




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 			a__    (					snake_case__      ):
						_a							:    int					=    """deberta-v2"""






						def __init__(   self		,			_A=1_2_8_1_0_0		,			_A=1_5_3_6		,			_A=2_4		,			_A=2_4		,			_A=6_1_4_4		,			_A="gelu"		,			_A=0.1		,			_A=0.1		,			_A=5_1_2		,			_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			)

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

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

											__lowerCAmelCase				   =       pos_att_type
											__lowerCAmelCase				   =       vocab_size
											__lowerCAmelCase				   =       layer_norm_eps

											__lowerCAmelCase				   =       kwargs.get("pooler_hidden_size"		,			_A			)
											__lowerCAmelCase				   =       pooler_dropout
											__lowerCAmelCase				   =       pooler_hidden_act






class 			a__    (					snake_case__      ):






						@property
						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



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




											"""simple docstring"""



											return 1_2






						def 				__SCREAMING_SNAKE_CASE(   self		,			_A		,			_A = -1		,			_A = -1		,			_A = -1		,			_A = False		,			_A = None		,			_A = 3		,			_A = 4_0		,			_A = 4_0		,			_A = None		,			):




											"""simple docstring"""



											__lowerCAmelCase				   =       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








from __future__ import annotations







def        _lowerCamelCase(	lowercase__	)						->	list[int]:

		'''simple docstring'''







		__lowercase=			2
		__lowercase=			[]
		while i * i <= n:
				if n % i:
						i += 1
				else:
						n //= i
						factors.append(lowercase__	)
		if n > 1:
				factors.append(lowercase__	)
		return factors


if __name__ == "__main__":
	import doctest

	doctest.testmod()






