
Release Keras 2.3.0 · Keras-team/Keras - Anon84
https://github.com/keras-team/keras/releases/tag/2.3.0
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m0zg
Good move. I'd much rather it worked well for one backend then sucked mightily
on all of them. Eager mode means that for the first time ever you can _easily_
debug programs using the TensorFlow backend. That will be music to the ears of
anyone who's ever tried to debug a complex TF-backed model.

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aledalgrande
I don't think they have that in yet:

> However note that it does not support most TensorFlow 2.0 features, in
> particular eager execution.

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m0zg
They don't have that in _this_ standalone version. The one integrated into TF
2.0 itself does support eager execution IIRC.

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aledalgrande
Oh cool, thought you referred to this specific version.

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amrrs
Since TF included Keras in its codebase, I have been wondering if Keras would
be acquired by Google. Is this the reality of the open source world we live
in. TF vs Pytorch - Google vs FB. C

Seems indie frameworks in AI can't survive?

At least glad, Julia hasn't been in that way yet.

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fock
last I checked, there's also amazon/microsoft pushing MX.net (which seems
mature and actually seems to have tooling which is not presuming the user is
Google-internal)

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pjmlp
MX.net?

Microsoft is pushing ML.NET, which builds on top of DirectML and interoperates
with TensorFlow.

No idea about Amazon.

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xamlhacker
Keras still has CNTK and Theano backends in addition to Tensorflow. Given that
both frameworks are not being developed anymore, is there any point in
maintaining those backends in the future?

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lopuhin
From the release announcement:

> Development will focus on tf.keras going forward. We will keep maintaining
> multi-backend Keras over the next 6 months, but we will only be merging bug
> fixes.

So it's the end of Keras

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fock
and I thought there was discussion about including mx.net. Looks like if you
want to build, train and reuse NNs (in an established framework) you finally
have to choose between Google, Facebook or Amazon/Microsoft in every case.

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thomasdelteil
There is support for Keras with MXNet[1], however you need to install a forked
version of keras, `pip install keras-mxnet`.

[1] [https://github.com/awslabs/keras-apache-
mxnet](https://github.com/awslabs/keras-apache-mxnet)

