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TensorFlow Datasets provides many public datasets astf.data.Datasets.

To install and use TFDS, we strongly encourage to start with ourgetting started guide. Tryit interactively in aColab notebook.

Our documentation contains:

• Tutorials and guides
• List of allavailable datasets
• TheAPI reference

# !pip install tensorflow-datasetsimporttensorflow_datasetsastfdsimporttensorflowastf# Construct a tf.data.Datasetds=tfds.load('mnist',split='train',as_supervised=True,shuffle_files=True)# Build your input pipelineds=ds.shuffle(1000).batch(128).prefetch(10).take(5)forimage,labelinds:pass

TFDS has been built with these principles in mind:

• Simplicity: Standard use-cases should work out-of-the box
• Performance: TFDS followsbest practicesand can achieve state-of-the-art speed
• Determinism/reproducibility: All users get the same examples in the sameorder
• Customisability: Advanced users can have fine-grained control

If those use cases are not satisfied, please send usfeedback.

Adding a dataset is really straightforward by followingour guide.

Request a dataset by opening aDataset request GitHub issue.

And vote on the currentset of requestsby adding a thumbs-up reaction to the issue.

Please include the following citation when usingtensorflow-datasets for apaper, in addition to any citation specific to the used datasets.

@misc{TFDS,title ={{TensorFlow Datasets}, A collection of ready-to-use datasets},howpublished ={\url{https://www.tensorflow.org/datasets}},}

This is a utility library that downloads and prepares public datasets. We donot host or distribute these datasets, vouch for their quality or fairness, orclaim that you have license to use the dataset. It is your responsibility todetermine whether you have permission to use the dataset under the dataset'slicense.

If you're a dataset owner and wish to update any part of it (description,citation, etc.), or do not want your dataset to be included in thislibrary, please get in touch through a GitHub issue. Thanks for yourcontribution to the ML community!

If you're interested in learning more about responsible AI practices, includingfairness, please see Google AI'sResponsible AI Practices.

tensorflow/datasets is Apache 2.0 licensed. See theLICENSE file.