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README

TensorFlow Datasets

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

Unittests PyPI version Python 3.10+ Tutorial API Catalog

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)

# Build your input pipeline
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.

Core symbols most depended-on inside this repo

join
called by 1202
tensorflow_datasets/core/deprecated/text/text_encoder.py
download_and_extract
called by 251
tensorflow_datasets/core/download/download_manager.py
get
called by 233
tensorflow_datasets/core/features/features_dict.py
items
called by 220
tensorflow_datasets/core/dataset_info.py
dataset_info_from_configs
called by 185
tensorflow_datasets/core/dataset_builder.py
exists
called by 164
tensorflow_datasets/core/github_api/github_path.py
read
called by 117
tensorflow_datasets/core/reader.py
load
called by 115
tensorflow_datasets/core/logging/base_logger.py

Shape

Method 3,794
Function 2,012
Class 1,654
Route 35

Languages

Python100%

Modules by API surface

tensorflow_datasets/robotics/rtx/rtx.py320 symbols
tensorflow_datasets/core/dataset_builder_test.py117 symbols
tensorflow_datasets/core/dataset_info.py99 symbols
tensorflow_datasets/scripts/documentation/dataset_markdown_builder.py82 symbols
tensorflow_datasets/core/dataset_builder.py80 symbols
tensorflow_datasets/core/features/feature.py70 symbols
tensorflow_datasets/testing/test_utils.py66 symbols
tensorflow_datasets/core/splits.py62 symbols
tensorflow_datasets/core/registered_test.py62 symbols
tensorflow_datasets/core/writer.py55 symbols
tensorflow_datasets/core/dataset_info_test.py55 symbols
tensorflow_datasets/scripts/documentation/build_community_catalog.py53 symbols

For agents

$ claude mcp add datasets \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact