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keras model / deep learning

User: "Thiru"
New Altair Community Member
Updated by Jocelyn
1   Im trying to use the Iris data set  and  the respective deep learning process  given in Rapidminer repository , under 'keras sample" - iris data set..
But im not able to execute the same.  But I couldnt do it, with warning of " process failed'.   ( please find enclosed the process jpg).  i tried with some other data set, the issue remains.  can you help me to resolve this. thanks.

does using Keral model  -need any special  settings in rapidmine?

thirumurthy m


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    User: "Mate"
    New Altair Community Member
    Hi Thiru,

    quick question: which extension version are you using and how exactly did you find this process ?
    I can't seem to find it myself, i.e. I don't have a "Keras Samples" repo.

    Mate
    User: "Thiru"
    New Altair Community Member
    OP
    hello @Mate
    thanks for your reply.  Im using version 9.9.   see the enclosed full screen pic. 
    By clicking process - "iris classification' under 'keras samples' folder,  Im getting this process.


    thiru

    User: "Mate"
    New Altair Community Member
    Updated by Mate
    I meant the extension version, not RapidMiner :).

    + I don't really understand what you are trying to do here.
    Can you please shed some light on why you are trying to do here ?
    Btw, what does it have to do with "Keras" ? This is just a normal deep learning training in RapidMiner right ?
    User: "Thiru"
    New Altair Community Member
    OP
    deep learning extension version: 0.9.003,  & Keras extension: 1.0.

    Im trying to learn the deep learning process , as i'm new to this. 
     I'm following the video   by phillip schlunder.  ->    rapidminer.com/resource/state-deep-learning/
    User: "Mate"
    New Altair Community Member
    Updated by Mate
    Well, that's a bit older than the one we currently have.
    Could you maybe upgrade your extension(s) to the latest version(s) ?

    + we have tutorial processes that can help, amongst them one for the Iris use-case.
    User: "jacobcybulski"
    New Altair Community Member
    Make sure that you have a Python Scripting extension installed and both Python and Keras are configured to point to the correct location of your Python. If you use an Anaconda environment then also specify the environment for Python and for Keras you will need to navigate to the Python in the same environment. Of course TensorFlow and Keras have to be installed (pip or conda). However, Keras extension is no longer supported and works only with TensorFlow 1.xxx (not the current version 2.xxx). So the best is to switch to Deep Learning extension, which is Java native (no need for Python) and continuously supported by RapidMiner.
    User: "Thiru"
    New Altair Community Member
    OP
     I updated the latest version of  , deeplearning, Keras model, Python scripting.  
    But still the error persists,  when I'm using the process given in sample repository.   (iris classification in 'Keras sample').
    How to resolve this?
    User: "jacobcybulski"
    New Altair Community Member
    Updated by jacobcybulski
    When configuring Keras and Python in preferences, have you tried to press the test button in each? Keras installation is non trivial and requires a lot of system bits to satisfy the assumptions of the extension, e. g. it will not work with Python 3.8, Tensorflow 2, needs some libraries, etc. As I said before, the extension has not been updated for a vew years and it is safer to use Deep Learning extension. I have given up on using it a while ago. However, I'll try to reinstall it and will let you know if there are any issues, which I expect to be, perhaps it is no longer compatible with RM 9.9?
    User: "jacobcybulski"
    New Altair Community Member
    Updated by jacobcybulski
    OK, I have reinstalled the current version of Keras, configured and tested my Python and Keras extensions in preferences, ensuring that they point to the same version of Python in the same location. I have loaded the Iris example and yes the process shows the "potential" problem, however, when executing it runs fine. What happens is that Keras extension generates a custom (i.e. non-standard RM) model and so RapidMiner does not know if the model type generated and then used when applied are compatible. And yet, RM will pass the model from the output port to the input port and the model will be applied to the test data. All this is assuming that your Python 3.7 / TensorFlow 1.14 / Keras 2.2.5 are correctly installed.
    User: "jacobcybulski"
    New Altair Community Member
    Updated by jacobcybulski
    When installing Keras on top of Tensorflow, you will need additional Python packages, i.e. pydot, HDF5, h5py, graphviz, python-graphviz. Note that you need to install graphviz software separately. Depending on your environment, you may need to install some additional software, e.g. cython, so watch the warnings and add those libraries as required. When you get warning on version incompatibilities, e.g. with bleach and htm5lib, you may try ignoring them.
    User: "Thiru"
    New Altair Community Member
    OP
    @jacobcybulski
    thanks for your clarifications.   ( I got into keras, as it was explained in training video.    rapidminer.com/resource/state-deep-learning )

    Anything to be installed if we use just  'deep learning extension'.
    does this 'DL extension' has same capacity as 'keras extn' ?

    regds
    thiru
    User: "jacobcybulski"
    New Altair Community Member
    Accepted Answer
    Updated by jacobcybulski
    If you use Deep Learning extension, you will also need to install ND4j extension which manages its back end. If all you need is to run your DL processes on a CPU then you are done. If you have a suitable NVidia GPU then you will also need additional software, such as gou drivers and a GPU development kit. 
    User: "Thiru"
    New Altair Community Member
    OP
    @jacobcybulski
    thanks again for your inputs.

    regdsthiru