-
Notifications
You must be signed in to change notification settings - Fork 0
/
MultiCriterion.lua
40 lines (35 loc) · 1.19 KB
/
MultiCriterion.lua
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
local MultiCriterion, parent = torch.class('nn.MultiCriterion', 'nn.Criterion')
function MultiCriterion:__init()
parent.__init(self)
self.criterions = {}
self.weights = torch.DoubleStorage()
end
function MultiCriterion:add(criterion, weight)
assert(criterion, 'no criterion provided')
weight = weight or 1
table.insert(self.criterions, criterion)
self.weights:resize(#self.criterions, true)
self.weights[#self.criterions] = weight
return self
end
function MultiCriterion:updateOutput(input, target)
self.output = 0
for i=1,#self.criterions do
self.output = self.output + self.weights[i]*self.criterions[i]:updateOutput(input, target)
end
return self.output
end
function MultiCriterion:updateGradInput(input, target)
self.gradInput = nn.utils.recursiveResizeAs(self.gradInput, input)
nn.utils.recursiveFill(self.gradInput, 0)
for i=1,#self.criterions do
nn.utils.recursiveAdd(self.gradInput, self.weights[i], self.criterions[i]:updateGradInput(input, target))
end
return self.gradInput
end
function MultiCriterion:type(type)
for i,criterion in ipairs(self.criterions) do
criterion:type(type)
end
return parent.type(self, type)
end