DataModule

class flash.core.data.data_module.DataModule(train_input=None, val_input=None, test_input=None, predict_input=None, data_fetcher=None, val_split=None, batch_size=None, num_workers=0, sampler=None, pin_memory=True, persistent_workers=False)

A basic DataModule class for all Flash tasks. This class includes references to a Input and a BaseDataFetcher.

Parameters

• train_input (Optional[Input]) – Input dataset for training. Defaults to None.

• val_input (Optional[Input]) – Input dataset for validating model performance during training. Defaults to None.

• test_input (Optional[Input]) – Input dataset to test model performance. Defaults to None.

• predict_input (Optional[Input]) – Input dataset for predicting. Defaults to None.

• data_fetcher (Optional[BaseDataFetcher]) – The BaseDataFetcher to attach to the InputTransform. If None, the output from configure_data_fetcher() will be used.

• val_split (Optional[float]) – An optional float which gives the relative amount of the training dataset to use for the validation dataset.

• batch_size (Optional[int]) – The batch size to be used by the DataLoader.

• num_workers (int) – The number of workers to use for parallelized loading.

• sampler (Optional[Type[Sampler]]) – A sampler following the Sampler type. Will be passed to the DataLoader for the training dataset. Defaults to None.

static configure_data_fetcher(*args, **kwargs)

This function is used to configure a BaseDataFetcher.

Override with your custom one.

Return type

BaseDataFetcher

property data_fetcher: flash.core.data.callback.BaseDataFetcher

This property returns the data fetcher.

Return type

BaseDataFetcher

input_transform_cls

alias of flash.core.data.io.input_transform.InputTransform

property inputs: Optional[Union[flash.core.data.io.input.Input, List[flash.core.data.io.input.InputBase]]]

Property that returns the inputs associated with this DataModule.

Return type

Union[Input, List[InputBase], None]

property labels: Optional[int]

Property that returns the labels if this DataModule contains classification data.

Return type

Optional[int]

property multi_label: Optional[bool]

Property that returns True if this DataModule contains multi-label data.

Return type

Optional[bool]

property num_classes: Optional[int]

Property that returns the number of classes of the datamodule if a multiclass task.

Return type

Optional[int]

property predict_dataset: Optional[flash.core.data.io.input.Input]

This property returns the predict dataset.

Return type

Optional[Input]

show_predict_batch(hooks_names='load_sample', reset=True)

This function is used to visualize a batch from the predict dataloader.

Return type

None

show_test_batch(hooks_names='load_sample', reset=True)

This function is used to visualize a batch from the test dataloader.

Return type

None

show_train_batch(hooks_names='load_sample', reset=True)

This function is used to visualize a batch from the train dataloader.

Return type

None

show_val_batch(hooks_names='load_sample', reset=True)

This function is used to visualize a batch from the validation dataloader.

Return type

None

property test_dataset: Optional[flash.core.data.io.input.Input]

This property returns the test dataset.

Return type

Optional[Input]

property train_dataset: Optional[flash.core.data.io.input.Input]

This property returns the train dataset.

Return type

Optional[Input]

property val_dataset: Optional[flash.core.data.io.input.Input]

This property returns the validation dataset.

Return type

Optional[Input]