pytorch-lightning
https://github.com/pytorchlightning/pytorch-lightning
Python
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
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- Issues
- DDP with Hydra multirun doesn't work when dirpath in checkpoint callback is specified
- Logging a TorchMetric resets it, produces very subtle and unexpected behaviour
- Adopt PEP 563, PEP 585, and PEP 604
- Add "interval": "validation" to scheduler configuration
- Use the Callback state_key to disambiguate callbacks provided to trainer and from LightningModule
- WandbLogger does not log checkpoints from multiple ModelCheckpoint callbacks, but only from last one
- LightningModule self.log add_dataloader_idx doesn't reduce properly the metric across dataloaders
- Refactor trainer._log_device_info() method and warnings
- Integrate Intel Neural Compressor tool to quantize fp32 model
- Trainer validates `gradient_clip_algorithm` although `configure_gradient_clipping` is defined
- Docs
- Python not yet supported