2.12 Tips


For R based models it is often useful to install some R packages through the operating system, especially those that are identified as system dependencies in MLHUB.yaml. Other dependencies are installed locally for the user if they have not already been installed on the system. For this case some useful packages to pre-install are identified below. This can be done at any time, but is useful before installing any of the R based MLHub packages. Users will not then individually need to install the packages for themselves.

$ R
> install.packages(c("rpart", "tidyverse"))

Similarly for common Python dependencies. One particular example is tensorflow which does not have a Ubuntu package and thus is installed using pip. This can be installed any time, and any mlhub package that requires tensorflow will not need to install it separately.

$ pip install tensorflow

If you have system administrator access (generally through the sudo command) then you may want to checkout a package’s MLHUB.yaml file to install any dependencies on the system, rather than per user when they install the MLHub package.

If a model has installed badly, got corrupted, or not working as expected, sometimes an uninstall followed by install will fix the problem. When uninstalling in these circumstances it is usually a good idea to remove the cache as well:

$ ml uninstall objects
Remove '/home/kayon/.mlhub/objects/' [Y/n]? y
Remove cache '/home/kayon/.mlhub/.cache/objects/' as well [y/N]? y

$ ml install objects

Commands Auto Completion

The bash shell on Linux supports command line auto-completion which is pretty handy. You can download ml.bash from the MLHub and place the file into ~/.local/share/bash-completion/completions/ for recent versions of bash, or into the system-wide location /etc/bash_completion.d/. The configure command installs the file into the system-wide location. Be sure to restart the shell for the auto-completion to take effect.

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