1 6 Regular - Pytorch Lightning

.. list-table:: reg. user 1.6 :widths: 40 40 20 :header-rows: 1

- If
- Then
- Ref
- used Trainer’s flag terminate_on_nan
- set detect_anomaly instead, which enables detecting anomalies in the autograd engine
- PR9175_
- used Trainer’s flag weights_summary
- pass a ModelSummary callback with max_depth instead
- PR9699_
- used Trainer’s flag checkpoint_callback
- set enable_checkpointing. If you set enable_checkpointing=True, it configures a default ModelCheckpoint callback if none is provided lightning.pytorch.trainer.trainer.Trainer.callbacks.ModelCheckpoint
- PR9754_
- used Trainer’s flag stochastic_weight_avg
- add the StochasticWeightAveraging callback directly to the list of callbacks, so for example, Trainer(..., callbacks=[StochasticWeightAveraging(), ...])
- PR8989_
- used Trainer’s flag flush_logs_every_n_steps
- pass it to the logger init if it is supported for the particular logger
- PR9366_
- used Trainer’s flag max_steps to the Trainer, max_steps=None won't have any effect
- turn off the limit by passing Trainer(max_steps=-1) which is the default
- PR9460_
- used Trainer’s flag resume_from_checkpoint="..."
- pass the same path to the fit function instead, trainer.fit(ckpt_path="...")
- PR9693_
- used Trainer’s flag log_gpu_memory, gpu_metrics
- use the DeviceStatsMonitor callback instead
- PR9921_
- used Trainer’s flag progress_bar_refresh_rate
- set the ProgressBar callback and set refresh_rate there, or pass enable_progress_bar=False to disable the progress bar
- PR9616_
- called LightningModule.summarize()
- use the utility function pl.utilities.model_summary.summarize(model)
- PR8513_
- used the LightningModule.model_size property
- use the utility function pl.utilities.memory.get_model_size_mb(model)
- PR8495_
- relied on the on_train_dataloader() hooks in LightningModule and LightningDataModule
- use train_dataloader
- PR9098_
- relied on the on_val_dataloader() hooks in LightningModule and LightningDataModule
- use val_dataloader
- PR9098_
- relied on the on_test_dataloader() hooks in LightningModule and LightningDataModule
- use test_dataloader
- PR9098_
- relied on the on_predict_dataloader() hooks in LightningModule and LightningDataModule
- use predict_dataloader
- PR9098_
- implemented the on_keyboard_interrupt callback hook
- implement the on_exception hook, and specify the exception type
- PR9260_
- relied on the TestTubeLogger
- Use another logger like TensorBoardLogger
- PR9065_
- used the basic progress bar ProgressBar callback
- use the TQDMProgressBar callback instead with the same arguments
- PR10134_
- were using GPUStatsMonitor callbacks
- use DeviceStatsMonitor callback instead
- PR9924_
- were using XLAStatsMonitor callbacks
- use DeviceStatsMonitor callback instead
- PR9924_