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Template Class MapDataset#

Inheritance Relationships#

Base Type#

  • public torch::data::datasets::BatchDataset< MapDataset< SourceDataset, AppliedTransform >, detail::optional_if_t< SourceDataset::is_stateful, AppliedTransform::OutputBatchType >, SourceDataset::BatchRequestType > (Template Class BatchDataset)

Class Documentation#

template<typename SourceDataset, typename AppliedTransform>
class MapDataset : public torch::data::datasets::BatchDataset<MapDataset<SourceDataset, AppliedTransform>, detail::optional_if_t<SourceDataset::is_stateful, AppliedTransform::OutputBatchType>, SourceDataset::BatchRequestType>#

A MapDataset is a dataset that applies a transform to a source dataset.

Public Types

using DatasetType = SourceDataset#
using TransformType = AppliedTransform#
using BatchRequestType = typename SourceDataset::BatchRequestType#
using OutputBatchType = detail::optional_if_t<SourceDataset::is_stateful, typename AppliedTransform::OutputBatchType>#

Public Functions

inline MapDataset(DatasetType dataset, TransformType transform)#
inline virtual OutputBatchType get_batch(BatchRequestType indices) override#

Gets a batch from the source dataset and applies the transform to it, returning the result.

inline virtual std::optional<size_t> size() const noexcept override#

Returns the size of the source dataset.

inline void reset()#

Calls reset() on the underlying dataset.

NOTE: Stateless datasets do not have a reset() method, so a call to this method will only compile for stateful datasets (which have a reset() method).

inline const SourceDataset &dataset() noexcept#

Returns the underlying dataset.

inline const AppliedTransform &transform() noexcept#

Returns the transform being applied.