code: def __init__(self, in_channels, cond_channels, downsample_factor):
      super(GBlock, self).__init__()
  
      self.in_channels = in_channels
      self.cond_channels = cond_channels
      self.downsample_factor = downsample_factor
  
      self.start = nn.Sequential(
          nn.AvgPool1d(downsample_factor, stride=downsample_factor),
          nn.ReLU(),
          nn.Conv1d(
              in_channels, in_channels * 2, kernel_size=3, padding=1
          ),
      )
      self.lc_conv1d = nn.Conv1d(
          cond_channels, in_channels * 2, kernel_size=1
      )
      self.end = nn.Sequential(
          nn.ReLU(),
          nn.Conv1d(
              in_channels * 2,
              in_channels * 2,
              kernel_size=3,
              dilation=2,
              padding=2,
          ),
      )
      self.residual = nn.Sequential(
          nn.Conv1d(in_channels, in_channels * 2, kernel_size=1),
          nn.AvgPool1d(downsample_factor, stride=downsample_factor),
      )
  
imports: import numpy
  from torch import nn
label_desc: Use image node_id 1 to create a new GBlock object from inherited base classes: nn with example: obj = GBlock(in_channels, cond_channels, downsample_factor)