INNER CODE UNIT · Python

result

yashbhalgat/HashNeRF-pytorch · hash_encoding.py:121

        result = torch.empty((*input.shape[:-1], self.out_dim), dtype=input.dtype, device=input.device)
        x, y, z = input.unbind(-1)

        result[..., 0] = self.C0
        if self.degree > 1:
            result[..., 1] = -self.C1 * y
            result[..., 2] = self.C1 * z
            result[..., 3] = -self.C1 * x
            if self.degree > 2:
                xx, yy, zz = x * x, y * y, z * z
                xy, yz, xz = x * y, y * z, x * z
                result[..., 4] = self.C2[0] * xy
                result[..., 5] = self.C2[1] * yz
                result[..., 6] = self.C2[2] * (2.0 * zz - xx - yy)
                #result[..., 6] = self.C2[2] * (3.0 * zz - 1) # xx + yy + zz == 1, but this will lead to different backward gradients, interesting...
                result[..., 7] = self.C2[3] * xz
                result[..., 8] = self.C2[4] * (xx - yy)
                if self.degree > 3:

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