@fmassa @apaszke  I guess I am getting very confused here… To my knowledge, my forward_prop member function IS my definition of the forward function in my Net module.… have I misunderstood something here? For completeness, I have pasted my Net class here:
class Net(nn.Module):
 
  def __init__(self):
    super(Net, self).__init__()

    # Define the network
    self.bn1 = nn.BatchNorm2d(8)
    self.bn2 = nn.BatchNorm2d(16)        
    self.conv1 = nn.Conv2d(1, 8, 3, stride = (1,1), padding = (1,1))
    self.conv2 = nn.Conv2d(8, 16, 3, stride = (1,1), padding = (1,1))    
    self.conv3 = nn.Conv2d(16, 32, 2, stride = (1,1), padding = (0,0))
    self.conv4 = nn.Conv2d(32, 64, 3, stride = (1,1), padding = (1,1))
    self.conv5 = nn.Conv2d(64, 64, 3, stride = (3,3), padding = (0,0))
    self.fc1   = nn.Linear(256, 32) 
    self.fc2   = nn.Linear(32, 16)
    self.fc3   = nn.Linear(16, 2)

  def forward_prop(self, x):
    
    # Conv1 with batch norm
    x = F.max_pool2d(F.relu(self.bn1(self.conv1(x))), (2,2))

    # Conv2 with batch norm.
    x = F.max_pool2d(F.relu(self.bn2(self.conv2(x))), (2,2))    

    # Conv3
    x = F.max_pool2d(F.relu(self.conv3(x)), (2,2))    

    # Conv4
    x = F.max_pool2d(F.relu(self.conv4(x)), (2,2))

    # Conv5
    x = F.relu(self.conv5(x))
    
    # Flatten the feature map thus far for use in the fully connected layer.
    x = x.view(-1, self.num_flat_features(x))
        
    # Fully connected 1    
    x = F.relu(self.fc1(x))

    # Fully connected 2    
    x = F.relu(self.fc2(x))

    # Final layer
    x = self.fc3(x)

    return x

  def num_flat_features(self, x):    
    # all dimensions except the batch dimension
    size = x.size()[1:] 
    num_features = 1
    for s in size:
        num_features *= s
    return num_features

So real quick, in the rest of my file, I basically have:
net = Net().cuda()
net.forward_prop(trainingBatch)

Now what I would simply like to do is given this setup, I want to just use the DataParallel setup. I looked at the DCGAN example, however I cannot use it at first glance, because I do not know how to do a reshape-operation in the nn.Sequentual() function, and as far as the image_net example, it is not clear to me what their “model” is, vis-a-vis what I have here.
So instead I wrote a simple net (as above), and would like to use the DataParallel capability here. What would I do differently on this setup as above?
thanks again!