This repository has been archived by the owner on Nov 17, 2023. It is now read-only.
Implement remaining nn_activation ops in opperf #17475
Merged
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Description
This PR serves to implement the remaining operators from the nn_activation category in opperf. To achieve this, I refactored the preexisting individual
run_performance_test
calls (for the four operators that had already been implemented) into a single generalized function call torun_op_benchmarks
. I also implemented Softmax, SoftmaxActivation, softmin, and Activation ops, which are also called via therun_op_benchmarks
function.Checklist
Essentials
Please feel free to remove inapplicable items for your PR.
Changes
Comments
Tested on c5.18xl & p2.16xl w/ubuntu 16.04 and Mac OS with:
run_activation_operators_benchmarks
- runs all activation ops on default dataopperf.py
(full run of all ops)