nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

Siemens Community Catalyst Program

The Siemens Community Catalyst program was co-created with our community to acknowledge technology leaders who consistently contribute to the Siemens Community. Nominations are accepted on a rolling basis.

Nominate Now

Keras Extension Dependencies

ZAM

Hello,

For some reason, my Keras extension cant find "Keras" and "Scikit-learn" libraries on my computer although they are in the same folder as the other required libraries such as "Tensorflow".

Anyone encountered a similar problem or can help, i would appreciate that.

Thanks a lot.

Find more posts tagged with

AI Studio

Extensions

Deep Learning + Neural Nets

Accepted answers

varunm1

Hello @ZAM

Keras is having lot of issues and not much stable. There is a deep learning extension in Rapidminer that can be used instead of keras which runs on DL4J.
https://community.rapidminer.com/discussion/53800/a-more-native-deep-learning-solution

If you want to try keras, you should follow the exact specification provided in the below thread. All the versions should be same as in this thread.

https://community.rapidminer.com/discussion/comment/54662#Comment_54662

All comments

varunm1

SGolbert

Hi,

I also wanted to ask what are the future plans for the Keras extension ( @pschlunder ). I think that as long as DL4J has similar capabilities, it makes more sense to use that, so long the implementation from RapidMiner is done efficiently. To illustrate the last point, a lot of the computing time when using Keras from Python comes from Python-TensorFlow communication. If that could be avoided in RapidMiner+DL4J, we have the potential of having an excellent performance.

Regards,

Sebastian

sgenzer

I will defer to @pschlunder for the details but, in short, the DL4J extension is going to be supported moving forward in lieu of the Keras one - for all the reasons stated above. In the RM ecosystem I would strongly recommend staying with DL4J.

[that said, a little birdie has told me that there will be new RM integration with Jupyter notebooks in the very near future, so you could likely avoid some of the Keras issues but simply taking advantage of that...stay tuned )

pschlunder

Hi,

thanks for using our Deep Learning functionality. Sorry to hear, that the keras extension is causing you problems. When saying, that tensorflow can be found, is it with the python scripting operator? If so please ensure, that the python path for the Keras extension is set to the same folder in the general RapidMiner settings in the Keras tab. Unfortunately you need to set the path for both the Python and the Keras extension.

As mentioned by others maybe you could try the currently under development Deep Learning extension. Many of the previously available functionality from the Keras extension is already there. As Sebastian mentioned, it's not relying on Python and hence works more performant since data can be kept in Java.

For the future expect Deep Learning capabilities from the new extension, if you need to apply models created in Keras (e.g. from colleagues or previous projects), please try out the "Read Keras Model" operator from Deep Learning extension. It enables you to load models trained in python and apply them inside RapidMiner.

Hope this helps,

Philipp