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We are excited to share the story behind TF-Replicator, a software library that helps developers deploy their TensorFlow code between CPUs, GPUs and TPUs with minimal effort. Blog post: https://deepmind.com/blog/tf-replicator-distributed-machine-learning/ … Paper: https://arxiv.org/abs/1902.00465 pic.twitter.com/y3MaWCEGGm
If you share our mission and are excited about accelerating state-of-the-art AI research, look out for open Software Engineering positions at https://deepmind.com/careers (machine learning experience is optional for many of these roles).
This is a hidden gem among all the Tensorflow 2.0 release over the last two days. This looks to be very interesting solution to scaling with both Model and Data Parallel methods.
You may use it to detect all the diying RTX cards ;-)
How is this different from Mirrored strategy? Also will this work with Keras models?
The MirroredStrategy API is being revised to closely match our TF-Replicator API, see https://github.com/tensorflow/community/blob/master/rfcs/20181016-replicator.md …. This will also work with Keras.
@Kashish95260608 check this
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