Fix to make compatible with MarginRankingCriterion #108
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Currently ModuleFromCriterion assumes that gradPrediction line 26 is a tensor. This assumption break for criterions like MarginRankingCriterion where it is a table instead. Adding code to make it compatible for criterions where prediction (as well as gradPrediction) can be a table.
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Not sure why the build fails on LUA52 .. :( |
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It still works, on others. Anyone? |
| self.gradInput[1]:resizeAs(gradPrediction):copy(gradPrediction):mul(gradOutput[1]) | ||
| if type(gradPrediction) == 'table' then | ||
| if type(self.gradInput[1]) ~= 'table' then | ||
| self.gradInput[1] = gradPrediction |
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in this case, aren't you forgetting to multiply by gradOutput[1]?
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@soumith - Thanks for pointing out. Fixed it now. Hopefully this time around, it is correct.
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The Lua 5.2 fails weren't your fault, I fixed them in trunk. Made an in-line comment for this PR. |
| if type(self.gradInput[1]) ~= 'table' then | ||
| self.gradInput[1] = {} -- initializing to table first time if it is tensor (which it is: line 10) | ||
| for i=1, #gradPrediction do | ||
| self.gradInput[1][i] = gradPrediction[i]:clone() -- and putting tensors of right size inside. |
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the clone is wasteful here. you just need:
self.gradInput[1][i] = gradPrediction[i].new()
below, you resize the tensor and copy the contents over.
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@soumith - I agree. Changed it now as per your suggestion.
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Thanks Abhi! |
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Before the fix ModuleFromCriterion assumes that gradPrediction (line 26) is a tensor. This assumption breaks for criterions like MarginRankingCriterion where it is a table instead. Adding code to make it compatible for criterions where prediction (as well as gradPrediction) can be a table.