That might be the case, but it’s hard to tell without seeing the actual architecture and forward pass.
The error is raised, if you try to push an input of [4096, 1] to a linear layer, which accepts 4096 input features:
x = torch.randn(4096, 1)
lin = nn.Linear(4096, 11)

out = lin(x)
# RuntimeError: size mismatch, m1: [4096 x 1], m2: [4096 x 11]