TensorFlow Datasets
TensorFlow Datasets provides many public datasets as tf.data.Datasets.






Documentation
To install and use TFDS, we strongly encourage to start with our
getting started guide. Try
it interactively in a
Colab notebook.
Our documentation contains:
# !pip install tensorflow-datasets
import tensorflow_datasets as tfds
import tensorflow as tf
Construct a tf.data.Dataset
ds = tfds.load('mnist', split='train', as_supervised=True, shuffle_files=True)
ds = ds.shuffle(1000).batch(128).prefetch(10).take(5)
for image, label in ds:
pass
TFDS core values
TFDS has been built with these principles in mind:
- Simplicity: Standard use-cases should work out-of-the box
- Performance: TFDS follows
best practices
and can achieve state-of-the-art speed
- Determinism/reproducibility: All users get the same examples in the same
order
- Customisability: Advanced users can have fine-grained control
If those use cases are not satisfied, please send us
feedback.
Want a certain dataset?
Adding a dataset is really straightforward by following
our guide.
Request a dataset by opening a
Dataset request GitHub issue.
And vote on the current
set of requests
by adding a thumbs-up reaction to the issue.
Citation
Please include the following citation when using tensorflow-datasets for a
paper, 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}},
}
Disclaimers
This is a utility library that downloads and prepares public datasets. We do
not host or distribute these datasets, vouch for their quality or fairness, or
claim that you have license to use the dataset. It is your responsibility to
determine whether you have permission to use the dataset under the dataset's
license.
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 this
library, please get in touch through a GitHub issue. Thanks for your
contribution to the ML community!
If you're interested in learning more about responsible AI practices, including
fairness, please see Google AI's Responsible AI Practices.
tensorflow/datasets is Apache 2.0 licensed. See the
LICENSE file.