class_docstr: A position-wise feed forward module.
  
  Projects to a higher-dimensional space before applying ReLU, then projects
  back.
class_docstr_tok: ["A","position-wise","feed","forward","module",".","Projects","to","a","higher-dimensional","space","before","applying","ReLU",",","then","projects","back","."]
code: def forward(self, x, batch_idxs):
      residual = x
  
      output = self.w_1(x)
      output = self.relu_dropout(self.relu(output), batch_idxs)
      output = self.w_2(output)
  
      output = self.residual_dropout(output, batch_idxs)
      return self.layer_norm(output + residual)
  
imports: import numpy
  import functools
  import sys
  import torch
  from torch.autograd import Variable
  import torch.nn
  import torch.nn.init
label_desc: Use image node_id 2 for calling the PositionwiseFeedForward obj's underlying member method code with example usage: obj.forward(x, batch_idxs) and returns: self