Known Issues

Cannot open shared object file …

If you are getting an error message like cannot open shared object file: No such file or directory when trying to import AutoNLU, it means that there is something not completely ok with your Python setup. This is mainly a problem for compiled packages (like AutoNLU) and you might therefore not really notice this problem with most other packages.

Solution 1

In most cases, the error can be fixed by installing the static library for your Python version. For example, in Ubuntu, the package to install for Python 3.6 would be libpython3.6-dev:

sudo apt install libpython3.6-dev

You will have to check what package exactly you need, depending on your Python version and Linux distribution.

Solution 2

If you are not able to find the appropriate package for your Python version, or the problem persists even after installing it (e.g. if you have installed a certain Python version via other means than your systems package manager) then you have to manually point Python to the correct path where to find the library.

First, we need to find where those libraries are stored on your system. Search for the file name that was part of your original error message using locate. E.g. :

sudo updatedb

This might give you an output like the following:


which means your static library can be found in /home/peter/mypython/lib. We can now add this path to the LD_LIBRARY_PATH evironment variable:

export LD_LIBRARY_PATH=/home/peter/mypython/lib:$LD_LIBRARY_PATH

After this command, you should be able to import AutoNLU correctly. To make this change permanent, you have to add this line to your .bashrc file, which can also be done with the following command:

echo "export LD_LIBRARY_PATH=/home/peter/mypython/lib:\$LD_LIBRARY_PATH" >> ~/.bashrc

Solution for Azure Machine Learning Instances

Azure machine learning compute instances have exactly this problem and we have to use Solution 2. More specifically:

export LD_LIBRARY_PATH=/anaconda/envs/azureml_py36/lib:$LD_LIBRARY_PATH

And to make the change permanent:

echo "export LD_LIBRARY_PATH=/anaconda/envs/azureml_py36/lib:\$LD_LIBRARY_PATH" >> ~/.bashrc

Solution for Azure Notebooks

If you want to use the Notebooks that are directly integrated into the Azure Machine Learning Studio, the previous solution does not work because the changed LD_LIBRARY_PATH will be ignored and we have to directly change this in the Jupyter kernel configuration.

Open a terminal to the compute instance you are running your notebook on and use the command jupyter kernelspec list to find the path of the Jupyter Kernel you are using for your Notebooks. The path of your Kernel contains a kernel.json file you will have to edit (e.g. using nano kernel.json). You have to add the line "env": {"LD_LIBRARY_PATH":"/anaconda/envs/azureml_py36/lib"}, to this file. After this it should look similar to this:

 "argv": [
 "env": {"LD_LIBRARY_PATH":"/anaconda/envs/azureml_py36/lib"},
 "display_name": "Python 3.6 - AzureML",
 "language": "python"

You have to restart your notebook after these changes and importing AutoNLU should also work correctly for the notebooks.