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This pull request was exported from Phabricator. Differential Revision: D19739656 |
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Summary: Pull Request resolved: facebookresearch#385 Test Plan: . Differential Revision: D19739656 Pulled By: vreis fbshipit-source-id: 347772745f2811bf2947128a23986161395c526d
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This pull request was exported from Phabricator. Differential Revision: D19739656 |
Summary: This changes ClassificationTask to compute some high-level performance numbers (img/sec) and plot them in Tensorboard. This is useful for comparing performance optimizations since we now get a "blessed" performance number. Also, this was done in a way that's comparable to NVidia's benchmarks (e.g. https://ngc.nvidia.com/catalog/model-scripts/nvidia:resnet_50_v1_5_for_pytorch/performance), so we know how well we're doing compared to other implementations. In terms of implementation, I could have made a hook instead, but decided against it for two reasons: (1) it would introduce dependencies between hooks; (2) we want to control precisely when the timing measurements are taken; Pull Request resolved: facebookresearch#385 Test Plan: ./classy_train.py --config configs/template_config.json Reviewed By: mannatsingh Differential Revision: D19739656 Pulled By: vreis fbshipit-source-id: a63c394308851e6accee9d260d9cb1d972f33a7f
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This changes ClassificationTask to compute some high-level performance
numbers (img/sec) and plot them in Tensorboard. This is useful for comparing
performance optimizations since we now get a "blessed" performance number.
Also, this was done in a way that's comparable to NVidia's benchmarks (e.g. https://ngc.nvidia.com/catalog/model-scripts/nvidia:resnet_50_v1_5_for_pytorch/performance), so we know how well we're doing compared to other implementations.
In terms of implementation, I could have made a hook instead, but decided against it for two reasons: (1) it would introduce dependencies between hooks; (2) we want to control precisely when the timing measurements are taken;