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Implement hinge_embedding_loss as a native function.#5080

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gchanan merged 1 commit into
pytorch:masterfrom
gchanan:hinge_embedding3
Feb 6, 2018
Merged

Implement hinge_embedding_loss as a native function.#5080
gchanan merged 1 commit into
pytorch:masterfrom
gchanan:hinge_embedding3

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@gchanan gchanan commented Feb 6, 2018

Hinge embedding currently fails nn tests when WITH_SCALARS is enabled due to some python function implementation details (that should go away soon when variable and tensor are merged). In addition, this is simpler and faster.

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gchanan commented Feb 6, 2018

Here's some cuda float benchmarks I ran on size (3,224,224) inputs X 5000 times.

forward (original) [0.9593739309348166, 0.9427497601136565, 0.941170543897897]
backward (original) [1.0326906968839467, 1.0211834060028195, 0.9418218401260674]
double backward (original) [1.9777256692759693, 2.0245397542603314, 1.9404461211524904]

forward (new C++) [0.8017345448024571, 0.7572555402293801, 0.7593198330141604]
backward (new C++) [0.8029062300920486, 0.8118076100945473, 0.8187787951901555]
double backward (new C++) [0.8795343148522079, 0.8794920057989657, 0.8756329459138215]

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