training_policies
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mlcommons
Evaluation bottle necks
Sometimes evaluation can be very time consuming and done by 3rd party code. How can we reduce the influence of 3rd party evaluation code performance on the benchmark scores and engineering burden?
SWG Notes:
Possible solutions (brain storming, have many pros/cons):
- Not time evaluation
- Fewer evaluation
- Provide/choose optimized implementations for evaluation
- Let submitters figure out how to handle it
AI(Jacob) - Present thoughts from HPC on this next week. AI(all submitters) - This is a call for proposal :)
Can someone provide an example of a benchmark where third-party code is used for serial evaluation and becomes a bottleneck?
I've run into this issue with the translation and image-classification benchmarks, but haven't made it far enough along in porting of the other benchmarks to know which ones are most problematic.
SWG Notes:
We believe Maskrcnn and SSD with coco evaluation is at the top of the list.
SWG Notes:
Long term we'd like a unified solution to this, but for v0.6 it will be up to submitters to optimization evaluation code themselves if they deem it necessary. We intend to revisit this issue in the future to reduce effort submitters have to put into evaluation.
