| accelerator | Create an accelerator |
| as_dataloader | Creates a dataloader from its input |
| as_dataloader.array | Creates a dataloader from its input |
| as_dataloader.dataloader | Creates a dataloader from its input |
| as_dataloader.dataset | Creates a dataloader from its input |
| as_dataloader.list | Creates a dataloader from its input |
| as_dataloader.matrix | Creates a dataloader from its input |
| as_dataloader.numeric | Creates a dataloader from its input |
| as_dataloader.torch_tensor | Creates a dataloader from its input |
| context | Context object |
| ctx | Context object |
| evaluate | Evaluates a fitted model on a dataset |
| fit.luz_module_generator | Fit a 'nn_module' |
| get_metrics | Get metrics from the object |
| get_metrics.luz_module_fitted | Get metrics from the object |
| lr_finder | Learning Rate Finder |
| luz_callback | Create a new callback |
| luz_callback_auto_resume | Resume training callback |
| luz_callback_csv_logger | CSV logger callback |
| luz_callback_early_stopping | Early stopping callback |
| luz_callback_gradient_clip | Gradient clipping callback |
| luz_callback_interrupt | Interrupt callback |
| luz_callback_keep_best_model | Keep the best model |
| luz_callback_lr_scheduler | Learning rate scheduler callback |
| luz_callback_metrics | Metrics callback |
| luz_callback_mixup | Mixup callback |
| luz_callback_model_checkpoint | Checkpoints model weights |
| luz_callback_profile | Profile callback |
| luz_callback_progress | Progress callback |
| luz_callback_resume_from_checkpoint | Allow resume model training from a specific checkpoint |
| luz_callback_tfevents | tfevents callback |
| luz_callback_train_valid | Train-eval callback |
| luz_load | Load trained model |
| luz_load_checkpoint | Loads a checkpoint |
| luz_load_model_weights | Loads model weights into a fitted object. |
| luz_metric | Creates a new luz metric |
| luz_metric_accuracy | Accuracy |
| luz_metric_binary_accuracy | Binary accuracy |
| luz_metric_binary_accuracy_with_logits | Binary accuracy with logits |
| luz_metric_binary_auroc | Computes the area under the ROC |
| luz_metric_mae | Mean absolute error |
| luz_metric_mse | Mean squared error |
| luz_metric_multiclass_auroc | Computes the multi-class AUROC |
| luz_metric_rmse | Root mean squared error |
| luz_metric_set | Creates a metric set |
| luz_save | Saves luz objects to disk |
| luz_save_model_weights | Loads model weights into a fitted object. |
| nnf_mixup | Mixup logic |
| nn_mixup_loss | Loss to be used with 'callbacks_mixup()'. |
| predict.luz_module_fitted | Create predictions for a fitted model |
| setup | Set's up a 'nn_module' to use with luz |
| set_hparams | Set hyper-parameter of a module |
| set_opt_hparams | Set optimizer hyper-parameters |