# Tensorflow/Keras installation conflict **URL:** \ **Category:** KNIME Analytics Platform\ **Created:** [November 5, 2022, 10:18pm UTC](https://forum.knime.com/t/tensorflow-keras-installation-conflict/48670 "2022-11-05T22:18:45Z")\ **Posts on this page:** 1\ **Showing post:** 4
**Author:** ![mlauber71](https://forum-cdn.knime.com/user_avatar/forum.knime.com/mlauber71/32/73590_2.png) [@mlauber71](https://forum.knime.com/u/mlauber71)\ **Post date:** [November 8, 2022, 6:01am UTC](https://forum.knime.com/t/tensorflow-keras-installation-conflict/48670/4 "2022-11-08T06:01:02Z")
@TargetFilled what you can do besides following the [KNIME Deep Learning Integration Installation Guide](https://docs.knime.com/latest/deep_learning_installation_guide/index.html) and letting KNIME do the deep learning setup ([KNIME Deep Learning Integration Installation Guide](https://docs.knime.com/latest/deep_learning_installation_guide/index.html#_installation)) is getting the [official KNIME yaml configuration files](https://forum.knime.com/t/python-environment-creation-problem/41577/7) for deep learning and use them just with [miniforge](https://github.com/conda-forge/miniforge) and [conda-forge](https://anaconda.org/conda-forge) repository to avoid licencing problems and also have a clean and slim setup only settings the minimum restrictions with versions KNIME is recommending: > [@Python Environment Creation Problem](https://forum.knime.com/t/python-environment-creation-problem/41577/6): > > @kienerj on a Windows machine you can (currently) see the YAML files used under: \knime\_4.5.x\plugins\org.knime.python2.envconfigs\_4.5.x.yyyyyyyyyy\envconfigs that can help to build one’s own configuration. If you already have built an [environment](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) and want to save it in a ‘clean’ (reusable) way the way to go seems to be the --from-history function: Linux … conda env export --from-history | grep -v “prefix” \> environment.yaml Windows: conda env export --from-history | findstr -v “pref… Or you can try some deep learning setup for [Keras](https://kni.me/w/8pLvXVGL1hj7lXDh) and [Tensorflow](https://kni.me/w/0P1TaKHmebS4g8zv) with the [environment propagation](https://www.knime.com/blog/how-to-manage-python-environments-conda-and-knime). I have two prepared for python 3.6 and 3.9 for MacOS and Windows: > [@AttributeError: module ‘keras.optimizers’ has no attribute ‘Adam’](https://forum.knime.com/t/attributeerror-module-keras-optimizers-has-no-attribute-adam/38461/3): > > @akhtarameen as it happens I just have collected some example how to set up [Keras](https://hub.knime.com/search?tag=Keras&type=Workflow) and [Tensor Flow](https://hub.knime.com/search?tag=TensorFlow&type=Workflow) 2 (for classification tasks) with the help of the [Conda Environment propagation](https://kni.me/n/7HrPteTMsla4bZml). If you have a working [Miniconda](https://docs.conda.io/en/latest/miniconda.html) or Anaconda environment [configured in KNIME](https://docs.knime.com/latest/python_installation_guide/index.html#configure_python_integration) you should be able to just use the propagation and get a [working deep learning setup](https://docs.knime.com/latest/deep_learning_installation_guide/index.html#_introduction). You would then have to carefully check and plan what you want to d with the setup and what architecture you want to use. The setup in … I also try to keep this article up to date about KNIME and python in general with additional links for further reference: > **[Meta Collection about KNIME and Python – mlauber71](https://hub.knime.com/mlauber71/spaces/Public/_knime_and_python_meta_collection~AvjrddXKOIoZYLV3/current-state)** > > KNIME and Python - just good friends It can be a little confusing at first but I would recommend to invest a few maybe hours to grasp the concept of using miniconda or miniforge and [conda environments](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-from-an-environment-yml-file) with [yaml files](https://forum.knime.com/t/data-separate-and-melting/45710/9) and versions. It will greatly enhance your knowledge about how to use python and interact with KNIME. Sometimes the books will struggle somewhat to keep track with all versions and dependencies the latest conda might help. - use conda and only conda-forge channel via miniforge or miniconda - find the latest KNIME recommended yaml file with a minimum of version restrictions - let conda handle all additions and version restrictions and possible updates - tell KNIME where to find your python-environment for deep learning - destill that into a conda environment propagation node to share and have easy access - if you encounter version problems start with only a few restrictions and keep adding and editing them (like @steffen_KNIME has suggested). Check if a KNIME sample workflow would still run Ok you probably got more than you were bargaining for 😊. I plan on writing some more about this with examples and screenshots. – Edit: [KNIME and Python — Setting up Deep Learning Environments for Keras and TensorFlow | by Markus Lauber | Low Code for Data Science | Medium](https://medium.com/low-code-for-advanced-data-science/knime-and-python-setting-up-deep-learning-environments-for-keras-and-tensorflow-4b66003858f4) --- _[View the full topic](https://forum.knime.com/t/tensorflow-keras-installation-conflict/48670)._