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
- self.log(.., on_epoch=True) runs extremely slow
- Using a non-named parameter for DataLoader initialization results in an error when using a LightningDataModule
- Error when instantiating Logger with **kwargs only arguments via CLI (NeptuneLogger)
- Graceful termination doesn't work when DataLoaders have num_workers > 0
- ModelCheckpoint `every_n_train_steps` and Trainer `accumulate_grad_batches` (kinda) don't make sense
- Automated metric logging in Lightning Trainer
- Interleaved Model for combined_loader
- Add `WandbLogger` callback for customizing checkpoint artifact logging
- Race condition between `AsyncCheckpointIO` and `WandbLogger`
- Periodic checkpoints logged for every epoch to wandb with ModelCheckpoint & WandbLogger
- Docs
- Python not yet supported