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local SpatialMaxSampling, parent = torch.class('nn.SpatialMaxSampling', 'nn.Module')
function SpatialMaxSampling:__init(...)
parent.__init(self)
xlua.unpack_class(
self, {...}, 'nn.SpatialMaxSampling',
'resample an image using max selection',
{arg='owidth', type='number', help='output width'},
{arg='oheight', type='number', help='output height'}
)
self.indices = torch.Tensor()
end
function SpatialMaxSampling:updateOutput(input)
input.nn.SpatialMaxSampling_updateOutput(self, input)
return self.output
end
function SpatialMaxSampling:updateGradInput(input, gradOutput)
input.nn.SpatialMaxSampling_updateGradInput(self, input, gradOutput)
return self.gradInput
end
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