1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
|
------------------------------------------------------------------------
--[[ MultiSoftMax ]]--
-- Takes 2D or 3D input and performs a softmax over the last dimension.
------------------------------------------------------------------------
local MultiSoftMax, parent = torch.class('nn.MultiSoftMax', 'nn.Module')
function MultiSoftMax.__init(self)
parent.__init(self)
self._input = torch.Tensor()
self._output = torch.Tensor()
self._gradInput = torch.Tensor()
self._gradOutput = torch.Tensor()
end
function MultiSoftMax:updateOutput(input)
if input:dim() == 2 then
return input.THNN.SoftMax_updateOutput(input:cdata(), self.output:cdata())
end
if input:dim() ~= 3 then
error"Only supports 2D or 3D inputs"
end
self._input:view(input, input:size(1)*input:size(2), input:size(3))
local output = self.output
self.output = self._output
input.THNN.SoftMax_updateOutput(self._input:cdata(), self.output:cdata())
output:viewAs(self.output, input)
self.output = output
return self.output
end
function MultiSoftMax:updateGradInput(input, gradOutput)
if input:dim() == 2 then
return input.THNN.SoftMax_updateGradInput(input:cdata(), gradOutput:cdata(),
self.gradInput:cdata(), self.output:cdata())
end
self._gradOutput:view(gradOutput, input:size(1)*input:size(2), input:size(3))
local gradInput = self.gradInput
self.gradInput = self._gradInput
local output = self.output
self.output = self._output
input.THNN.SoftMax_updateGradInput(self._input:cdata(), self._gradOutput:cdata(),
self.gradInput:cdata(), self.output:cdata())
self.gradInput = gradInput:viewAs(self.gradInput, input)
self.output = output
return self.gradInput
end
|
