





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


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

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

lowerCAmelCase_     =     25_0004
lowerCAmelCase_     =     25_0020



@require_sentencepiece
@require_tokenizers
class 							_lowerCAmelCase     (      _UpperCamelCase				,     unittest.TestCase				):


  '''simple docstring'''
  a_				:							Union[str, Any]          =MBartaaTokenizer
  a_				:							List[Any]          =MBartaaTokenizerFast
  a_				:							str          =True
  a_				:							Dict          =True







  def UpperCamelCase_			(   self   :       Any				):


    '''simple docstring'''





    super().setUp()

    # We have a SentencePiece fixture for testing
    _snake_case :					Any								=						MBartaaTokenizer(UpperCamelCase   ,					src_lang='en_XX'   ,					tgt_lang='ro_RO'   ,					keep_accents=UpperCamelCase				)
    tokenizer.save_pretrained(self.tmpdirname				)







  def UpperCamelCase_			(   self   :       Optional[int]				):


    '''simple docstring'''





    _snake_case :					Union[str, Any]								=						"<s>"
    _snake_case :					Any								=						0

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







  def UpperCamelCase_			(   self   :       Dict				):


    '''simple docstring'''





    _snake_case :					int								=						list(self.get_tokenizer().get_vocab().keys()				)

    self.assertEqual(vocab_keys[0]   ,					'<s>'				)
    self.assertEqual(vocab_keys[1]   ,					'<pad>'				)
    self.assertEqual(vocab_keys[-1]   ,					'<mask>'				)
    self.assertEqual(len(UpperCamelCase				)   ,					10_54				)







  def UpperCamelCase_			(   self   :       Optional[Any]				):


    '''simple docstring'''





    self.assertEqual(self.get_tokenizer().vocab_size   ,					10_54				)







  def UpperCamelCase_			(   self   :       Union[str, Any]				):


    '''simple docstring'''





    _snake_case :					int								=						MBartaaTokenizer(UpperCamelCase   ,					src_lang='en_XX'   ,					tgt_lang='ro_RO'   ,					keep_accents=UpperCamelCase				)

    _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				)   ,					[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]   ,					)

    _snake_case :					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', '.']   ,					)
    _snake_case :					List[str]								=						tokenizer.convert_tokens_to_ids(UpperCamelCase				)
    self.assertListEqual(
        UpperCamelCase   ,					[
            value + tokenizer.fairseq_offset
            for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
        ]   ,					)

    _snake_case :					Dict								=						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>', '.']   ,					)







  @slow
  def UpperCamelCase_			(   self   :       Tuple				):


    '''simple docstring'''





    _snake_case :					Tuple								=						{"input_ids": [[25_00_04, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [25_00_04, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 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], [25_00_04, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 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]], "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, 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], [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]]}  # noqa: E501
    # fmt: on

    self.tokenizer_integration_test_util(
        expected_encoding=UpperCamelCase   ,					model_name='facebook/mbart-large-50'   ,					revision='d3913889c59cd5c9e456b269c376325eabad57e2'   ,					)







  def UpperCamelCase_			(   self   :       Tuple				):


    '''simple docstring'''





    if not self.test_slow_tokenizer:
      # as we don't have a slow version, we can't compare the outputs between slow and fast versions
      return

    _snake_case :					Optional[Any]								=						(self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart50", {})
    for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
      with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
        _snake_case :					Union[str, Any]								=						self.rust_tokenizer_class.from_pretrained(UpperCamelCase   ,					**UpperCamelCase				)
        _snake_case :					Any								=						self.tokenizer_class.from_pretrained(UpperCamelCase   ,					**UpperCamelCase				)

        _snake_case :					Any								=						tempfile.mkdtemp()

        _snake_case :					List[Any]								=						tokenizer_r.save_pretrained(UpperCamelCase				)
        _snake_case :					int								=						tokenizer_p.save_pretrained(UpperCamelCase				)

        # Checks it save with the same files + the tokenizer.json file for the fast one
        self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files				)				)
        _snake_case :					Union[str, Any]								=						tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f				)
        self.assertSequenceEqual(UpperCamelCase   ,					UpperCamelCase				)

        # Checks everything loads correctly in the same way
        _snake_case :					str								=						tokenizer_r.from_pretrained(UpperCamelCase				)
        _snake_case :					Optional[int]								=						tokenizer_p.from_pretrained(UpperCamelCase				)

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

        shutil.rmtree(UpperCamelCase				)

        # Save tokenizer rust, legacy_format=True
        _snake_case :					Optional[Any]								=						tempfile.mkdtemp()

        _snake_case :					Union[str, Any]								=						tokenizer_r.save_pretrained(UpperCamelCase   ,					legacy_format=UpperCamelCase				)
        _snake_case :					str								=						tokenizer_p.save_pretrained(UpperCamelCase				)

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

        # Checks everything loads correctly in the same way
        _snake_case :					List[Any]								=						tokenizer_r.from_pretrained(UpperCamelCase				)
        _snake_case :					List[Any]								=						tokenizer_p.from_pretrained(UpperCamelCase				)

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

        shutil.rmtree(UpperCamelCase				)

        # Save tokenizer rust, legacy_format=False
        _snake_case :					Optional[Any]								=						tempfile.mkdtemp()

        _snake_case :					Dict								=						tokenizer_r.save_pretrained(UpperCamelCase   ,					legacy_format=UpperCamelCase				)
        _snake_case :					str								=						tokenizer_p.save_pretrained(UpperCamelCase				)

        # Checks it saved the tokenizer.json file
        self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files				)				)

        # Checks everything loads correctly in the same way
        _snake_case :					Dict								=						tokenizer_r.from_pretrained(UpperCamelCase				)
        _snake_case :					Union[str, Any]								=						tokenizer_p.from_pretrained(UpperCamelCase				)

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

        shutil.rmtree(UpperCamelCase				)




@require_torch
@require_sentencepiece
@require_tokenizers
class 							_lowerCAmelCase     (      unittest.TestCase				):


  '''simple docstring'''
  a_				:							Dict          ='facebook/mbart-large-50-one-to-many-mmt'
  a_				:							Tuple          =[
      ' UN Chief Says There Is No Military Solution in Syria',
      ' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that "there is no military solution" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.',
  ]
  a_				:							List[str]          =[
      'Şeful ONU declară că nu există o soluţie militară în Siria',
      'Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'
      ' pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi că noi arme nu vor'
      ' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.',
  ]
  a_				:							Optional[Any]          =[EN_CODE, 8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2]







  @classmethod
  def UpperCamelCase_			(   cls   :       Union[str, Any]				):


    '''simple docstring'''





    _snake_case :					MBartaaTokenizer								=						MBartaaTokenizer.from_pretrained(
        cls.checkpoint_name   ,					src_lang='en_XX'   ,					tgt_lang='ro_RO'				)
    _snake_case :					Tuple								=						1
    return cls







  def UpperCamelCase_			(   self   :       int				):


    '''simple docstring'''





    self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']   ,					25_00_01				)
    self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']   ,					25_00_04				)
    self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']   ,					25_00_20				)
    self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']   ,					25_00_38				)







  def UpperCamelCase_			(   self   :       Dict				):


    '''simple docstring'''





    _snake_case :					Any								=						self.tokenizer.batch_encode_plus(self.src_text				).input_ids[0]
    self.assertListEqual(self.expected_src_tokens   ,					UpperCamelCase				)







  def UpperCamelCase_			(   self   :       Optional[Any]				):


    '''simple docstring'''





    self.assertIn(UpperCamelCase   ,					self.tokenizer.all_special_ids				)
    _snake_case :					Union[str, Any]								=						[RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
    _snake_case :					Any								=						self.tokenizer.decode(UpperCamelCase   ,					skip_special_tokens=UpperCamelCase				)
    _snake_case :					List[Any]								=						self.tokenizer.decode(generated_ids[1:]   ,					skip_special_tokens=UpperCamelCase				)
    self.assertEqual(UpperCamelCase   ,					UpperCamelCase				)
    self.assertNotIn(self.tokenizer.eos_token   ,					UpperCamelCase				)







  def UpperCamelCase_			(   self   :       Union[str, Any]				):


    '''simple docstring'''





    _snake_case :					List[str]								=						["this is gunna be a long sentence " * 20]
    assert isinstance(src_text[0]   ,					UpperCamelCase				)
    _snake_case :					Optional[Any]								=						10
    _snake_case :					Optional[Any]								=						self.tokenizer(UpperCamelCase   ,					max_length=UpperCamelCase   ,					truncation=UpperCamelCase				).input_ids[0]
    self.assertEqual(ids[0]   ,					UpperCamelCase				)
    self.assertEqual(ids[-1]   ,					2				)
    self.assertEqual(len(UpperCamelCase				)   ,					UpperCamelCase				)







  def UpperCamelCase_			(   self   :       Tuple				):


    '''simple docstring'''





    self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']				)   ,					[25_00_53, 25_00_01]				)







  def UpperCamelCase_			(   self   :       str				):


    '''simple docstring'''





    _snake_case :					Any								=						tempfile.mkdtemp()
    _snake_case :					int								=						self.tokenizer.fairseq_tokens_to_ids
    self.tokenizer.save_pretrained(UpperCamelCase				)
    _snake_case :					Any								=						MBartaaTokenizer.from_pretrained(UpperCamelCase				)
    self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,					UpperCamelCase				)







  @require_torch
  def UpperCamelCase_			(   self   :       List[str]				):


    '''simple docstring'''





    _snake_case :					Union[str, Any]								=						self.tokenizer(self.src_text   ,					text_target=self.tgt_text   ,					padding=UpperCamelCase   ,					return_tensors='pt'				)
    _snake_case :					Optional[Any]								=						shift_tokens_right(batch['labels']   ,					self.tokenizer.pad_token_id				)

    # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
    assert batch.input_ids[1][0] == EN_CODE
    assert batch.input_ids[1][-1] == 2
    assert batch.labels[1][0] == RO_CODE
    assert batch.labels[1][-1] == 2
    assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]







  @require_torch
  def UpperCamelCase_			(   self   :       List[str]				):


    '''simple docstring'''





    _snake_case :					Dict								=						self.tokenizer(
        self.src_text   ,					text_target=self.tgt_text   ,					padding=UpperCamelCase   ,					truncation=UpperCamelCase   ,					max_length=len(self.expected_src_tokens				)   ,					return_tensors='pt'   ,					)
    _snake_case :					Optional[int]								=						shift_tokens_right(batch['labels']   ,					self.tokenizer.pad_token_id				)

    self.assertIsInstance(UpperCamelCase   ,					UpperCamelCase				)

    self.assertEqual((2, 14)   ,					batch.input_ids.shape				)
    self.assertEqual((2, 14)   ,					batch.attention_mask.shape				)
    _snake_case :					int								=						batch.input_ids.tolist()[0]
    self.assertListEqual(self.expected_src_tokens   ,					UpperCamelCase				)
    self.assertEqual(2   ,					batch.decoder_input_ids[0, 0]				)  # decoder_start_token_id
    # Test that special tokens are reset
    self.assertEqual(self.tokenizer.prefix_tokens   ,					[EN_CODE]				)
    self.assertEqual(self.tokenizer.suffix_tokens   ,					[self.tokenizer.eos_token_id]				)







  def UpperCamelCase_			(   self   :       Optional[Any]				):


    '''simple docstring'''





    _snake_case :					str								=						self.tokenizer(self.src_text   ,					padding=UpperCamelCase   ,					truncation=UpperCamelCase   ,					max_length=3   ,					return_tensors='pt'				)
    _snake_case :					Union[str, Any]								=						self.tokenizer(
        text_target=self.tgt_text   ,					padding=UpperCamelCase   ,					truncation=UpperCamelCase   ,					max_length=10   ,					return_tensors='pt'				)
    _snake_case :					int								=						targets["input_ids"]
    _snake_case :					Optional[Any]								=						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 UpperCamelCase_			(   self   :       Union[str, Any]				):


    '''simple docstring'''





    _snake_case :					Optional[Any]								=						self.tokenizer._build_translation_inputs(
        'A test'   ,					return_tensors='pt'   ,					src_lang='en_XX'   ,					tgt_lang='ar_AR'				)

    self.assertEqual(
        nested_simplify(UpperCamelCase				)   ,					{
            # en_XX, A, test, EOS
            'input_ids': [[25_00_04, 62, 30_34, 2]],
            'attention_mask': [[1, 1, 1, 1]],
            # ar_AR
            'forced_bos_token_id': 25_00_01,
        }   ,					)









"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCAmelCase							:   Optional[int]				=				logging.get_logger(__name__)

_lowerCAmelCase							:   Any				=				{
    "roberta-base": "https://huggingface.co/roberta-base/resolve/main/config.json",
    "roberta-large": "https://huggingface.co/roberta-large/resolve/main/config.json",
    "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/config.json",
    "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/config.json",
    "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json",
    "roberta-large-openai-detector": "https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json",
}






class       UpperCAmelCase_    (							_UpperCamelCase		):
      __SCREAMING_SNAKE_CASE		:  Optional[int]						=					'roberta'



      def __init__(	self	:      str	,      A	:      Optional[int]=5_0_2_6_5	,      A	:      Optional[int]=7_6_8	,      A	:      Tuple=1_2	,      A	:      Optional[Any]=1_2	,      A	:      Optional[int]=3_0_7_2	,      A	:      str="gelu"	,      A	:      List[Any]=0.1	,      A	:      Optional[Any]=0.1	,      A	:      Any=5_1_2	,      A	:      Dict=2	,      A	:      Union[str, Any]=0.02	,      A	:      str=1e-12	,      A	:      Optional[int]=1	,      A	:      List[str]=0	,      A	:      int=2	,      A	:      Any="absolute"	,      A	:      Optional[int]=True	,      A	:      int=None	,      **A	:      str	,      ):
           super().__init__(pad_token_id=A	,      bos_token_id=A	,      eos_token_id=A	,      **A		)

           _UpperCAmelCase     :      str														=       vocab_size
           _UpperCAmelCase     :      Dict														=       hidden_size
           _UpperCAmelCase     :      List[str]														=       num_hidden_layers
           _UpperCAmelCase     :      Any														=       num_attention_heads
           _UpperCAmelCase     :      List[str]														=       hidden_act
           _UpperCAmelCase     :      Any														=       intermediate_size
           _UpperCAmelCase     :      Union[str, Any]														=       hidden_dropout_prob
           _UpperCAmelCase     :      str														=       attention_probs_dropout_prob
           _UpperCAmelCase     :      Tuple														=       max_position_embeddings
           _UpperCAmelCase     :      Union[str, Any]														=       type_vocab_size
           _UpperCAmelCase     :      str														=       initializer_range
           _UpperCAmelCase     :      int														=       layer_norm_eps
           _UpperCAmelCase     :      Tuple														=       position_embedding_type
           _UpperCAmelCase     :      int														=       use_cache
           _UpperCAmelCase     :      Dict														=       classifier_dropout







class       UpperCAmelCase_    (							_UpperCamelCase		):



      @property
      def 		snake_case_   (	self	:      Tuple		):
           if self.task == "multiple-choice":
                _UpperCAmelCase     :      Optional[Any]														=       {0: "batch", 1: "choice", 2: "sequence"}
           else:
                _UpperCAmelCase     :      List[Any]														=       {0: "batch", 1: "sequence"}
           return OrderedDict(
               [
                   ("input_ids", dynamic_axis),
                   ("attention_mask", dynamic_axis),
               ]		)
