





"""simple docstring"""
import os
from shutil import copyfile
from typing import Optional, Tuple

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
   from .tokenization_deberta_va import DebertaVaTokenizer
else:
   lowerCAmelCase:	Optional[Any]							      =None

lowerCAmelCase:	Tuple							      =logging.get_logger(__name__)

lowerCAmelCase:	List[str]							      ={"vocab_file": "spm.model", "tokenizer_file": "tokenizer.json"}

lowerCAmelCase:	Union[str, Any]							      ={
    "vocab_file": {
        "microsoft/deberta-v2-xlarge": "https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model",
        "microsoft/deberta-v2-xxlarge": "https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model",
        "microsoft/deberta-v2-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model"
        ),
        "microsoft/deberta-v2-xxlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model"
        ),
    }
}

lowerCAmelCase:	int							      ={
    "microsoft/deberta-v2-xlarge": 512,
    "microsoft/deberta-v2-xxlarge": 512,
    "microsoft/deberta-v2-xlarge-mnli": 512,
    "microsoft/deberta-v2-xxlarge-mnli": 512,
}

lowerCAmelCase:	List[Any]							      ={
    "microsoft/deberta-v2-xlarge": {"do_lower_case": False},
    "microsoft/deberta-v2-xxlarge": {"do_lower_case": False},
    "microsoft/deberta-v2-xlarge-mnli": {"do_lower_case": False},
    "microsoft/deberta-v2-xxlarge-mnli": {"do_lower_case": False},
}
class lowerCamelCase__  (    __UpperCamelCase				):
   __UpperCAmelCase        =					VOCAB_FILES_NAMES
   __UpperCAmelCase        =					PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase        =					PRETRAINED_INIT_CONFIGURATION
   __UpperCAmelCase        =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase        =					DebertaVaTokenizer



   def __init__(       self      ,   snake_case=None      ,   snake_case=None      ,   snake_case=False      ,   snake_case=False      ,   snake_case="[CLS]"      ,   snake_case="[SEP]"      ,   snake_case="[UNK]"      ,   snake_case="[SEP]"      ,   snake_case="[PAD]"      ,   snake_case="[CLS]"      ,   snake_case="[MASK]"      ,   **snake_case      ,   ) ->    None:







      """simple docstring"""
      super().__init__(
          snake_case      ,   tokenizer_file=snake_case      ,   do_lower_case=snake_case      ,   bos_token=snake_case      ,   eos_token=snake_case      ,   unk_token=snake_case      ,   sep_token=snake_case      ,   pad_token=snake_case      ,   cls_token=snake_case      ,   mask_token=snake_case      ,   split_by_punct=snake_case      ,   **snake_case      ,   )

      lowercase    :			Dict  =       do_lower_case
      lowercase    :			Optional[int]  =       split_by_punct
      lowercase    :			Optional[Any]  =       vocab_file
      lowercase    :			str  =       False if not self.vocab_file else True



   def    _UpperCAmelCase	(       self      ,   snake_case      ,   snake_case=None	) ->    Optional[int]:







      """simple docstring"""

      if token_ids_a is None:
         return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      lowercase    :			int  =       [self.cls_token_id]
      lowercase    :			int  =       [self.sep_token_id]
      return cls + token_ids_a + sep + token_ids_a + sep



   def    _UpperCAmelCase	(       self      ,   snake_case      ,   snake_case=None      ,   snake_case=False	) ->    Optional[int]:







      """simple docstring"""

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

      if token_ids_a is not None:
         return [1] + ([0] * len(snake_case	)) + [1] + ([0] * len(snake_case	)) + [1]
      return [1] + ([0] * len(snake_case	)) + [1]



   def    _UpperCAmelCase	(       self      ,   snake_case      ,   snake_case=None	) ->    Any:







      """simple docstring"""
      lowercase    :			Optional[int]  =       [self.sep_token_id]
      lowercase    :			Optional[Any]  =       [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      ,   snake_case      ,   snake_case = None	) ->    Tuple[str]:







      """simple docstring"""
      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(snake_case	):
         logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
         return
      lowercase    :			Any  =       os.path.join(
          snake_case      ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]	)

      if os.path.abspath(self.vocab_file	) != os.path.abspath(snake_case	):
         copyfile(self.vocab_file      ,   snake_case	)

      return (out_vocab_file,)









"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase:	int							      =logging.get_logger(__name__)

lowerCAmelCase:	int							      ={
    "bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/config.json",
    # QDQBERT models can be loaded from any BERT checkpoint, available at https://huggingface.co/models?filter=bert
}
class lowerCamelCase__  (    __UpperCamelCase				):
   __UpperCAmelCase        =					"""qdqbert"""



   def __init__(       self      ,   snake_case=3_0_5_2_2      ,   snake_case=7_6_8      ,   snake_case=1_2      ,   snake_case=1_2      ,   snake_case=3_0_7_2      ,   snake_case="gelu"      ,   snake_case=0.1      ,   snake_case=0.1      ,   snake_case=5_1_2      ,   snake_case=2      ,   snake_case=0.02      ,   snake_case=1E-12      ,   snake_case=True      ,   snake_case=1      ,   snake_case=0      ,   snake_case=2      ,   **snake_case      ,   ) ->    List[str]:







      """simple docstring"""
      super().__init__(pad_token_id=snake_case      ,   bos_token_id=snake_case      ,   eos_token_id=snake_case      ,   **snake_case	)

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


