d7bd8bca1dd54a8255afffb462b84c8b9c3b7eca,torch_geometric/nn/functional/spline_gcn/edgewise_spline_weighting_cpu.py,_EdgewiseSplineGcn,backward,#_EdgewiseSplineGcn#Any#,33

Before Change

        features_grad_in = torch.zeros(n, M_in).type_as(features_in)
        weight_grad_in = torch.zeros(weight.size()).type_as(weight)

        for k in range(self.m**self.dim):
            b = self.amount[:, k]  // [|E|]
            c = self.index[:, k]  // [|E|]
            c_expand = c.contiguous().view(-1, 1).expand(c.size(0), M_out)

After Change

        k_max = self.amount.size(1)
        num_edges = input.size(0)

        grad_input = grad_output.new(num_edges, M_in).fill_(0)
        grad_weight = grad_output.new(K, M_in, M_out).fill_(0)

        for k in range(k_max):
            b = self.amount[:, k]  // [|E|]

Instances