




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							=      logging.get_logger(__name__)

_lowerCamelCase							=      {
    '''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        UpperCAmelCase__				(							a__				):



     '''simple docstring'''
     _SCREAMING_SNAKE_CASE      :					List[Any]     					=    'deberta'
     def __init__(				self ,    _lowerCAmelCase=50_265 ,    _lowerCAmelCase=768 ,    _lowerCAmelCase=12 ,    _lowerCAmelCase=12 ,    _lowerCAmelCase=3_072 ,    _lowerCAmelCase="gelu" ,    _lowerCAmelCase=0.1 ,    _lowerCAmelCase=0.1 ,    _lowerCAmelCase=512 ,    _lowerCAmelCase=0 ,    _lowerCAmelCase=0.02 ,    _lowerCAmelCase=1E-7 ,    _lowerCAmelCase=False ,    _lowerCAmelCase=-1 ,    _lowerCAmelCase=0 ,    _lowerCAmelCase=True ,    _lowerCAmelCase=None ,    _lowerCAmelCase=0 ,    _lowerCAmelCase="gelu" ,    **_lowerCAmelCase ,    ):
            super().__init__(**__UpperCAmelCase	)

            a			   =hidden_size
            a			   =num_hidden_layers
            a			   =num_attention_heads
            a			   =intermediate_size
            a			   =hidden_act
            a			   =hidden_dropout_prob
            a			   =attention_probs_dropout_prob
            a			   =max_position_embeddings
            a			   =type_vocab_size
            a			   =initializer_range
            a			   =relative_attention
            a			   =max_relative_positions
            a			   =pad_token_id
            a			   =position_biased_input

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

            a			   =pos_att_type
            a			   =vocab_size
            a			   =layer_norm_eps

            a			   =kwargs.get("""pooler_hidden_size""" ,    __UpperCAmelCase	)
            a			   =pooler_dropout
            a			   =pooler_hidden_act



class        UpperCAmelCase__				(							a__				):



     '''simple docstring'''
     @property
     def        lowerCAmelCase__  (				self	):
            if self.task == "multiple-choice":
                   a			   ={0: """batch""", 1: """choice""", 2: """sequence"""}
            else:
                   a			   ={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        lowerCAmelCase__  (				self	):
            return 12






     def        lowerCAmelCase__  (				self ,    _lowerCAmelCase ,    _lowerCAmelCase = -1 ,    _lowerCAmelCase = -1 ,    _lowerCAmelCase = -1 ,    _lowerCAmelCase = False ,    _lowerCAmelCase = None ,    _lowerCAmelCase = 3 ,    _lowerCAmelCase = 40 ,    _lowerCAmelCase = 40 ,    _lowerCAmelCase = None ,    ):
            a			   =super().generate_dummy_inputs(preprocessor=__UpperCAmelCase ,    framework=__UpperCAmelCase	)
            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 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


__snake_case												=							logging.get_logger(__name__)

__snake_case												=							{
    '''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	(       a__					):

     '''simple docstring'''
     A_							:						List[Any]     =		'deberta'


     def __init__(   self     ,					__UpperCAmelCase=50265     ,					__UpperCAmelCase=768     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=3072     ,					__UpperCAmelCase="gelu"     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=512     ,					__UpperCAmelCase=0     ,					__UpperCAmelCase=0.02     ,					__UpperCAmelCase=1e-7     ,					__UpperCAmelCase=False     ,					__UpperCAmelCase=-1     ,					__UpperCAmelCase=0     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=None     ,					__UpperCAmelCase=0     ,					__UpperCAmelCase="gelu"     ,					**__UpperCAmelCase     ,					)							->				Any:
          super().__init__(**__UpperCAmelCase				)

          _a     						=					hidden_size
          _a     						=					num_hidden_layers
          _a     						=					num_attention_heads
          _a     						=					intermediate_size
          _a     						=					hidden_act
          _a     						=					hidden_dropout_prob
          _a     						=					attention_probs_dropout_prob
          _a     						=					max_position_embeddings
          _a     						=					type_vocab_size
          _a     						=					initializer_range
          _a     						=					relative_attention
          _a     						=					max_relative_positions
          _a     						=					pad_token_id
          _a     						=					position_biased_input

          # Backwards compatibility
          if type(__UpperCAmelCase				) == str:
               _a     						=					[x.strip() for x in pos_att_type.lower().split('''|'''				)]

          _a     						=					pos_att_type
          _a     						=					vocab_size
          _a     						=					layer_norm_eps

          _a     						=					kwargs.get('''pooler_hidden_size'''     ,					__UpperCAmelCase				)
          _a     						=					pooler_dropout
          _a     						=					pooler_hidden_act







class      __lowerCamelCase	(       a__					):

     '''simple docstring'''


     @property
     def 				_UpperCAmelCase   (   self				)							->				Mapping[str, Mapping[int, str]]:
          if self.task == "multiple-choice":
               _a     						=					{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
          else:
               _a     						=					{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				)							->				int:
          return 12





     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = -1     ,					__UpperCAmelCase = -1     ,					__UpperCAmelCase = -1     ,					__UpperCAmelCase = False     ,					__UpperCAmelCase = None     ,					__UpperCAmelCase = 3     ,					__UpperCAmelCase = 40     ,					__UpperCAmelCase = 40     ,					__UpperCAmelCase = None     ,					)							->				Mapping[str, Any]:
          _a     						=					super().generate_dummy_inputs(preprocessor=__UpperCAmelCase     ,					framework=__UpperCAmelCase				)
          if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
               del dummy_inputs["token_type_ids"]
          return dummy_inputs