
TensorFlow 1.11 released - jamesblonde
https://github.com/tensorflow/tensorflow/releases/tag/v1.11.0
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jamesblonde
The main highlight is a new version of AllReduce native to TensorFlow. This,
like Horovod, builds a ring and has both native and NCCL implementations.
Early results (albeit on a single host) show that it outperforms Horovod:
[https://groups.google.com/a/tensorflow.org/forum/#!topic/dis...](https://groups.google.com/a/tensorflow.org/forum/#!topic/discuss/7T05tNV08Us)

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minimaxir
And it looks like it's natively supported via Keras too?
[https://github.com/tensorflow/tensorflow/tree/master/tensorf...](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/distribute)

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jamesblonde
Yes, and with the estimator API, too.

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breckuh
> Add multi-GPU DistributionStrategy support in tf.keras. Users can now use
> fit, evaluate and predict to distribute their model on multiple GPUs.

Is this different than the existing multi_gpu_model?
([https://keras.io/utils/#multi_gpu_model](https://keras.io/utils/#multi_gpu_model))

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SloopJon
Looks like Python 3.7 is not supported yet:

[https://github.com/tensorflow/tensorflow/issues/20517](https://github.com/tensorflow/tensorflow/issues/20517)

Somewhat off topic: I'm rediscovering the dance required to set up a new
Windows 10 laptop with Python, CUDA, and TensorFlow. If I understand
correctly, pyenv does not work on Windows. Is there something similar?

Also, if I installed TensorFlow in WSL, it wouldn't be able to use the GPU,
would it?

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breckuh
Python 3.7 is supported if you build master from source. But that can be a lot
of work and though it may solve your TF problem, it may create other problems
with other Python packages.

In my experience conda is the way to go for setting up your environment. I did
not have great luck with pyenv, YMMV.

I don't know about WSL. Maybe setup a dual boot with Ubuntu on your system?

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dairychris
Does it still have that horrible java build dependency?

