






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


A_		:		Union[str, Any]		     =			{}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A_		:		Optional[int]		     =			['GPTSw3Tokenizer']


if TYPE_CHECKING:
   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_gpt_swa import GPTSwaTokenizer

else:
   import sys

   A_		:		Tuple		     =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







from collections import OrderedDict
from typing import Mapping

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


A_		:		List[Any]		     =			logging.get_logger(__name__)

A_		:		Optional[Any]		     =			{
    'YituTech/conv-bert-base': 'https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json',
    'YituTech/conv-bert-medium-small': (
        'https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json'
    ),
    'YituTech/conv-bert-small': 'https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json',
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}




class     _lowerCAmelCase(	UpperCAmelCase_ ):





       """simple docstring"""







       a    :		str									='''convbert'''





       def __init__( self  ,      _lowerCamelCase=3_0_5_2_2  ,      _lowerCamelCase=7_6_8  ,      _lowerCamelCase=1_2  ,      _lowerCamelCase=1_2  ,      _lowerCamelCase=3_0_7_2  ,      _lowerCamelCase="gelu"  ,      _lowerCamelCase=0.1  ,      _lowerCamelCase=0.1  ,      _lowerCamelCase=5_1_2  ,      _lowerCamelCase=2  ,      _lowerCamelCase=0.0_2  ,      _lowerCamelCase=1e-12  ,      _lowerCamelCase=1  ,      _lowerCamelCase=0  ,      _lowerCamelCase=2  ,      _lowerCamelCase=7_6_8  ,      _lowerCamelCase=2  ,      _lowerCamelCase=9  ,      _lowerCamelCase=1  ,      _lowerCamelCase=None  ,      **_lowerCamelCase  ,      ):
         super().__init__(
             pad_token_id=_lowerCamelCase  ,      bos_token_id=_lowerCamelCase  ,      eos_token_id=_lowerCamelCase  ,      **_lowerCamelCase  ,      )

         UpperCamelCase_: Dict   				=    vocab_size
         UpperCamelCase_: Tuple   				=    hidden_size
         UpperCamelCase_: Optional[int]   				=    num_hidden_layers
         UpperCamelCase_: Optional[int]   				=    num_attention_heads
         UpperCamelCase_: Optional[Any]   				=    intermediate_size
         UpperCamelCase_: Tuple   				=    hidden_act
         UpperCamelCase_: Any   				=    hidden_dropout_prob
         UpperCamelCase_: Any   				=    attention_probs_dropout_prob
         UpperCamelCase_: List[Any]   				=    max_position_embeddings
         UpperCamelCase_: List[Any]   				=    type_vocab_size
         UpperCamelCase_: Optional[int]   				=    initializer_range
         UpperCamelCase_: Tuple   				=    layer_norm_eps
         UpperCamelCase_: List[str]   				=    embedding_size
         UpperCamelCase_: int   				=    head_ratio
         UpperCamelCase_: Dict   				=    conv_kernel_size
         UpperCamelCase_: List[Any]   				=    num_groups
         UpperCamelCase_: Dict   				=    classifier_dropout







class     _lowerCAmelCase(	UpperCAmelCase_ ):





       """simple docstring"""







       @property
       def       _a   ( self							):
         if self.task == "multiple-choice":
           UpperCamelCase_: Dict   				=    {0: 'batch', 1: 'choice', 2: 'sequence'}
         else:
           UpperCamelCase_: Dict   				=    {0: 'batch', 1: 'sequence'}
         return OrderedDict(
             [
                 ('input_ids', dynamic_axis),
                 ('attention_mask', dynamic_axis),
                 ('token_type_ids', dynamic_axis),
             ]							)