code: def __init__(self, hidden_size, residual_channels, dilation):
      super().__init__()
      self.dilated_conv = nn.Conv1d(
          residual_channels,
          2 * residual_channels,
          3,
          padding=dilation,
          dilation=dilation,
          padding_mode="circular",
      )
      self.diffusion_projection = nn.Linear(
          hidden_size, residual_channels
      )
      self.conditioner_projection = nn.Conv1d(
          1,
          2 * residual_channels,
          1,
          padding=2,
          padding_mode="circular",
      )
      self.output_projection = nn.Conv1d(
          residual_channels, 2 * residual_channels, 1
      )
  
      nn.init.kaiming_normal_(self.conditioner_projection.weight)
      nn.init.kaiming_normal_(self.output_projection.weight)
  
imports: import math
  import torch
  from torch import nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new ResidualBlock object from inherited base classes: nn with example: obj = ResidualBlock(hidden_size, residual_channels, dilation)