






"""simple docstring"""



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-base""": """https://huggingface.co/microsoft/deberta-base/resolve/main/config.json""",
    """microsoft/deberta-large""": """https://huggingface.co/microsoft/deberta-large/resolve/main/config.json""",
    """microsoft/deberta-xlarge""": """https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json""",
    """microsoft/deberta-base-mnli""": """https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json""",
    """microsoft/deberta-large-mnli""": """https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json""",
    """microsoft/deberta-xlarge-mnli""": """https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json""",
}




class        lowerCAmelCase__       (  __magic_name__					):
   SCREAMING_SNAKE_CASE_					      ='''deberta'''
   def __init__(						self	:     List[Any]				,       snake_case__	:     str=5_0_2_6_5				,       snake_case__	:     Optional[int]=7_6_8				,       snake_case__	:     Dict=1_2				,       snake_case__	:     List[Any]=1_2				,       snake_case__	:     int=3_0_7_2				,       snake_case__	:     List[Any]="gelu"				,       snake_case__	:     Optional[Any]=0.1				,       snake_case__	:     Optional[int]=0.1				,       snake_case__	:     List[str]=5_1_2				,       snake_case__	:     Optional[int]=0				,       snake_case__	:     List[Any]=0.02				,       snake_case__	:     List[str]=1e-7				,       snake_case__	:     Tuple=False				,       snake_case__	:     Tuple=-1				,       snake_case__	:     Any=0				,       snake_case__	:     Optional[Any]=True				,       snake_case__	:     Dict=None				,       snake_case__	:     Dict=0				,       snake_case__	:     Any="gelu"				,       **snake_case__	:     Tuple				,       ):


        '''simple docstring'''
        super().__init__(**snake_case__				)

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

        # Backwards compatibility
        if type(snake_case__				) == str:
             UpperCAmelCase__		:  Dict				=				[x.strip() for x in pos_att_type.lower().split("|"				)]

        UpperCAmelCase__		:  int				=				pos_att_type
        UpperCAmelCase__		:  List[str]				=				vocab_size
        UpperCAmelCase__		:  Dict				=				layer_norm_eps

        UpperCAmelCase__		:  Optional[int]				=				kwargs.get("pooler_hidden_size"				,       snake_case__				)
        UpperCAmelCase__		:  Tuple				=				pooler_dropout
        UpperCAmelCase__		:  Tuple				=				pooler_hidden_act




class        lowerCAmelCase__       (  __magic_name__					):
   @property
   def 	__a				(						self	:     Tuple				):


        '''simple docstring'''
        if self.task == "multiple-choice":
             UpperCAmelCase__		:  Optional[int]				=				{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 	__a				(						self	:     str				):


        '''simple docstring'''
        return 1_2




   def 	__a				(						self	:     str				,       snake_case__	:     Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]				,       snake_case__	:     int = -1				,       snake_case__	:     int = -1				,       snake_case__	:     int = -1				,       snake_case__	:     bool = False				,       snake_case__	:     Optional["TensorType"] = None				,       snake_case__	:     int = 3				,       snake_case__	:     int = 4_0				,       snake_case__	:     int = 4_0				,       snake_case__	:     "PreTrainedTokenizerBase" = None				,       ):


        '''simple docstring'''
        UpperCAmelCase__		:  Union[str, Any]				=				super().generate_dummy_inputs(preprocessor=snake_case__				,       framework=snake_case__				)
        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'''



from ..utils import DummyObject, requires_backends

class       _a (metaclass=_lowerCamelCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE					=     ['torch', 'librosa']






       def __init__(							self				,							*A__				,							**A__					)			->	str:
          requires_backends(self				,							["""torch""", """librosa"""]					)






       @classmethod
       def 				UpperCamelCase (							cls				,							*A__				,							**A__					)			->	Tuple:
          requires_backends(cls				,							["""torch""", """librosa"""]					)






       @classmethod
       def 				UpperCamelCase (							cls				,							*A__				,							**A__					)			->	Optional[Any]:
          requires_backends(cls				,							["""torch""", """librosa"""]					)






class       _a (metaclass=_lowerCamelCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE					=     ['torch', 'librosa']






       def __init__(							self				,							*A__				,							**A__					)			->	Dict:
          requires_backends(self				,							["""torch""", """librosa"""]					)






       @classmethod
       def 				UpperCamelCase (							cls				,							*A__				,							**A__					)			->	Optional[Any]:
          requires_backends(cls				,							["""torch""", """librosa"""]					)






       @classmethod
       def 				UpperCamelCase (							cls				,							*A__				,							**A__					)			->	Union[str, Any]:
          requires_backends(cls				,							["""torch""", """librosa"""]					)






