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View Code? Open in Web Editor NEWAIBench, a tool for comparing and evaluating AI serving solutions. forked from [tsbs](https://github.com/timescale/tsbs) and adapted to AI serving use case
License: MIT License
AIBench, a tool for comparing and evaluating AI serving solutions. forked from [tsbs](https://github.com/timescale/tsbs) and adapted to AI serving use case
License: MIT License
Each runner struct that is of inference.Processor
type should implement a common CollectRunTimeMetrics()
method that will asks the specific runner to fetch (opt-in) runtime stats that will then be stored on the results file.
Return data should include the collection timestamp and an interface with all fetched data.
Given the different backends dimension order, we should be able to prepare the tensors on HxWxC formatting or CxHxW formatting.
Models to be assessed:
Modify/fork https://github.com/NVIDIA-AI-IOT/jetson_benchmarks and execute on RedisAI for supported framework
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