class_docstr: Residual block (a) in the paper
class_docstr_tok: ["Residual","block","(","a",")","in","the","paper"]
code: def forward(self, x):  # x: [batch_size, seq_len, embed_size]
      out = F.relu(self.ln1(x))
      out = out.permute(0, 2, 1).unsqueeze(2)
      out = self.conv1(out).squeeze(2).permute(0, 2, 1)
  
      out2 = F.relu(self.ln2(out))
      out2 = self.conv_pad(out2, self.dilation)
      out2 = self.conv2(out2).squeeze(2).permute(0, 2, 1)
  
      out3 = F.relu(self.ln3(out2))
      out3 = out3.permute(0, 2, 1).unsqueeze(2)
      out3 = self.conv3(out3).squeeze(2).permute(0, 2, 1)
      return out3 + x
  
imports: import numpy
  import torch
  from torch import nn
  from torch.nn import functional
  from torch.nn.init import uniform_, xavier_normal_, constant_
  from recbole.model.abstract_recommender import SequentialRecommender
  from recbole.model.loss import RegLoss, BPRLoss
label_desc: Use image node_id 2 for calling the ResidualBlock_a obj's underlying member method code with example usage: obj.forward(x) and returns: unknown