





'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase__		:     List[Any]			=							logging.get_logger(__name__)

lowercase__		:     List[Any]			=							{
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}
class 							__lowerCAmelCase	(       _lowerCamelCase					):






       """simple docstring"""
       _snake_case      :	int									=       'roberta-prelayernorm'





       def __init__(				self  :						str			,					lowerCAmelCase__  :						Union[str, Any]=50265			,					lowerCAmelCase__  :						List[Any]=768			,					lowerCAmelCase__  :						Any=12			,					lowerCAmelCase__  :						str=12			,					lowerCAmelCase__  :						List[str]=3072			,					lowerCAmelCase__  :						List[Any]="gelu"			,					lowerCAmelCase__  :						Optional[Any]=0.1			,					lowerCAmelCase__  :						List[Any]=0.1			,					lowerCAmelCase__  :						Union[str, Any]=512			,					lowerCAmelCase__  :						Any=2			,					lowerCAmelCase__  :						List[Any]=0.02			,					lowerCAmelCase__  :						Any=1e-1_2			,					lowerCAmelCase__  :						Optional[int]=1			,					lowerCAmelCase__  :						List[str]=0			,					lowerCAmelCase__  :						int=2			,					lowerCAmelCase__  :						List[str]="absolute"			,					lowerCAmelCase__  :						List[str]=True			,					lowerCAmelCase__  :						Any=None			,					**lowerCAmelCase__  :						str			,					)       ->	Tuple:

            '''simple docstring'''




            super().__init__(pad_token_id=__UpperCamelCase			,					bos_token_id=__UpperCamelCase			,					eos_token_id=__UpperCamelCase			,					**__UpperCamelCase	)

            _UpperCamelCase							       =			vocab_size
            _UpperCamelCase							       =			hidden_size
            _UpperCamelCase							       =			num_hidden_layers
            _UpperCamelCase							       =			num_attention_heads
            _UpperCamelCase							       =			hidden_act
            _UpperCamelCase							       =			intermediate_size
            _UpperCamelCase							       =			hidden_dropout_prob
            _UpperCamelCase							       =			attention_probs_dropout_prob
            _UpperCamelCase							       =			max_position_embeddings
            _UpperCamelCase							       =			type_vocab_size
            _UpperCamelCase							       =			initializer_range
            _UpperCamelCase							       =			layer_norm_eps
            _UpperCamelCase							       =			position_embedding_type
            _UpperCamelCase							       =			use_cache
            _UpperCamelCase							       =			classifier_dropout

class 							__lowerCAmelCase	(       _lowerCamelCase					):






       """simple docstring"""





       @property
       def snake_case__		(				self  :						str	)       ->	Mapping[str, Mapping[int, str]]:

            '''simple docstring'''




            if self.task == "multiple-choice":
                 _UpperCamelCase							       =			{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
            else:
                 _UpperCamelCase							       =			{0: '''batch''', 1: '''sequence'''}
            return OrderedDict(
                [
                    ('''input_ids''', dynamic_axis),
                    ('''attention_mask''', dynamic_axis),
                ]	)








from collections.abc import Callable

import numpy as np






def  lowerCamelCase_	(      lowerCAmelCase__	:	Callable			,	lowerCAmelCase__	:	float			,	lowerCAmelCase__	:	float			,	lowerCAmelCase__	:	float			,	lowerCAmelCase__	:	float				)       ->							np.array:

							'''simple docstring'''






							A      						=    int(np.ceil((x_end - xa) / step_size				)				)
							A      						=    np.zeros((n + 1,)				)
							A      						=    ya
							A      						=    xa

							for k in range(lowerCAmelCase__				):
														A      						=    y[k] + step_size * ode_func(lowerCAmelCase__			,	y[k]				)
														A      						=    y[k] + (
														    (step_size / 2) * (ode_func(lowerCAmelCase__			,	y[k]				) + ode_func(x + step_size			,	lowerCAmelCase__				))
														)
														x += step_size

							return y


if __name__ == "__main__":
				import doctest

				doctest.testmod()