放大2倍插值运算代码:
def interpolate(raw_tensor):
'''
等效于F.interpolate(source, scale_factor=scale, mode="nearest")
:param raw_tensor: (B, C, H, W)
:return: (B, C, 2 * H, 2 * W)
'''
b, c, h, w = raw_tensor.shape
out = torch.zeros((b, c, h * 2, w * 2))
out[..., 0::2, 0::2] = raw_tensor[..., 0::1, 0::1]
out[..., 0::2, 1::2] = raw_tensor[..., 0::1, 0::1]
out[..., 1::2, 0::2] = raw_tensor[..., 0::1, 0::1]
out[..., 1::2, 1::2] = raw_tensor[..., 0::1, 0::1]
out[..., 2::2, 0::2] = raw_tensor[..., 1::1, 0::1]
out[..., 2::2, 1::2] = raw_tensor[..., 1::1, 0::1]
out[..., 3::2, 0::2] = raw_tensor[..., 1::1, 0::1]
out[..., 3::2, 1::2] = raw_tensor[..., 1::1, 0::1]
return out
缩小2倍插值运算方法:
def de_interpolate(raw_tensor):
"""
F.interpolate(source, scale_factor=scale, mode="nearest")的逆操作!
:param raw_tensor: [B, C, H, W]
:return: [B, C, H // 2, W // 2]
"""
out = raw_tensor[:, :, 0::2, 0::2]
return out