PyTorchCon: Meta engineers on predicting big training-run behavior with fewer resources
PyTorch · x · 2026-10-21
The official PyTorch account shares more from Meta engineer Edward Yang at PyTorchCon on predicting big training-run behavior with fewer resources.
His earlier conversation with Alban Desmaison covered simpler hardware integration (torch.accelerator), backend testing, tools to catch problems before expensive training runs, torchremat for activation checkpointing, and FlexShard for separating storage sharding from compute sharding.
Related event: Meta Engineers Unveil Training Stability Tools at PyTorch Conference(3 posts)→
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