requires grad for the network
I really should have done the tests
@@ -92,7 +92,7 @@ class SolidHarmonicsNN(nn.Module):
def __init__(self, max_degree=4):
super(SolidHarmonicsNN, self).__init__()
self.output_shape = ((max_degree + 1) ** 2,)
- self.weights = torch.rand(self.output_shape)
+ self.weights = torch.rand(self.output_shape).requires_grad_(True)
powers = [
l
for l in range(max_degree + 1)
