






from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin


class     _a							(	UpperCAmelCase__    ,							UpperCAmelCase__     ):






  """simple docstring"""





  @register_to_config
  def __init__(  self		,		_UpperCAmelCase = 768		,		)      ->			Dict:
     super().__init__()

     UpperCamelCase_						=  nn.Parameter(torch.zeros(1		,		_UpperCAmelCase			)			)
     UpperCamelCase_						=  nn.Parameter(torch.ones(1		,		_UpperCAmelCase			)			)




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase = None		,		_UpperCAmelCase = None		,		)      ->			List[Any]:
     UpperCamelCase_						=  nn.Parameter(self.mean.to(_UpperCAmelCase			).to(_UpperCAmelCase			)			)
     UpperCamelCase_						=  nn.Parameter(self.std.to(_UpperCAmelCase			).to(_UpperCAmelCase			)			)
     return self




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			Dict:
     UpperCamelCase_						=  (embeds - self.mean) * 1.0 / self.std
     return embeds




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			List[str]:
     UpperCamelCase_						=  (embeds * self.std) + self.mean
     return embeds









from ...configuration_utils import PretrainedConfig
from ...utils import logging


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

UpperCAmelCase   :    List[Any]     =		{
    "SCUT-DLVCLab/lilt-roberta-en-base": (
        "https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"
    ),
}







class        __lowercase       (							a_  ):



		"""simple docstring"""

		UpperCamelCase     :					List[str]			       =		"lilt"







		def __init__( self		,      A=3_05_22		,      A=7_68		,      A=12		,      A=12		,      A=30_72		,      A="gelu"		,      A=0.1		,      A=0.1		,      A=5_12		,      A=2		,      A=0.02		,      A=1e-1_2		,      A=0		,      A="absolute"		,      A=None		,      A=4		,      A=10_24		,      **A		,      )  -> List[Any]:







					'''simple docstring'''







					super().__init__(pad_token_id=A		,      **A	)

					lowerCamelCase    		=  vocab_size
					lowerCamelCase    		=  hidden_size
					lowerCamelCase    		=  num_hidden_layers
					lowerCamelCase    		=  num_attention_heads
					lowerCamelCase    		=  hidden_act
					lowerCamelCase    		=  intermediate_size
					lowerCamelCase    		=  hidden_dropout_prob
					lowerCamelCase    		=  attention_probs_dropout_prob
					lowerCamelCase    		=  max_position_embeddings
					lowerCamelCase    		=  type_vocab_size
					lowerCamelCase    		=  initializer_range
					lowerCamelCase    		=  layer_norm_eps
					lowerCamelCase    		=  position_embedding_type
					lowerCamelCase    		=  classifier_dropout
					lowerCamelCase    		=  channel_shrink_ratio
					lowerCamelCase    		=  max_ad_position_embeddings

