snorkel.augmentation.TFApplier

class snorkel.augmentation.TFApplier(tfs, policy)[source]

Bases: snorkel.augmentation.apply.core.BaseTFApplier

TF applier for a list of data points.

Augments a list of data points (e.g. SimpleNamespace). Primarily useful for testing.

__init__(tfs, policy)[source]

Initialize self. See help(type(self)) for accurate signature.

Return type

None

Methods

__init__(tfs, policy)

Initialize self.

apply(data_points[, progress_bar])

Augment a list of data points using TFs and policy.

apply_generator(data_points, batch_size)

Augment a list of data points using TFs and policy in batches.

apply(data_points, progress_bar=True)[source]

Augment a list of data points using TFs and policy.

Parameters
  • data_points (Sequence[Any]) – List containing data points to be transformed

  • progress_bar (bool) – Display a progress bar?

Returns

List of data points in augmented data set

Return type

List[DataPoint]

apply_generator(data_points, batch_size)[source]

Augment a list of data points using TFs and policy in batches.

This method acts as a generator, yielding augmented data points for a given input batch of data points. This can be useful in a training loop when it is too memory-intensive to pregenerate all transformed examples.

Parameters
  • data_points (Sequence[Any]) – List containing data points to be transformed

  • batch_size (int) – Batch size for generator. Yields augmented data points for the next batch_size input data points.

Yields

List[DataPoint] – List of data points in augmented data set for batches of inputs

Return type

Iterator[List[Any]]