





from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

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


if TYPE_CHECKING:
    from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


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

__lowerCamelCase       :     List[Any]   =     {
    """microsoft/deberta-v2-xlarge""": """https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/config.json""",
    """microsoft/deberta-v2-xxlarge""": """https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/config.json""",
    """microsoft/deberta-v2-xlarge-mnli""": (
        """https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/config.json"""
    ),
    """microsoft/deberta-v2-xxlarge-mnli""": (
        """https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/config.json"""
    ),
}



class 					A__   (       __snake_case			):
      _UpperCAmelCase	:Dict						    =   'deberta-v2'





      def __init__( self       ,							A_=12_8100       ,							A_=1536       ,							A_=24       ,							A_=24       ,							A_=6144       ,							A_="gelu"       ,							A_=0.1       ,							A_=0.1       ,							A_=512       ,							A_=0       ,							A_=0.02       ,							A_=1e-7       ,							A_=False       ,							A_=-1       ,							A_=0       ,							A_=True       ,							A_=None       ,							A_=0       ,							A_="gelu"       ,							**A_       ,							):
       '''simple docstring'''




       super().__init__(**A_   )

       UpperCamelCase	:					Optional[Any]       	=   hidden_size
       UpperCamelCase	:					Optional[int]       	=   num_hidden_layers
       UpperCamelCase	:					Tuple       	=   num_attention_heads
       UpperCamelCase	:					Optional[int]       	=   intermediate_size
       UpperCamelCase	:					str       	=   hidden_act
       UpperCamelCase	:					List[Any]       	=   hidden_dropout_prob
       UpperCamelCase	:					List[Any]       	=   attention_probs_dropout_prob
       UpperCamelCase	:					List[str]       	=   max_position_embeddings
       UpperCamelCase	:					Optional[Any]       	=   type_vocab_size
       UpperCamelCase	:					Dict       	=   initializer_range
       UpperCamelCase	:					str       	=   relative_attention
       UpperCamelCase	:					Union[str, Any]       	=   max_relative_positions
       UpperCamelCase	:					List[Any]       	=   pad_token_id
       UpperCamelCase	:					Tuple       	=   position_biased_input

       # Backwards compatibility
       if type(A_   ) == str:
        UpperCamelCase	:					Any       	=   [x.strip() for x in pos_att_type.lower().split("|"   )]

       UpperCamelCase	:					Any       	=   pos_att_type
       UpperCamelCase	:					Optional[Any]       	=   vocab_size
       UpperCamelCase	:					Optional[int]       	=   layer_norm_eps

       UpperCamelCase	:					List[str]       	=   kwargs.get("pooler_hidden_size"       ,							A_   )
       UpperCamelCase	:					Any       	=   pooler_dropout
       UpperCamelCase	:					Optional[Any]       	=   pooler_hidden_act



class 					A__   (       __snake_case			):





      @property
      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       if self.task == "multiple-choice":
        UpperCamelCase	:					str       	=   {0: "batch", 1: "choice", 2: "sequence"}
       else:
        UpperCamelCase	:					List[Any]       	=   {0: "batch", 1: "sequence"}
       if self._config.type_vocab_size > 0:
        return OrderedDict(
            [("input_ids", dynamic_axis), ("attention_mask", dynamic_axis), ("token_type_ids", dynamic_axis)]   )
       else:
        return OrderedDict([("input_ids", dynamic_axis), ("attention_mask", dynamic_axis)]   )





      @property
      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       return 12





      def        __UpperCamelCase( self       ,							A_       ,							A_ = -1       ,							A_ = -1       ,							A_ = -1       ,							A_ = False       ,							A_ = None       ,							A_ = 3       ,							A_ = 40       ,							A_ = 40       ,							A_ = None       ,							):
       '''simple docstring'''




       UpperCamelCase	:					List[Any]       	=   super().generate_dummy_inputs(preprocessor=A_       ,							framework=A_   )
       if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
        del dummy_inputs["token_type_ids"]
       return dummy_inputs




'''simple docstring'''
def 			a      (			__a ,					__a   )  ->	int:



					'''simple docstring'''






					if len(__a   ) != len(__a   ):
										raise ValueError('''String lengths must match!'''   )

					UpperCamelCase__   :Union[str, Any]												= 0

					for chara, chara in zip(__a ,					__a   ):
										if chara != chara:
															count += 1

					return count


if __name__ == "__main__":
		import doctest

		doctest.testmod()