
from collections import OrderedDict
from typing import Mapping

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


__magic_name__  							=	logging.get_logger(__name__)

__magic_name__  							=	{
    '''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        _SCREAMING_SNAKE_CASE	(   __UpperCamelCase			):
      _A    :		Optional[Any]     						=  'convbert'
      def __init__(      self		,						lowerCamelCase=3_05_22		,						lowerCamelCase=7_68		,						lowerCamelCase=12		,						lowerCamelCase=12		,						lowerCamelCase=30_72		,						lowerCamelCase="gelu"		,						lowerCamelCase=0.1		,						lowerCamelCase=0.1		,						lowerCamelCase=5_12		,						lowerCamelCase=2		,						lowerCamelCase=0.0_2		,						lowerCamelCase=1e-12		,						lowerCamelCase=1		,						lowerCamelCase=0		,						lowerCamelCase=2		,						lowerCamelCase=7_68		,						lowerCamelCase=2		,						lowerCamelCase=9		,						lowerCamelCase=1		,						lowerCamelCase=None		,						**lowerCamelCase		,						):
          super().__init__(
              pad_token_id=lowerCamelCase		,						bos_token_id=lowerCamelCase		,						eos_token_id=lowerCamelCase		,						**lowerCamelCase		,						)

          snake_case__    =					vocab_size
          snake_case__    =					hidden_size
          snake_case__    =					num_hidden_layers
          snake_case__    =					num_attention_heads
          snake_case__    =					intermediate_size
          snake_case__    =					hidden_act
          snake_case__    =					hidden_dropout_prob
          snake_case__    =					attention_probs_dropout_prob
          snake_case__    =					max_position_embeddings
          snake_case__    =					type_vocab_size
          snake_case__    =					initializer_range
          snake_case__    =					layer_norm_eps
          snake_case__    =					embedding_size
          snake_case__    =					head_ratio
          snake_case__    =					conv_kernel_size
          snake_case__    =					num_groups
          snake_case__    =					classifier_dropout





class        _SCREAMING_SNAKE_CASE	(   __UpperCamelCase			):
      @property
      def A_      (      self			):
          if self.task == "multiple-choice":
              snake_case__    =					{0: "batch", 1: "choice", 2: "sequence"}
          else:
              snake_case__    =					{0: "batch", 1: "sequence"}
          return OrderedDict(
              [
                  ("input_ids", dynamic_axis),
                  ("attention_mask", dynamic_axis),
                  ("token_type_ids", dynamic_axis),
              ]			)





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				):
    return round(float(moles / volume				) * nfactor				)





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				):
    return round(float((moles * 0.0_821 * temperature) / (volume)				)				)





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				):
    return round(float((moles * 0.0_821 * temperature) / (pressure)				)				)





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				):
    return round(float((pressure * volume) / (0.0_821 * moles)				)				)


if __name__ == "__main__":
     import doctest

     doctest.testmod()



