Method __init__

k_diffusion/layers.py:423–426

(self, in_features, out_features, std=1.)

class FourierFeatures(nn.Module):
    def __init__(self, in_features, out_features, std=1.):
        super().__init__()
        assert out_features % 2 == 0
        self.register_buffer('weight', torch.randn([out_features // 2, in_features]) * std)

    def forward(self, input):
        f = 2 * math.pi * input @ self.weight.T