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-0.19.0.dev20220204-py2.py3-none-any.whl.

File metadata

  • Download URL: tensorflow_federated_nightly-0.19.0.dev20220204-py2.py3-none-any.whl
  • Upload date:
  • Size: 814.6 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.9

File hashes

Hashes for tensorflow_federated_nightly-0.19.0.dev20220204-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 5bb8825cf539880b46d34772febf32cf35bea17e2e453295f343b3340e97be0e
MD5 8a4e525c19244e28343a8da4e8862426
BLAKE2b-256 3a9c81806c0864bf58fa1f9a226c64f42370ca973ea95b3526d37f68d26eb866

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