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 |