Skip to main content

TensorFlow Federated is an open-source federated learning framework.

Project description

TensorFlow Federated (TFF) is an open-source framework for machine learning and
other computations on decentralized data. TFF has been developed to facilitate
open research and experimentation with Federated Learning (FL), an approach to
machine learning where a shared global model is trained across many
participating clients that keep their training data locally. For example, FL has
been used to train prediction models for mobile keyboards without uploading
sensitive typing data to servers.

TFF enables developers to use the included federated learning algorithms with
their models and data, as well as to experiment with novel algorithms. The
building blocks provided by TFF can also be used to implement non-learning
computations, such as aggregated analytics over decentralized data.

TFF's interfaces are organized in two layers:

* Federated Learning (FL) API

The `tff.learning` layer offers a set of high-level interfaces that allow
developers to apply the included implementations of federated training and
evaluation to their existing TensorFlow models.

* Federated Core (FC) API

At the core of the system is a set of lower-level interfaces for concisely
expressing novel federated algorithms by combining TensorFlow with distributed
communication operators within a strongly-typed functional programming
environment. This layer also serves as the foundation upon which we've built
`tff.learning`.

TFF enables developers to declaratively express federated computations, so they
could be deployed to diverse runtime environments. Included with TFF is a
single-machine simulation runtime for experiments. Please visit the
tutorials and try it out yourself!


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

File details

Details for the file tensorflow_federated_nightly-0.16.1.dev20201007-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for tensorflow_federated_nightly-0.16.1.dev20201007-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 27a4480f403e57846d2299900c56753d942ce31ced744b415bcbd0cc44a52c76
MD5 6904f2a799258fa61f5e71abeed1bb6f
BLAKE2b-256 afd6ee23a6836617ce7386ad13b77b59805c794271574313845723ef00c56151

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page