str=None     ,  UpperCamelCase :							Optional[int]=True     ,  UpperCamelCase :							Optional[Any]="[UNK]"     ,  UpperCamelCase :							Dict="[SEP]"     ,  UpperCamelCase :							Optional[int]="[PAD]"     ,  UpperCamelCase :							int="[CLS]"     ,  UpperCamelCase :							Optional[Any]="[MASK]"     ,  UpperCamelCase :							Any=True     ,  UpperCamelCase :							Optional[int]=None     ,  **UpperCamelCase :							Optional[int]     ,  )->str:
      super().__init__(
          UpperCamelCase     ,  tokenizer_file=UpperCamelCase     ,  do_lower_case=UpperCamelCase     ,  unk_token=UpperCamelCase     ,  sep_token=UpperCamelCase     ,  pad_token=UpperCamelCase     ,  cls_token=UpperCamelCase     ,  mask_token=UpperCamelCase     ,  tokenize_chinese_chars=UpperCamelCase     ,  strip_accents=UpperCamelCase     ,  **UpperCamelCase     ,  )

      __SCREAMING_SNAKE_CASE       :    int       =	json.loads(self.backend_tokenizer.normalizer.__getstate__()				)
      if (
          pre_tok_state.get("lowercase"     ,  UpperCamelCase				) != do_lower_case
          or pre_tok_state.get("strip_accents"     ,  UpperCamelCase				) != strip_accents
      ):
       __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	getattr(UpperCamelCase     ,  pre_tok_state.pop("type"				)				)
       __SCREAMING_SNAKE_CASE       :    List[str]       =	do_lower_case
       __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	strip_accents
       __SCREAMING_SNAKE_CASE       :    int       =	pre_tok_class(**UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    Dict       =	do_lower_case





     def __getstate__(       self :							Any				)->Union[str, Any]:
      __SCREAMING_SNAKE_CASE       :    Tuple       =	self.__dict__.copy()
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	BertPreTokenizer()
      return state





     def __setstate__(       self :							Tuple     ,  UpperCamelCase :							Union[str, Any]				)->str:
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	d
      __SCREAMING_SNAKE_CASE       :    List[str]       =	self.__dict__["_tokenizer"].get_vocab()
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	PreTokenizer.custom(JiebaPreTokenizer(UpperCamelCase				)				)





     def 	__snake_case    (       self :							List[str]     ,  UpperCamelCase :							Optional[Any]     ,  UpperCamelCase :							Dict=None				)->str:
      __SCREAMING_SNAKE_CASE       :    Tuple       =	[self.cls_token_id] + token_ids_a + [self.sep_token_id]

      if token_ids_a:
       output += token_ids_a + [self.sep_token_id]

      return output





     def 	__snake_case    (       self :							List[Any]     ,  UpperCamelCase :							List[int]     ,  UpperCamelCase :							Optional[List[int]] = None				)->List[int]:
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	[self.sep_token_id]
      __SCREAMING_SNAKE_CASE       :    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				) * [0] + len(token_ids_a + sep				) * [1]





     def 	__snake_case    (       self :							int     ,  UpperCamelCase :							str     ,  UpperCamelCase :							Optional[str] = None				)->Tuple[str]:
      __SCREAMING_SNAKE_CASE       :    str       =	self._tokenizer.model.save(UpperCamelCase     ,  name=UpperCamelCase				)
      return tuple(UpperCamelCase				)






     def 	__snake_case    (       self :							Optional[int]     ,  UpperCamelCase :							Tuple     ,  UpperCamelCase :							List[str]=None     ,  UpperCamelCase :							Optional[int]=None     ,  UpperCamelCase :							int=False     ,  **UpperCamelCase :							List[str]     ,  )->List[Any]:
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	BertPreTokenizer()
      return super().save_pretrained(UpperCamelCase     ,  UpperCamelCase     ,  UpperCamelCase     ,  UpperCamelCase     ,  **UpperCamelCase				)











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


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

_lowerCamelCase						    =  128022
_lowerCamelCase						    =  128028

@require_sentencepiece
class       _SCREAMING_SNAKE_CASE	(UpperCamelCase			,    unittest.TestCase ):
     lowerCAmelCase					=			MaMaaaTokenizer
     lowerCAmelCase					=			False
     lowerCAmelCase					=			False
     lowerCAmelCase					=			True





     def 	__snake_case    (       self :							Union[str, Any]				)->Optional[Any]:
      super().setUp()

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

      __SCREAMING_SNAKE_CASE       :    Any       =	MaMaaaTokenizer.from_pretrained(self.tmpdirname				)
      tokenizer.save_pretrained(self.tmpdirname				)





     def 	__snake_case    (       self :							Optional[int]     ,  **UpperCamelCase :							Any				)->Dict:
      return MaMaaaTokenizer.from_pretrained(self.tmpdirname     ,  **UpperCamelCase				)





     def 	__snake_case    (       self :							Dict     ,  UpperCamelCase :							List[str]				)->int:
      return (
          "This is a test",
          "This is a test",
      )





     def 	__snake_case    (       self :							str				)->Tuple:
      __SCREAMING_SNAKE_CASE       :    List[Any]       =	"</s>"
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	0

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





     def 	__snake_case    (       self :							Tuple				)->Optional[Any]:
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	self.get_tokenizer()
      __SCREAMING_SNAKE_CASE       :    Any       =	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(UpperCamelCase				)     ,  tokenizer.vocab_size + len(tokenizer.get_added_vocab()				)				)





     @unittest.skip("Skip this test while all models are still to be uploaded."				)
     def 	__snake_case    (       self :							Dict				)->Dict:
      pass





     def 	__snake_case    (       self :							Union[str, Any]				)->Union[str, Any]:
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	self.get_tokenizer()

      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	tokenizer.tokenize("This is a test"				)
      self.assertListEqual(UpperCamelCase     ,  ["▁This", "▁is", "▁a", "▁t", "est"]				)

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

      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]				)
      self.assertListEqual(UpperCamelCase     ,  ["▁This", "▁is", "▁a", "▁t", "est"]				)

      __SCREAMING_SNAKE_CASE       :    Any       =	tokenizer.convert_tokens_to_string(UpperCamelCase				)
      self.assertEqual(UpperCamelCase     ,  "This is a test"				)






     @slow
     def 	__snake_case    (       self :							Any				)->Union[str, Any]:
      # fmt: off
      __SCREAMING_SNAKE_CASE       :    Tuple       =	{"input_ids": [[1_2_8_0_2_2, 1_1_0_1_0_8, 3_9_7, 1_1, 3_8_2_7_2, 2_2_4_7, 1_2_4_8_1_1, 2_8_5, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 3_9_5_3_4, 4_4_2_8, 3_9_7, 1_0_1_9, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 4_1_3_3_7, 1_6_7_8_6, 2_4_1, 7, 2_0_2_1_4, 1_7, 1_2_5_6_9_0, 1_0_3_9_8, 7, 4_4_3_7_8, 5_8_0_6_9, 6_8_3_4_2, 7_7_9_8, 7_3_4_3, 1_1, 2_9_9, 3_3_3_1_0, 4, 1_5_8, 3_7_3_5_0, 9_4_0_7_7, 4_5_6_9, 2_9_9, 3_3_3_1_0, 9_0, 4, 5_2_8_4_0, 2_9_0, 4, 3_1_2_7_0, 1_1_2, 2_9_9, 6_8_2, 4, 5_2_8_4_0, 3_9_9_5_3, 1_4_0_7_9, 1_9_3, 5_2_5_1_9, 9_0_8_9_4, 1_7_8_9_4, 1_2_0_6_9_7, 1_1, 4_0_4_4_5, 5_5_1, 1_7, 1_0_1_9, 5_2_5_1_9, 9_0_8_9_4, 1_7_7_5_6, 9_6_3, 1_1, 4_0_4_4_5, 4_8_0, 1_7, 9_7_9_2, 1_1_2_0, 5_1_7_3, 1_3_9_3, 6_2_4_0, 1_6_7_8_6, 2_4_1, 1_2_0_9_9_6, 2_8, 1_2_4_5, 1_3_9_3, 1_1_8_2_4_0, 1_1_1_2_3, 1_0_1_9, 9_3_6_1_2, 2_6_9_1, 1_0_6_1_8, 9_8_0_5_8, 1_2_0_4_0_9, 1_9_2_8, 2_7_9, 4, 4_0_6_8_3, 3_6_7, 1_7_8, 2_0_7, 1_0_1_9, 1_0_3, 1_0_3_1_2_1, 5_0_6, 6_5_2_9_6, 5, 2], [1_2_8_0_2_2, 2_1_2_1_7, 3_6_7, 1_1_7, 1_2_5_4_5_0, 1_2_8, 7_1_9, 7, 7_3_0_8, 4_0, 9_3_6_1_2, 1_2_6_6_9, 1_1_1_6, 1_6_7_0_4, 7_1, 1_7_7_8_5, 3_6_9_9, 1_5_5_9_2, 3_5, 1_4_4, 9_5_8_4, 2_4_1, 1_1_9_4_3, 7_1_3, 9_5_0, 7_9_9, 2_2_4_7, 8_8_4_2_7, 1_5_0, 1_4_9, 1_1_8_8_1_3, 1_2_0_7_0_6, 1_0_1_9, 1_0_6_9_0_6, 8_1_5_1_8, 2_8, 1_2_2_4, 2_2_7_9_9, 3_9_7, 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_2_8_0_2_2, 1_6_5_8, 1_2_3_3_1_1, 5_1_5_5, 5_5_7_8, 4_7_2_2, 2_7_9, 1_4_9_4_7, 2_3_6_6, 1_1_2_0, 1_1_9_7, 1_4, 1_3_4_8, 9_2_3_2, 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=UpperCamelCase     ,  model_name="facebook/m2m100_418M"     ,  revision="c168bae485c864188cf9aa0e4108b0b6934dc91e"     ,  )






@require_torch
@require_sentencepiece
@require_tokenizers
class       _SCREAMING_SNAKE_CASE	(unittest.TestCase ):
     lowerCAmelCase					=			"""facebook/m2m100_418M"""
     lowerCAmelCase					=			[
         """In my opinion, there are two levels of response from the French government.""",
         """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
     ]
     lowerCAmelCase					=			[
         """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
     lowerCAmelCase					=			[EN_CODE, 593, 1949, 11_5781, 4, 7_1586, 4234, 6_0633, 12_6233, 432, 12_3808, 1_5592, 1197, 11_7132, 12_0618, 5, 2]





     @classmethod
     def 	__snake_case    (       cls :							List[Any]				)->Union[str, Any]:
      __SCREAMING_SNAKE_CASE       :    MaMaaaTokenizer       =	MaMaaaTokenizer.from_pretrained(
          cls.checkpoint_name     ,  src_lang="en"     ,  tgt_lang="fr"				)
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	1
      return cls





     def 	__snake_case    (       self :							Dict				)->Any:
      self.assertEqual(self.tokenizer.get_lang_id("ar"				)     ,  1_2_8_0_0_6				)
      self.assertEqual(self.tokenizer.get_lang_id("en"				)     ,  1_2_8_0_2_2				)
      self.assertEqual(self.tokenizer.get_lang_id("ro"				)     ,  1_2_8_0_7_6				)
      self.assertEqual(self.tokenizer.get_lang_id("mr"				)     ,  1_2_8_0_6_3				)





     def 	__snake_case    (       self :							Any				)->Union[str, Any]:
      __SCREAMING_SNAKE_CASE       :    str       =	self.tokenizer.get_vocab()
      self.assertEqual(len(UpperCamelCase				)     ,  self.tokenizer.vocab_size				)
      self.assertEqual(vocab["<unk>"]     ,  3				)
      self.assertIn(self.tokenizer.get_lang_token("en"				)     ,  UpperCamelCase				)





     def 	__snake_case    (       self :							List[Any]				)->str:
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	"en"
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	self.tokenizer.batch_encode_plus(self.src_text				).input_ids[0]
      self.assertListEqual(self.expected_src_tokens     ,  UpperCamelCase				)





     def 	__snake_case    (       self :							Union[str, Any]				)->List[Any]:
      self.assertIn(UpperCamelCase     ,  self.tokenizer.all_special_ids				)
      # fmt: off
      __SCREAMING_SNAKE_CASE       :    Dict       =	[FR_CODE, 5_3_6_4, 8_2, 8_6_4_2, 4, 2_9_4, 4_7, 8, 1_4_0_2_8, 1_3_6, 3_2_8_6, 9_7_0_6, 6, 9_0_7_9_7, 6, 1_4_4_0_1_2, 1_6_2, 8_8_1_2_8, 3_0_0_6_1, 5, 2]
      # fmt: on
      __SCREAMING_SNAKE_CASE       :    int       =	self.tokenizer.decode(UpperCamelCase     ,  skip_special_tokens=UpperCamelCase				)
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	self.tokenizer.decode(generated_ids[1:]     ,  skip_special_tokens=UpperCamelCase				)
      self.assertEqual(UpperCamelCase     ,  UpperCamelCase				)
      self.assertNotIn(self.tokenizer.eos_token     ,  UpperCamelCase				)





     def 	__snake_case    (       self :							Any				)->List[Any]:
      __SCREAMING_SNAKE_CASE       :    int       =	tempfile.mkdtemp()
      __SCREAMING_SNAKE_CASE       :    List[Any]       =	self.tokenizer.lang_token_to_id
      self.tokenizer.save_pretrained(UpperCamelCase				)
      __SCREAMING_SNAKE_CASE       :    Any       =	MaMaaaTokenizer.from_pretrained(UpperCamelCase				)
      self.assertDictEqual(new_tok.lang_token_to_id     ,  UpperCamelCase				)





     @require_torch
     def 	__snake_case    (       self :							Any				)->int:
      __SCREAMING_SNAKE_CASE       :    List[str]       =	"en"
      __SCREAMING_SNAKE_CASE       :    Dict       =	"fr"

      __SCREAMING_SNAKE_CASE       :    str       =	self.tokenizer(self.src_text     ,  text_target=self.tgt_text     ,  padding=UpperCamelCase     ,  return_tensors="pt"				)

      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	shift_tokens_right(
          batch["labels"]     ,  self.tokenizer.pad_token_id     ,  self.tokenizer.eos_token_id				)

      for k in batch:
       __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	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 	__snake_case    (       self :							str				)->int:
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	"mr"
      self.assertListEqual(self.tokenizer.prefix_tokens     ,  [self.tokenizer.get_lang_id("mr"				)]				)
      self.assertListEqual(self.tokenizer.suffix_tokens     ,  [self.tokenizer.eos_token_id]				)

      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	"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 	__snake_case    (       self :							Optional[Any]				)->List[Any]:
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	"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				)]				)

      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	"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 	__snake_case    (       self :							Tuple				)->Optional[int]:
      __SCREAMING_SNAKE_CASE       :    Any       =	self.tokenizer._build_translation_inputs("A test"     ,  return_tensors="pt"     ,  src_lang="en"     ,  tgt_lang="ar"				)

      self.assertEqual(
          nested_simplify(UpperCamelCase				)     ,  {
              # en_XX, A, test, EOS
              "input_ids": [[1_2_8_0_2_2, 5_8, 4_1_8_3, 2]],
              "attention_mask": [[1, 1, 1, 1]],
              # ar_AR
              "forced_bos_token_id": 1_2_8_0_0_6,
          }     ,  )






