pytorch 简单的tensor插值放大和缩小运算

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