3382a5de41ec450eb8e5adbd57fc4b80633befe5,torchsample/utils.py,,th_bilinear_interp_2d,#Any#Any#,161

Before Change

                    for i in range(input.size(0))],0)
    
    c_u = coords.unsqueeze(0).repeat(input.size(0),1,1)
    clt_u = coords_lt.unsqueeze(0).repeat(input.size(0),,).type(coords.type())
    coords_offset_lt = c_u - clt_u
                       
    vals_t = vals_lt + (vals_rt - vals_lt) * coords_offset_lt[:,:,0]
    vals_b = vals_lb + (vals_rb - vals_lb) * coords_offset_lt[:,:,0]
    mapped_vals = vals_t + (vals_b - vals_t) * coords_offset_lt[:,:,1]

After Change

        coordinates to index the input on
    
    // repeat coords along channel dim if not given that way
    if coords.dim() == 2:
        coords = coords.unsqueeze(0).repeat(input.size(0),1,1)

    xc = torch.clamp(coords[:,:,0], 0, input.size(1)-1)
    yc = torch.clamp(coords[:,:,1], 0, input.size(2)-1)
    coords = torch.stack([xc, yc],2)

Instances