code: def forward(self, x, conditioner, diffusion_step):
      diffusion_step = self.diffusion_projection(
          diffusion_step
      ).unsqueeze(-1)
      conditioner = self.conditioner_projection(conditioner)
  
      y = x + diffusion_step
      y = self.dilated_conv(y) + conditioner
  
      gate, filter = torch.chunk(y, 2, dim=1)
      y = torch.sigmoid(gate) * torch.tanh(filter)
  
      y = self.output_projection(y)
      y = F.leaky_relu(y, 0.4)
      residual, skip = torch.chunk(y, 2, dim=1)
      return (x + residual) / math.sqrt(2.0), skip
  
imports: import math
  import torch
  from torch import nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the ResidualBlock obj's underlying member method code with example usage: obj.forward(x, conditioner, diffusion_step) and returns: unknown,  skip