Skip to main content

TensorFlow Bindings for PySyft

Project description


TensorFlow bindings for PySyft.

PySyft is a Python framework for secure, private deep learning. PySyft-TensorFlow brings secure, private deep learning to TensorFlow.

Build Status Chat on Slack


PySyft-TensorFlow is available on pip

pip install syft-tensorflow

NOTE: We aren't yet on a proper release schedule. Until then, we recommend building the code from source. The master branch is intended to be kept in line with this branch on the DropoutLabs fork of PySyft. If you have any trouble, please open an issue or reach out on Slack via the #team_tensorflow or #team_pysyft channels.


See the PySyft tutorials if you are unfamiliar with any Syft paradigms.

import tensorflow as tf
import syft

hook = sy.TensorFlowHook(tf)
# Simulates a remote worker (ie another computer)
remote = sy.VirtualWorker(hook, id="remote")

# Send data to the other worker
x = tf.constant(5).send(remote)
y = tf.constant(10).send(remote)

z = x * y

# => 50

Developing PySyft-TensorFlow


Project Support

PySyft-Tensorflow was contributed by and continues to be maintained by the team at Dropout Labs.

Please reach out to for support.

Dropout Labs

Project details

Download files

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

Files for syft-tensorflow, version 0.1.0
Filename, size File type Python version Upload date Hashes
Filename, size syft_tensorflow-0.1.0-py3-none-any.whl (37.2 kB) File type Wheel Python version py3 Upload date Hashes View hashes
Filename, size syft-tensorflow-0.1.0.tar.gz (17.3 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page