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* initial multitensor jit support and tests * Added graphs to multitensor jit and updated tests * update unbind api * fix set device, add TinyJit to resnet * update_stats includes device --------- Co-authored-by: ramenguy99 <ramenguy99@gmail.com>
Each model should be a clean single file. They are imported from the top level `models` directory It should be capable of loading weights from the reference imp. We will focus on these 5 models: # Resnet50-v1.5 (classic) -- 8.2 GOPS/input # Retinanet # 3D UNET (upconvs) # RNNT # BERT-large (transformer) They are used in both the training and inference benchmark: https://mlcommons.org/en/training-normal-21/ https://mlcommons.org/en/inference-edge-30/ And we will submit to both. NOTE: we are Edge since we don't have ECC RAM