INNER CODE UNIT · Python

c00

yashbhalgat/HashNeRF-pytorch · hash_encoding.py:44

        c00 = voxel_embedds[:,0]*(1-weights[:,0][:,None]) + voxel_embedds[:,4]*weights[:,0][:,None]
        c01 = voxel_embedds[:,1]*(1-weights[:,0][:,None]) + voxel_embedds[:,5]*weights[:,0][:,None]
        c10 = voxel_embedds[:,2]*(1-weights[:,0][:,None]) + voxel_embedds[:,6]*weights[:,0][:,None]
        c11 = voxel_embedds[:,3]*(1-weights[:,0][:,None]) + voxel_embedds[:,7]*weights[:,0][:,None]

        # step 2
        c0 = c00*(1-weights[:,1][:,None]) + c10*weights[:,1][:,None]
        c1 = c01*(1-weights[:,1][:,None]) + c11*weights[:,1][:,None]

        # step 3
        c = c0*(1-weights[:,2][:,None]) + c1*weights[:,2][:,None]

        return c

    def forward(self, x):
        # x is 3D point position: B x 3
        x_embedded_all = []
        for i in range(self.n_levels):

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