A few more general remarks:
- with Python and KNIME it is all about compatibility and consistency of the packages. That is where Anaconda tries to help
- you should not update individual packages but let Anaconda manage that
- concerning Tensorflow and Keras note which versions are supported by the various KNIME nodes (typically that is not the most recent version)
- these versions must be compatible with your Python version (it might be that it is to large)
I am working on a text about KNIME and Python. But in general your path could look something like this. Please check hints that would come from conda and adapt accordingly.
#create KNIME’s Conda environment
#KNIME Python Integration Guide
#https://docs.knime.com/latest/python_installation_guide/img/py36_knime.yml
conda env create -f=/Users/test/py36_knime.yml
#check the environments if py36_knime is there
conda info --envs
#active KNIME Python environment
source activate py36_knime
#set anaconda as top priority channel
#my impression is that anaconda as priority is more stable
conda config --prepend channels anaconda
#add conda-forge at the end of channels
conda config --append channels conda-forge
#check channel priority
conda config --get channels
#should look something like this:
#--add channels ‘conda-forge’#lowest priority
#--add channels ‘defaults’
#--add channels ‘anaconda’#highest priority
#set channel priority to flexible
conda config --set channel_priority flexible
#update anaconda
conda update conda
conda update anaconda
#install tensorflow (you might try to set a different version, you might have to try)
conda install -c conda-forge tensorflow=1.8.0
a
#install Keras (you might try to set a different version, you might have to try)
conda install -c conda-forge keras=2.1.6
#repeat update anaconda
conda update conda
conda update anaconda