upsample_bilinear¶

dragon.vm.torch.nn.functional.upsample_bilinear(
  input,
  size=None,
  scale_factor=None
)[source]¶

Upsample input via bilinear interpolating.

Examples:

x = torch.ones((1, 2, 3, 4))
y = F.upsample_bilinear(x, size=6)  # Shape: (1, 2, 6, 6)
z = F.upsample_bilinear(x, scale_factor=2)  # Shape: (1, 2, 6, 8)

Parameters:

• input (dragon.vm.torch.Tensor) – The input tensor.
• size (Union[int, Sequence[int]], optional) – The output size.
• scale_factor (Union[number, Sequence[number]], optional) – The scale factor along each input dimension.

Returns:

dragon.vm.torch.Tensor – The output tensor.

See also

torch.nn.UpsamplingBilinear2d(…)