nn.Upsample(scale_factor=2, mode='nearest')
        >>> m(input)
        tensor([[[[1., 1., 2., 2.],
                  [1., 1., 2., 2.],
                  [3., 3., 4., 4.],
                  [3., 3., 4., 4.]]]])

        >>> # xdoctest: +IGNORE_WANT("other tests seem to modify printing styles")
        >>> m = nn.Upsample(scale_factor=2, mode='bilinear')  # align_corners=False
        >>> m(input)
        tensor([[[[1.0000, 1.2500, 1.7500, 2.0000],
                  [1.5000, 1.7500, 2.2500, 2.5000],
                  [2.5000, 2.7500, 3.2500, 3.5000],
                  [3.0000, 3.2500, 3.7500, 4.0000]]]])

        >>> m = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True)
        >>> m(input)
        tensor([[[[1.0000, 1.3333, 1.6667, 2.0000],
                  [1.6667, 2.0000, 2.3333, 2.6667],
                  [2.3333, 2.6667, 3.0000, 3.3333],
                  [3.0000, 3.3333, 3.6667, 4.0000]]]])

        >>> # Try scaling the same data in a larger tensor
        >>> input_3x3 = torch.zeros(3, 3).view(1, 1, 3, 3)
        >>> input_3x3[:, :, :2, :2].copy_(input)
        tensor([[[[1., 2.],
                  [3., 4.]]]])
        >>> input_3x3
        tensor([[[[1., 2., 0.],
                  [3., 4., 0.],
                  [0., 0., 0.]]]])

        >>> # xdoctest: +IGNORE_WANT("seems to fail when other tests are run in the same session")
        >>> m = nn.Upsample(scale_factor=2, mode='bilinear')  # align_corners=False
        >>> # Notice that values in top left corner are the same with the small input (except at boundary)
        >>> m(input_3x3)
        tensor([[[[1.0000, 1.2500, 1.7500, 1.5000, 0.5000, 0.0000],
                  [1.5000, 1.7500, 2.2500, 1.8750, 0.6250, 0.0000],
                  [2.5000, 2.7500, 3.2500, 2.6250, 0.8750, 0.0000],
                  [2.2500, 2.4375, 2.8125, 2.2500, 0.7500, 0.0000],
                  [0.7500, 0.8125, 0.9375, 0.7500, 0.2500, 0.0000],
                  [0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000]]]])

        >>> m = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True)
        >>> # Notice that values in top left corner are now changed
        >>> m(input_3x3)
        tensor([[[[1.0000, 1.4000, 1.8000, 1.6000, 0.8000, 0.0000],
                  [1.8000, 2.2000, 2.6000, 2.2400, 1.1200, 0.0000],
                  [2.6000, 3.0000, 3.4000, 2.8800, 1.4400, 0.0000],
                  [2.4000, 2.7200, 3.0400, 2.5600, 1.2800, 0.0000],
                  [1.2000, 1.3600, 1.5200, 1.2800, 0.6400, 0.0000],
                  [0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000]]]])
    )