
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path

import pytest

import transformers
from transformers import (
    BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
    GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
    AutoTokenizer,
    BertConfig,
    BertTokenizer,
    BertTokenizerFast,
    CTRLTokenizer,
    GPTaTokenizer,
    GPTaTokenizerFast,
    PreTrainedTokenizerFast,
    RobertaTokenizer,
    RobertaTokenizerFast,
    is_tokenizers_available,
)
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.auto.tokenization_auto import (
    TOKENIZER_MAPPING,
    get_tokenizer_config,
    tokenizer_class_from_name,
)
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import (
    DUMMY_DIFF_TOKENIZER_IDENTIFIER,
    DUMMY_UNKNOWN_IDENTIFIER,
    SMALL_MODEL_IDENTIFIER,
    RequestCounter,
    require_tokenizers,
    slow,
)


sys.path.append(str(Path(__file__).parent.parent.parent.parent / """utils"""))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
      from test_module.custom_tokenization_fast import CustomTokenizerFast





class 							A__		(	unittest.TestCase):
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Optional[Any]							=      0
      @slow
      def 						UpperCamelCase__							(      self      ):
       for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
        lowerCamelCase		:	Any							=      AutoTokenizer.from_pretrained(__magic_name__      )
        self.assertIsNotNone(__magic_name__      )
        self.assertIsInstance(__magic_name__    ,  (BertTokenizer, BertTokenizerFast)      )
        self.assertGreater(len(__magic_name__      )    ,  0      )

       for model_name in GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP.keys():
        lowerCamelCase		:	Tuple							=      AutoTokenizer.from_pretrained(__magic_name__      )
        self.assertIsNotNone(__magic_name__      )
        self.assertIsInstance(__magic_name__    ,  (GPTaTokenizer, GPTaTokenizerFast)      )
        self.assertGreater(len(__magic_name__      )    ,  0      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Union[str, Any]							=      AutoTokenizer.from_pretrained(__magic_name__      )
       self.assertIsInstance(__magic_name__    ,  (BertTokenizer, BertTokenizerFast)      )
       self.assertEqual(tokenizer.vocab_size    ,  1_2      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	int							=      AutoTokenizer.from_pretrained(__magic_name__      )
       self.assertIsInstance(__magic_name__    ,  (RobertaTokenizer, RobertaTokenizerFast)      )
       self.assertEqual(tokenizer.vocab_size    ,  2_0      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Dict							=      AutoConfig.from_pretrained(__magic_name__      )
       self.assertIsInstance(__magic_name__    ,  __magic_name__      )
       # Check that tokenizer_type ≠ model_type
       lowerCamelCase		:	int							=      AutoTokenizer.from_pretrained(__magic_name__    ,  config=__magic_name__      )
       self.assertIsInstance(__magic_name__    ,  (BertTokenizer, BertTokenizerFast)      )
       self.assertEqual(tokenizer.vocab_size    ,  1_2      )
      def 						UpperCamelCase__							(      self      ):
       with tempfile.TemporaryDirectory() as tmp_dir:
        shutil.copy("""./tests/fixtures/vocab.txt"""    ,  os.path.join(__magic_name__    ,  """vocab.txt"""      )      )

        lowerCamelCase		:	Optional[int]							=      AutoTokenizer.from_pretrained(__magic_name__    ,  tokenizer_type="""bert"""    ,  use_fast=__magic_name__      )
        self.assertIsInstance(__magic_name__    ,  __magic_name__      )

       with tempfile.TemporaryDirectory() as tmp_dir:
        shutil.copy("""./tests/fixtures/vocab.json"""    ,  os.path.join(__magic_name__    ,  """vocab.json"""      )      )
        shutil.copy("""./tests/fixtures/merges.txt"""    ,  os.path.join(__magic_name__    ,  """merges.txt"""      )      )

        lowerCamelCase		:	List[str]							=      AutoTokenizer.from_pretrained(__magic_name__    ,  tokenizer_type="""gpt2"""    ,  use_fast=__magic_name__      )
        self.assertIsInstance(__magic_name__    ,  __magic_name__      )
      @require_tokenizers
      def 						UpperCamelCase__							(      self      ):
       with tempfile.TemporaryDirectory() as tmp_dir:
        shutil.copy("""./tests/fixtures/vocab.txt"""    ,  os.path.join(__magic_name__    ,  """vocab.txt"""      )      )

        lowerCamelCase		:	List[str]							=      AutoTokenizer.from_pretrained(__magic_name__    ,  tokenizer_type="""bert"""      )
        self.assertIsInstance(__magic_name__    ,  __magic_name__      )

       with tempfile.TemporaryDirectory() as tmp_dir:
        shutil.copy("""./tests/fixtures/vocab.json"""    ,  os.path.join(__magic_name__    ,  """vocab.json"""      )      )
        shutil.copy("""./tests/fixtures/merges.txt"""    ,  os.path.join(__magic_name__    ,  """merges.txt"""      )      )

        lowerCamelCase		:	Any							=      AutoTokenizer.from_pretrained(__magic_name__    ,  tokenizer_type="""gpt2"""      )
        self.assertIsInstance(__magic_name__    ,  __magic_name__      )
      def 						UpperCamelCase__							(      self      ):
       with pytest.raises(__magic_name__      ):
        AutoTokenizer.from_pretrained("""./"""    ,  tokenizer_type="""xxx"""      )
      @require_tokenizers
      def 						UpperCamelCase__							(      self      ):
       for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
        lowerCamelCase		:	Union[str, Any]							=      tokenizer_class.from_pretrained("""wietsedv/bert-base-dutch-cased"""      )
        self.assertIsInstance(__magic_name__    ,  (BertTokenizer, BertTokenizerFast)      )

        if isinstance(__magic_name__    ,  __magic_name__      ):
         self.assertEqual(tokenizer.basic_tokenizer.do_lower_case    ,  __magic_name__      )
        else:
         self.assertEqual(tokenizer.do_lower_case    ,  __magic_name__      )

        self.assertEqual(tokenizer.model_max_length    ,  5_1_2      )
      @require_tokenizers
      def 						UpperCamelCase__							(      self      ):
       for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
        with self.assertRaisesRegex(
            __magic_name__    ,  """julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier"""    ,  ):
         lowerCamelCase		:	List[str]							=      tokenizer_class.from_pretrained("""julien-c/herlolip-not-exists"""      )
      def 						UpperCamelCase__							(      self      ):
       # tests: https://github.com/huggingface/transformers/pull/13251
       # 1. models with `-`, e.g. xlm-roberta -> xlm_roberta
       # 2. models that don't remap 1-1 from model-name to model file, e.g., openai-gpt -> openai
       lowerCamelCase		:	Tuple							=      TOKENIZER_MAPPING.values()
       lowerCamelCase		:	Tuple							=      []

       for slow_tok, fast_tok in tokenizers:
        if slow_tok is not None:
         tokenizer_names.append(slow_tok.__name__      )

        if fast_tok is not None:
         tokenizer_names.append(fast_tok.__name__      )

       for tokenizer_name in tokenizer_names:
        # must find the right class
        tokenizer_class_from_name(__magic_name__      )
      @require_tokenizers
      def 						UpperCamelCase__							(      self      ):
       self.assertIsInstance(AutoTokenizer.from_pretrained("""bert-base-cased"""    ,  use_fast=__magic_name__      )    ,  __magic_name__      )
       self.assertIsInstance(AutoTokenizer.from_pretrained("""bert-base-cased"""      )    ,  __magic_name__      )
      @require_tokenizers
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Union[str, Any]							=      AutoTokenizer.from_pretrained("""distilbert-base-uncased"""    ,  do_lower_case=__magic_name__      )
       lowerCamelCase		:	str							=      """Hello, world. How are you?"""
       lowerCamelCase		:	int							=      tokenizer.tokenize(__magic_name__      )
       self.assertEqual("""[UNK]"""    ,  tokens[0]      )

       lowerCamelCase		:	Dict							=      AutoTokenizer.from_pretrained("""microsoft/mpnet-base"""    ,  do_lower_case=__magic_name__      )
       lowerCamelCase		:	Optional[Any]							=      tokenizer.tokenize(__magic_name__      )
       self.assertEqual("""[UNK]"""    ,  tokens[0]      )
      @require_tokenizers
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Any							=      AutoTokenizer.from_pretrained("""robot-test/dummy-tokenizer-fast-with-model-config"""      )
       self.assertEqual(type(__magic_name__      )    ,  __magic_name__      )
       self.assertEqual(tokenizer.model_max_length    ,  5_1_2      )
       self.assertEqual(tokenizer.vocab_size    ,  3_0_0_0_0      )
       self.assertEqual(tokenizer.unk_token    ,  """[UNK]"""      )
       self.assertEqual(tokenizer.padding_side    ,  """right"""      )
       self.assertEqual(tokenizer.truncation_side    ,  """right"""      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Optional[Any]							=      AutoTokenizer.from_pretrained(__magic_name__      )
       self.assertIsInstance(__magic_name__    ,  (BertTokenizer, BertTokenizerFast)      )
       with tempfile.TemporaryDirectory() as tmp_dir:
        tokenizer.save_pretrained(__magic_name__      )
        lowerCamelCase		:	Any							=      AutoTokenizer.from_pretrained(__magic_name__      )

       self.assertIsInstance(__magic_name__    ,  tokenizer.__class__      )
       self.assertEqual(tokenizera.vocab_size    ,  1_2      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	str							=      AutoTokenizer.from_pretrained("""ctrl"""      )
       # There is no fast CTRL so this always gives us a slow tokenizer.
       self.assertIsInstance(__magic_name__    ,  __magic_name__      )
      def 						UpperCamelCase__							(      self      ):
       # Check we can load the tokenizer config of an online model.
       lowerCamelCase		:	Dict							=      get_tokenizer_config("""bert-base-cased"""      )
       lowerCamelCase		:	Optional[Any]							=      config.pop("""_commit_hash"""    ,  __magic_name__      )
       # If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
       self.assertEqual(__magic_name__    ,  {"""do_lower_case""": False}      )

       # This model does not have a tokenizer_config so we get back an empty dict.
       lowerCamelCase		:	Union[str, Any]							=      get_tokenizer_config(__magic_name__      )
       self.assertDictEqual(__magic_name__    ,  {}      )

       # A tokenizer saved with `save_pretrained` always creates a tokenizer config.
       lowerCamelCase		:	List[Any]							=      AutoTokenizer.from_pretrained(__magic_name__      )
       with tempfile.TemporaryDirectory() as tmp_dir:
        tokenizer.save_pretrained(__magic_name__      )
        lowerCamelCase		:	List[str]							=      get_tokenizer_config(__magic_name__      )

       # Check the class of the tokenizer was properly saved (note that it always saves the slow class).
       self.assertEqual(config["""tokenizer_class"""]    ,  """BertTokenizer"""      )
      def 						UpperCamelCase__							(      self      ):
       try:
        AutoConfig.register("""custom"""    ,  __magic_name__      )

        AutoTokenizer.register(__magic_name__    ,  slow_tokenizer_class=__magic_name__      )
        # Trying to register something existing in the Transformers library will raise an error
        with self.assertRaises(__magic_name__      ):
         AutoTokenizer.register(__magic_name__    ,  slow_tokenizer_class=__magic_name__      )

        lowerCamelCase		:	str							=      CustomTokenizer.from_pretrained(__magic_name__      )
        with tempfile.TemporaryDirectory() as tmp_dir:
         tokenizer.save_pretrained(__magic_name__      )

         lowerCamelCase		:	Any							=      AutoTokenizer.from_pretrained(__magic_name__      )
         self.assertIsInstance(__magic_name__    ,  __magic_name__      )

       finally:
        if "custom" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["custom"]
        if CustomConfig in TOKENIZER_MAPPING._extra_content:
         del TOKENIZER_MAPPING._extra_content[CustomConfig]
      @require_tokenizers
      def 						UpperCamelCase__							(      self      ):
       try:
        AutoConfig.register("""custom"""    ,  __magic_name__      )

        # Can register in two steps
        AutoTokenizer.register(__magic_name__    ,  slow_tokenizer_class=__magic_name__      )
        self.assertEqual(TOKENIZER_MAPPING[CustomConfig]    ,  (CustomTokenizer, None)      )
        AutoTokenizer.register(__magic_name__    ,  fast_tokenizer_class=__magic_name__      )
        self.assertEqual(TOKENIZER_MAPPING[CustomConfig]    ,  (CustomTokenizer, CustomTokenizerFast)      )

        del TOKENIZER_MAPPING._extra_content[CustomConfig]
        # Can register in one step
        AutoTokenizer.register(
            __magic_name__    ,  slow_tokenizer_class=__magic_name__    ,  fast_tokenizer_class=__magic_name__      )
        self.assertEqual(TOKENIZER_MAPPING[CustomConfig]    ,  (CustomTokenizer, CustomTokenizerFast)      )

        # Trying to register something existing in the Transformers library will raise an error
        with self.assertRaises(__magic_name__      ):
         AutoTokenizer.register(__magic_name__    ,  fast_tokenizer_class=__magic_name__      )

        # We pass through a bert tokenizer fast cause there is no converter slow to fast for our new toknizer
        # and that model does not have a tokenizer.json
        with tempfile.TemporaryDirectory() as tmp_dir:
         lowerCamelCase		:	Dict							=      BertTokenizerFast.from_pretrained(__magic_name__      )
         bert_tokenizer.save_pretrained(__magic_name__      )
         lowerCamelCase		:	Optional[Any]							=      CustomTokenizerFast.from_pretrained(__magic_name__      )

        with tempfile.TemporaryDirectory() as tmp_dir:
         tokenizer.save_pretrained(__magic_name__      )

         lowerCamelCase		:	Union[str, Any]							=      AutoTokenizer.from_pretrained(__magic_name__      )
         self.assertIsInstance(__magic_name__    ,  __magic_name__      )

         lowerCamelCase		:	Optional[int]							=      AutoTokenizer.from_pretrained(__magic_name__    ,  use_fast=__magic_name__      )
         self.assertIsInstance(__magic_name__    ,  __magic_name__      )

       finally:
        if "custom" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["custom"]
        if CustomConfig in TOKENIZER_MAPPING._extra_content:
         del TOKENIZER_MAPPING._extra_content[CustomConfig]
      def 						UpperCamelCase__							(      self      ):
       # If remote code is not set, we will time out when asking whether to load the model.
       with self.assertRaises(__magic_name__      ):
        lowerCamelCase		:	Dict							=      AutoTokenizer.from_pretrained("""hf-internal-testing/test_dynamic_tokenizer"""      )
       # If remote code is disabled, we can't load this config.
       with self.assertRaises(__magic_name__      ):
        lowerCamelCase		:	int							=      AutoTokenizer.from_pretrained(
            """hf-internal-testing/test_dynamic_tokenizer"""    ,  trust_remote_code=__magic_name__      )

       lowerCamelCase		:	List[Any]							=      AutoTokenizer.from_pretrained("""hf-internal-testing/test_dynamic_tokenizer"""    ,  trust_remote_code=__magic_name__      )
       self.assertTrue(tokenizer.special_attribute_present      )
       # Test tokenizer can be reloaded.
       with tempfile.TemporaryDirectory() as tmp_dir:
        tokenizer.save_pretrained(__magic_name__      )
        lowerCamelCase		:	Tuple							=      AutoTokenizer.from_pretrained(__magic_name__    ,  trust_remote_code=__magic_name__      )
       self.assertTrue(reloaded_tokenizer.special_attribute_present      )

       if is_tokenizers_available():
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizerFast"""      )
        self.assertEqual(reloaded_tokenizer.__class__.__name__    ,  """NewTokenizerFast"""      )

        # Test we can also load the slow version
        lowerCamelCase		:	int							=      AutoTokenizer.from_pretrained(
            """hf-internal-testing/test_dynamic_tokenizer"""    ,  trust_remote_code=__magic_name__    ,  use_fast=__magic_name__      )
        self.assertTrue(tokenizer.special_attribute_present      )
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizer"""      )
        # Test tokenizer can be reloaded.
        with tempfile.TemporaryDirectory() as tmp_dir:
         tokenizer.save_pretrained(__magic_name__      )
         lowerCamelCase		:	Union[str, Any]							=      AutoTokenizer.from_pretrained(__magic_name__    ,  trust_remote_code=__magic_name__    ,  use_fast=__magic_name__      )
        self.assertEqual(reloaded_tokenizer.__class__.__name__    ,  """NewTokenizer"""      )
        self.assertTrue(reloaded_tokenizer.special_attribute_present      )
       else:
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizer"""      )
        self.assertEqual(reloaded_tokenizer.__class__.__name__    ,  """NewTokenizer"""      )
      @require_tokenizers
      def 						UpperCamelCase__							(      self      ):





       class 							A__		(	__SCREAMING_SNAKE_CASE):
             _UpperCAmelCase				:    str           =			False





       class 							A__		(	__SCREAMING_SNAKE_CASE):
             _UpperCAmelCase				:    int           =			NewTokenizer
             _UpperCAmelCase				:    List[str]           =			False

       try:
        AutoConfig.register("""custom"""    ,  __magic_name__      )
        AutoTokenizer.register(__magic_name__    ,  slow_tokenizer_class=__magic_name__      )
        AutoTokenizer.register(__magic_name__    ,  fast_tokenizer_class=__magic_name__      )
        # If remote code is not set, the default is to use local
        lowerCamelCase		:	Union[str, Any]							=      AutoTokenizer.from_pretrained("""hf-internal-testing/test_dynamic_tokenizer"""      )
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizerFast"""      )
        self.assertFalse(tokenizer.special_attribute_present      )
        lowerCamelCase		:	List[str]							=      AutoTokenizer.from_pretrained("""hf-internal-testing/test_dynamic_tokenizer"""    ,  use_fast=__magic_name__      )
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizer"""      )
        self.assertFalse(tokenizer.special_attribute_present      )

        # If remote code is disabled, we load the local one.
        lowerCamelCase		:	Tuple							=      AutoTokenizer.from_pretrained(
            """hf-internal-testing/test_dynamic_tokenizer"""    ,  trust_remote_code=__magic_name__      )
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizerFast"""      )
        self.assertFalse(tokenizer.special_attribute_present      )
        lowerCamelCase		:	Tuple							=      AutoTokenizer.from_pretrained(
            """hf-internal-testing/test_dynamic_tokenizer"""    ,  trust_remote_code=__magic_name__    ,  use_fast=__magic_name__      )
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizer"""      )
        self.assertFalse(tokenizer.special_attribute_present      )

        # If remote is enabled, we load from the Hub
        lowerCamelCase		:	Dict							=      AutoTokenizer.from_pretrained(
            """hf-internal-testing/test_dynamic_tokenizer"""    ,  trust_remote_code=__magic_name__      )
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizerFast"""      )
        self.assertTrue(tokenizer.special_attribute_present      )
        lowerCamelCase		:	int							=      AutoTokenizer.from_pretrained(
            """hf-internal-testing/test_dynamic_tokenizer"""    ,  trust_remote_code=__magic_name__    ,  use_fast=__magic_name__      )
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizer"""      )
        self.assertTrue(tokenizer.special_attribute_present      )

       finally:
        if "custom" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["custom"]
        if CustomConfig in TOKENIZER_MAPPING._extra_content:
         del TOKENIZER_MAPPING._extra_content[CustomConfig]
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Any							=      AutoTokenizer.from_pretrained(
           """hf-internal-testing/test_dynamic_tokenizer_legacy"""    ,  trust_remote_code=__magic_name__      )
       self.assertTrue(tokenizer.special_attribute_present      )
       if is_tokenizers_available():
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizerFast"""      )

        # Test we can also load the slow version
        lowerCamelCase		:	int							=      AutoTokenizer.from_pretrained(
            """hf-internal-testing/test_dynamic_tokenizer_legacy"""    ,  trust_remote_code=__magic_name__    ,  use_fast=__magic_name__      )
        self.assertTrue(tokenizer.special_attribute_present      )
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizer"""      )
       else:
        self.assertEqual(tokenizer.__class__.__name__    ,  """NewTokenizer"""      )
      def 						UpperCamelCase__							(      self      ):
       with self.assertRaisesRegex(
           __magic_name__    ,  """bert-base is not a local folder and is not a valid model identifier"""      ):
        lowerCamelCase		:	Tuple							=      AutoTokenizer.from_pretrained("""bert-base"""      )
      def 						UpperCamelCase__							(      self      ):
       with self.assertRaisesRegex(
           __magic_name__    ,  r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""      ):
        lowerCamelCase		:	Any							=      AutoTokenizer.from_pretrained(__magic_name__    ,  revision="""aaaaaa"""      )






      def 						UpperCamelCase__							(      self      ):
       # Make sure we have cached the tokenizer.
       lowerCamelCase		:	List[str]							=      AutoTokenizer.from_pretrained("""hf-internal-testing/tiny-random-bert"""      )
       with RequestCounter() as counter:
        lowerCamelCase		:	List[str]							=      AutoTokenizer.from_pretrained("""hf-internal-testing/tiny-random-bert"""      )
        self.assertEqual(counter.get_request_count    ,  0      )
        self.assertEqual(counter.head_request_count    ,  1      )
        self.assertEqual(counter.other_request_count    ,  0      )






from collections import OrderedDict
from typing import Mapping

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


_lowerCamelCase					   =logging.get_logger(__name__)

_lowerCamelCase					   ={
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}





class 							A__		(	__SCREAMING_SNAKE_CASE):
      _UpperCAmelCase				:    Tuple           =			"""camembert"""
      def __init__(      self    ,  __magic_name__=3_0_5_2_2    ,  __magic_name__=7_6_8    ,  __magic_name__=1_2    ,  __magic_name__=1_2    ,  __magic_name__=3_0_7_2    ,  __magic_name__="gelu"    ,  __magic_name__=0.1    ,  __magic_name__=0.1    ,  __magic_name__=5_1_2    ,  __magic_name__=2    ,  __magic_name__=0.02    ,  __magic_name__=1e-12    ,  __magic_name__=1    ,  __magic_name__=0    ,  __magic_name__=2    ,  __magic_name__="absolute"    ,  __magic_name__=True    ,  __magic_name__=None    ,  **__magic_name__    ,  ):
       super().__init__(pad_token_id=__magic_name__    ,  bos_token_id=__magic_name__    ,  eos_token_id=__magic_name__    ,  **__magic_name__      )

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





class 							A__		(	__SCREAMING_SNAKE_CASE):
      @property
      def 						UpperCamelCase__							(      self      ):
       if self.task == "multiple-choice":
        lowerCamelCase		:	List[str]							=      {0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
        lowerCamelCase		:	List[str]							=      {0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
           ]      )




