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The TensorFlow bindings for PySyft
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Latest commit b2aa6e0 Oct 24, 2019


TensorFlow bindings for PySyft.

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

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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.

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