LightningLite enables pure PyTorch users to scale their existing code to any kind of hardware while retaining full control over their own loops and optimization logic. PL_FAULT_TOLERANT_TRAINING=1 python train.py LightningLite With this new experimental feature, you will be able to restore your training mid-epoch on the exact batch and continue training as if it never got interrupted. Once a Lightning experiment unexpectedly exits, a temporary checkpoint is saved that contains the exact state of all loops and the model. This is particularly interesting while training in the cloud with preemptive instances which can shutdown at any time. Fault-tolerant Trainingįault-tolerant Training is a new internal mechanism that enables PyTorch Lightning to recover from a hardware or software failure. With over 60 contributors working on features, bugfixes and documentation improvements, version 1.5 was their biggest release to date. Learn more about Exxact AI workstations starting at $3,700 ![]() Interested in a deep learning workstation?
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