


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


__UpperCamelCase    		=       logging.get_logger(__name__)

__UpperCamelCase    		=       {
    '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        lowerCamelCase__	(							lowercase_      ):






			"""simple docstring"""






			_UpperCamelCase		:					int    =		'deberta-v2'




			def __init__(							self      ,						snake_case=128100      ,						snake_case=1536      ,						snake_case=24      ,						snake_case=24      ,						snake_case=6144      ,						snake_case="gelu"      ,						snake_case=0.1      ,						snake_case=0.1      ,						snake_case=512      ,						snake_case=0      ,						snake_case=0.02      ,						snake_case=1E-7      ,						snake_case=False      ,						snake_case=-1      ,						snake_case=0      ,						snake_case=True      ,						snake_case=None      ,						snake_case=0      ,						snake_case="gelu"      ,						**snake_case      ,						):

						'''simple docstring'''


						super().__init__(**lowerCamelCase_     )

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

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

						UpperCamelCase__					=       pos_att_type
						UpperCamelCase__					=       vocab_size
						UpperCamelCase__					=       layer_norm_eps

						UpperCamelCase__					=       kwargs.get("pooler_hidden_size"      ,						lowerCamelCase_     )
						UpperCamelCase__					=       pooler_dropout
						UpperCamelCase__					=       pooler_hidden_act







class        lowerCamelCase__	(							lowercase_      ):






			"""simple docstring"""






			@property
			def 				snake_case__				(							self     ):

						'''simple docstring'''


						if self.task == "multiple-choice":
									UpperCamelCase__					=       {0: """batch""", 1: """choice""", 2: """sequence"""}
						else:
									UpperCamelCase__					=       {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 				snake_case__				(							self     ):

						'''simple docstring'''


						return 12







			def 				snake_case__				(							self      ,						snake_case      ,						snake_case = -1      ,						snake_case = -1      ,						snake_case = -1      ,						snake_case = False      ,						snake_case = None      ,						snake_case = 3      ,						snake_case = 40      ,						snake_case = 40      ,						snake_case = None      ,						):

						'''simple docstring'''


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






from abc import ABC, abstractmethod
from argparse import ArgumentParser







class        lowerCamelCase__	(							UpperCAmelCase      ):






			"""simple docstring"""






			@staticmethod
			@abstractmethod
			def 				snake_case__				(							snake_case     ):

						'''simple docstring'''


						raise NotImplementedError()







			@abstractmethod
			def 				snake_case__				(							self     ):

						'''simple docstring'''


						raise NotImplementedError()


