lightning
https://github.com/lightning-ai/lightning
Python
Deep learning framework to train, deploy, and ship AI products Lightning fast.
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- Issues
- Using the MLflow logger produces Inconsistent metric plots
- Possible bug in recognizing `mps` accelerator even though PyTorch seems to register the `mps` device?
- Error loading a saved model to run inference (using ddp_notebook strategy)
- Resume training, how to change learning scheduler?
- Added some more potentially robust ways to do learning rate tuning
- Support get optimizer and lr_schedulers from deepspeed config
- RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [68]] is at version 3; expected version 2 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True).
- When doing tuner.scale_batch_size, check full dataset length first
- Log `TensorBoard` histograms
- `ckpt_path` in `Trainer` accepts URIs to automatically load checkpoints from remote paths
- Docs
- Python not yet supported