TabularForecaster¶
- class flash.tabular.forecasting.model.TabularForecaster(parameters, backbone, backbone_kwargs=None, loss_fn=None, optimizer='Adam', lr_scheduler=None, metrics=None, learning_rate=None)[source]¶
- classmethod available_finetuning_strategies(cls)¶
Returns a list containing the keys of the available Finetuning Strategies.
- classmethod available_lr_schedulers(cls)¶
Returns a list containing the keys of the available LR schedulers.
- classmethod available_optimizers(cls)¶
Returns a list containing the keys of the available Optimizers.
- classmethod available_outputs(cls)¶
Returns the list of available outputs (that can be used during prediction or serving) for this
Task
.Examples
..testsetup:
>>> from flash import Task
>>> print(Task.available_outputs()) ['preds', 'raw']
- property pytorch_forecasting_model: pytorch_lightning.LightningModule¶
This property provides access to the
LightningModule
object that is wrapped by Flash for backbones provided by PyTorch Forecasting.This can be used with
convert_predictions()
to access the visualization features built in to PyTorch Forecasting.- Return type
LightningModule