code: def __init__(
      self, in_channels_x, in_channels_e, middle_channels, out_channels
  ):
      super(DecoderBlockV7, self).__init__()
      self.in_channels = in_channels_x + in_channels_e
      self.conv1 = ConvBn2d(self.in_channels, middle_channels)
      self.conv2 = ConvBn2d(middle_channels, out_channels)
      self.deconv = nn.ConvTranspose2d(
          in_channels_x,
          in_channels_x,
          kernel_size=4,
          stride=2,
          padding=1,
      )
      self.bn = nn.BatchNorm2d(self.in_channels)
      self.spatial_gate = SpatialAttentionGate(out_channels)
      self.channel_gate = ChannelAttentionGate(out_channels)
  
imports: from torch import nn
  from torch.nn import functional
  import torch
  from torchvision import models
  from torchvision.models import resnet34, resnet101, resnet50, resnet152
  import torchvision
label_desc: Use image node_id 1 to create a new DecoderBlockV7 object from inherited base classes: nn with example: obj = DecoderBlockV7(in_channels_x, in_channels_e, middle_channels, out_channels)