what is the principle of the deconvolution with bilinear interpolation kernel？

[fengliguantou24]

The code that I find in a website，but i dont know the principle。the code use this bilinear interpolation kernel to deconvolute。

code:
def bilinear_kernel(in_channels, out_channels, kernel_size):
"""Define a bilinear kernel according to in channels and out channels.
Returns:
return a bilinear filter tensor
"""
factor = (kernel_size + 1) // 2 #
if kernel_size % 2 == 1:
center = factor - 1
else:
center = factor - 0.5
og = np.ogrid[:kernel_size, :kernel_size]
bilinear_filter = (1 - abs(og[0] - center) / factor) * (1 - abs(og[1] - center) / factor)
weight = np.zeros((in_channels, out_channels, kernel_size, kernel_size), dtype=np.float32)
weight[range(in_channels), range(out_channels), :, :] = bilinear_filter
return torch.from_numpy(weight)