Fix reduction functions to respect the stride of the output#4995
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soumith merged 1 commit intopytorch:masterfrom Feb 6, 2018
Merged
Fix reduction functions to respect the stride of the output#4995soumith merged 1 commit intopytorch:masterfrom
soumith merged 1 commit intopytorch:masterfrom
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| dimension + TH_INDEX_BASE); | ||
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| int in_dims = THTensor_(nDimension)(t); | ||
| THTensor_(preserveReduceDimSemantics)(values_, in_dims, dimension, keepdim); |
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…put is correct size (pytorch#4995)
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Fixes #4974
Consider reduction ops like
torch.sum,torch.prod, etc, of the formreduce_op(output, input, keepdim)Let
output_sizebe the size of the output withkeepdim=False, andoutput_keepdim_sizebe the size of the output withkeepdim=True.Right now, what happens in a reduce op is the following:
we have an
inputand anoutput.outputis always resized tooutput_keepdim_size. Then, the reduction op is performed with that size, and output is finally either squeezed tooutput_sizeor kept atoutput_keepdim_sizedepending on whatkeepdimis.The problem with what currently happens is that if
keepdim=Falseandoutputinitially has sizeoutput_sizethenoutputwill be resized tooutput_keepdim_size, the reduce op will be performed, and then output will be squeezed tooutput_size. This resize is not a no-op and will affectoutput's contiguity.This PR fixes the issue by always unsqueezing
outputtooutput_keepdim_size. This operation preservesoutput's contiguity.This fixes the following operations:
Test Plan
New unit tests