Lightning 1.6: Habana Accelerator, Bagua Distributed, Fault-Tolerance Improvements

PyTorch Lightning 1.6 was released with contributions from 99 developers across more than 750 commits, adding hardware support, distributed-training improvements, and reliability updates. The release introduces compatibility with Intel’s Habana framework and Gaudi AI processors through the HPU accelerator setting, enabling both single-device and distributed training workloads. It also adds the Bagua strategy, which provides advanced distributed training algorithms and may outperform standard PyTorch Distributed Data Parallel training. In addition, Lightning continues stabilizing its core Accelerator, Strategy, and Plugin APIs, including renaming TrainingTypePlugin to Strategy to better reflect its broader role; this change primarily affects users with custom accelerator, strategy, or plugin implementations.

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