Name: TensorFlow 2.0 and Keras (#AskTensorFlow)
Uploaded: 2020-03-31T07:23:33.000Z
Duration: 5 min 23 s
Description: Thousands of YouTube videos with English-Chinese subtitles! Now you can learn to understand native speakers, expand your vocabulary, and improve your pronunciation...

To-infinitive

Welcome to Ask TensorFlow where we answer the questions

Past simple

that you submitted with the hashtag #AskTensorFlow.

I'm Paige and I'm a developer advocate on the TensorFlow team.

So for the first question today, Codigo asked,

"What will be the support model for stand-alone Keras?

Excellent, so that's a phenomenal question, Codigo

Keras has been integrated as part of TensorFlow 2.0

But stand-alone Keras still certainly exists.

A number of the optimizations that we've included

for tf.keras haven't yet made their way back

to the stand-alone package but we are setting up

a special interest group specifically for Keras users

So if you have any questions, comments, concerns,

feel free to join the SIG Keras group and you can find that

Our second question is from Gurjeet, who asked,

"Does tf.keras include everything that stand-alone Keras includes?"

That's a great question, Gurjeet, we get that one a lot,

and I understand where you're coming from.

There are lots of things in stand-alone Keras

like the Theano backend or the CNTK backend.

But all the useful pieces, all of the optimizers, the metrics,

the losses, the layers, the model building API,

all the things that you need to use Keras

to train your models, to deploy your models,

Absolutely, and if you're familiar with stand-alone Keras,

the syntax is very similar, if not identical using tf.keras.

"What will TensorFlow 2.0 change to stand-alone Keras?"

And the answer is that that's still yet to be defined.

I mentioned before that we have a special interest group,

it's going to be specifically focused on Keras

and that will include a lot of the interplay

The ideal is that all of the great optimizations

will find their way back to the open source community

and we would love to have your help with that.

So if you have interest, join the SIG Keras group.

Yeah, you can find all the TensorFlow SIGs

Our next question is also from Gurjeet, who asked,

"Is there support for Bayesian layers in tf.keras?"

you can do all sorts of cool things with it,

including turning your deep neural network

into a Gaussian process with just one line of code change.

They also have made a port for Bayesian methods for hackers

"Can I create custom layers through tf.keras?"

Do you want to go a little bit more into that, Alex?

Yeah, so you just do the same thing you'd do

So you can inherit from the layer class and make your own layer.

Same way you can inherit from the metric class

So shipping with a default set of layers, losses, metrics, optimizers, models--

all the things that you're already used to from Keras--

but we also make it easy to extend, right?

So if you want to add your own custom loss function,

your own custom layer, you can contribute it

to the open source community through TensorFlow add-ons

and we would love to have you submit it as a PR.

"Will the Keras namespace be removed in future releases of TF 2.0?"

Not just Keras, but any symbol that is in TF 2.0 API

is going to stay there until at least TF 3.0.

And this even includes the symbols that we removed from TF 1.0

So if you're using anything from TF 2.0 now,

for as long as there is a TF 2.X at least.

Absolutely, and I am super delighted to hear that.

Yeah, thanks for the question, Sharavsambuu.

And out next question is also from Siby, who asked,

"Can we use SavedModel for a Keras model?"

You can take a Keras model and export it to the SavedModel format

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TensorFlow 2.0 and Keras (#AskTensorFlow)

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