Upsample¶
- class
dragon.vm.torch.nn.
Upsample
(
size=None,
scale_factor=None,
mode='nearest',
align_corners=False
)[source]¶ Upsample input via interpolating neighborhoods.
Set
size
orscale_factor
to determine the output size:The interpolating method can be set by
mode
:See also
__init__¶
Upsample.
__init__
(
size=None,
scale_factor=None,
mode='nearest',
align_corners=False
)[source]¶Create an
Upsample
module.- Parameters:
- size (Union[int, Sequence[int]], optional) – The output size.
- scale_factor (Union[number, Sequence[number]], optional) – The scale factor along each input dimension.
- mode (str, optional, default='nearest') –
'nearest'
or'linear'
. - align_corners (bool, optional, default=False) – Whether to align corners in
'linear'
interpolating.