Hi! I’m using a model with 2 GATConv layer followed by a FC layer for binary graph classification.
For a batch size of 1:
- Shape of input features is [86,11] (86 nodes and 11 features)
- Shape of features after 1st GATConv: [86, 5, 64] which is flattened to [86, 320] (86 nodes, 5 heads, 64 is hidden dim)
3.Similarly, shape of features from last GATConv is [86, 64].
- Output of FC is coming as [86, 1]
So as expected, the shape of my label is 
As i am using CELoss, I don’t face an error while computing the loss, but this loss calculation is prone to error right?
Shouldn’t the output of the last layer be of shape  too?