class_docstr: Residual block (b) in the paper
class_docstr_tok: ["Residual","block","(","b",")","in","the","paper"]
code: def forward(self, x):  # x: [batch_size, seq_len, embed_size]
      x_pad = self.conv_pad(
          x, self.dilation
      )  # [batch_size, embed_size, 1, seq_len+(self.kernel_size-1)*dilations]
      out = self.conv1(x_pad).squeeze(2).permute(0, 2, 1)
      # [batch_size, seq_len+(self.kernel_size-1)*dilations-kernel_size+1, embed_size]
      out = F.relu(self.ln1(out))
      out_pad = self.conv_pad(out, self.dilation * 2)
      out2 = self.conv2(out_pad).squeeze(2).permute(0, 2, 1)
      out2 = F.relu(self.ln2(out2))
      return out2 + 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_b obj's underlying member method code with example usage: obj.forward(x) and returns: unknown