class_docstr: Locality-aware feedforward layer in SATRN, see `SATRN.
  
  <https://arxiv.org/abs/1910.04396>`_
  
  Args:
      d_in (int): Dimension of the input features.
      d_hid (int): Hidden dimension of feedforward layers.
      init_cfg (dict or list[dict], optional): Initialization configs.
          Defaults to [dict(type='Xavier', layer='Conv2d'),
          dict(type='Constant', layer='BatchNorm2d', val=1, bias=0)].
docstr: Forward propagation of Locality Aware Feedforward module.
  
  Args:
      x (Tensor): Feature tensor.
  
  Returns:
      Tensor: Feature tensor after Locality Aware Feedforward.
docstr_tok: ["Forward","propagation","of","Locality","Aware","Feedforward","module",".","Args",":","x","(","Tensor",")",":","Feature","tensor",".","Returns",":","Tensor",":","Feature","tensor","after","Locality","Aware","Feedforward","."]
code: def forward(self, x: Tensor) -> Tensor:
      """Forward propagation of Locality Aware Feedforward module.
  
      Args:
          x (Tensor): Feature tensor.
  
      Returns:
          Tensor: Feature tensor after Locality Aware Feedforward.
      """
      x = self.conv1(x)
      x = self.depthwise_conv(x)
      x = self.conv2(x)
      return x
  
imports: from typing import Dict, List, Optional, Union
  import numpy
  import torch
  import torch.nn
  from mmcv.cnn import ConvModule
  from mmengine.model import BaseModule
  from torch import Tensor
  from mmocr.models.common import MultiHeadAttention
label_desc: Use image node_id 2 for calling the LocalityAwareFeedforward obj's underlying member method code with example usage: obj.forward(x) and returns: x