# datasets-1 **Repository Path**: deeplearningrepos/datasets-1 ## Basic Information - **Project Name**: datasets-1 - **Description**: TFDS is a collection of datasets ready to use with TensorFlow, Jax, ... - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2021-03-30 - **Last Updated**: 2021-08-31 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # TensorFlow Datasets TensorFlow Datasets provides many public datasets as `tf.data.Datasets`. [![Kokoro](https://storage.googleapis.com/tfds-kokoro-public/kokoro-build.svg)](https://storage.googleapis.com/tfds-kokoro-public/kokoro-build.html) [![PyPI version](https://badge.fury.io/py/tensorflow-datasets.svg)](https://badge.fury.io/py/tensorflow-datasets) [![Tutorial](https://img.shields.io/badge/doc-tutorial-blue.svg)](https://www.tensorflow.org/datasets/overview) [![API](https://img.shields.io/badge/doc-api-blue.svg)](https://www.tensorflow.org/datasets/api_docs/python/tfds) [![Catalog](https://img.shields.io/badge/doc-datasets-blue.svg)](https://www.tensorflow.org/datasets/catalog/overview#all_datasets) ## Documentation To install and use TFDS, we strongly encourage to start with our [**getting started guide**](https://www.tensorflow.org/datasets/overview). Try it interactively in a [Colab notebook](https://colab.research.google.com/github/tensorflow/datasets/blob/master/docs/overview.ipynb). Our documentation contains: * [Tutorials and guides](https://www.tensorflow.org/datasets/overview) * List of all [available datasets](https://www.tensorflow.org/datasets/catalog/overview#all_datasets) * The [API reference](https://www.tensorflow.org/datasets/api_docs/python/tfds) ```python # !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](https://www.tensorflow.org/guide/data_performance) 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](https://github.com/tensorflow/datasets/issues). ## Want a certain dataset? Adding a dataset is really straightforward by following [our guide](https://www.tensorflow.org/datasets/add_dataset). Request a dataset by opening a [Dataset request GitHub issue](https://github.com/tensorflow/datasets/issues/new?assignees=&labels=dataset+request&template=dataset-request.md&title=%5Bdata+request%5D+%3Cdataset+name%3E). And vote on the current [set of requests](https://github.com/tensorflow/datasets/labels/dataset%20request) 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](https://ai.google/education/responsible-ai-practices).* *`tensorflow/datasets` is Apache 2.0 licensed. See the [`LICENSE`](LICENSE) file.*