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[Any]							=	logging.get_logger(__name__)

lowerCamelCase_    :		Optional[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		):
			A__    :       List[str]        =      'deberta-v2'



			def __init__(						self				,						UpperCAmelCase=1_2_8_1_0_0				,						UpperCAmelCase=1_5_3_6				,						UpperCAmelCase=2_4				,						UpperCAmelCase=2_4				,						UpperCAmelCase=6_1_4_4				,						UpperCAmelCase="gelu"				,						UpperCAmelCase=0.1				,						UpperCAmelCase=0.1				,						UpperCAmelCase=5_1_2				,						UpperCAmelCase=0				,						UpperCAmelCase=0.02				,						UpperCAmelCase=1e-7				,						UpperCAmelCase=False				,						UpperCAmelCase=-1				,						UpperCAmelCase=0				,						UpperCAmelCase=True				,						UpperCAmelCase=None				,						UpperCAmelCase=0				,						UpperCAmelCase="gelu"				,						**UpperCAmelCase				,						)			->   List[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 						a__							(       __snake_case		):



			@property
			def __SCREAMING_SNAKE_CASE							(						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 __SCREAMING_SNAKE_CASE							(						self   )			->   int:
								return 1_2







			def __SCREAMING_SNAKE_CASE							(						self				,						UpperCAmelCase				,						UpperCAmelCase = -1				,						UpperCAmelCase = -1				,						UpperCAmelCase = -1				,						UpperCAmelCase = False				,						UpperCAmelCase = None				,						UpperCAmelCase = 3				,						UpperCAmelCase = 4_0				,						UpperCAmelCase = 4_0				,						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





import warnings

from ..trainer import Trainer
from ..utils import logging


lowerCamelCase_    :		Union[str, Any]							=	logging.get_logger(__name__)


class 						a__							(       __snake_case		):



			def __init__(						self				,						UpperCAmelCase=None				,						**UpperCAmelCase   )			->   Any:
								warnings.warn(
								    '`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` '
								    'instead.'				,						UpperCAmelCase				,						)
								super().__init__(args=UpperCAmelCase				,						**UpperCAmelCase   )




