Module: tfds

Defined in

tensorflow_datasets (tfds) defines a collection of datasets ready-to-use with TensorFlow.

Each dataset is defined as a tfds.core.DatasetBuilder, which encapsulates the logic to download the dataset and construct an input pipeline, as well as contains the dataset documentation (version, splits, number of examples, etc.).

The main library entrypoints are:



core module: API to define datasets.

download module: API.

features module: tfds.features.FeatureConnector API defining feature types.

file_adapter module: tfds.file_adapter.FileFormatAdapters for GeneratorBasedBuilder.

units module: Defines convenience constants/functions for converting various units.

testing module: Testing utilities.


class GenerateMode: Enum for how to treat pre-existing downloads and data.

class percent: Syntactic sugar for defining slice subsplits: tfds.percent[75:-5].

class Split: Enum for dataset splits.


as_numpy(...): Converts a to an iterable of NumPy arrays.

builder(...): Fetches a tfds.core.DatasetBuilder by string name.

list_builders(...): Returns the string names of all tfds.core.DatasetBuilders.

load(...): Loads the named dataset into a