Issues with the new Azure ML Notebook VM

[sorinM]

Hi Team,

I’m assisting a Partner in Germany that started to work with the new Azure Machine Learning compute instance (NC6):

https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-instance

Because this is in preview, I found it as a good idea to relay the Partner feedback to you. Please take a quick look over these issues and let me know if some of them are known, or should I redirect the Partner to technical support.

Here are the Partner questions:

1. How should I manage conda environments in the notebook vm jupyter lab?
   1. Currently I create environments and add to the selectable kernels in the jupyter lab via “ipykernel install”
   2. I also tried nb_conda but that didn’t work.
   3. Now I experience some strange behaviour. After activating the environment I seems like I can only use the base env pip. E.g. if I install a pypi module inside the env it is not available in the notebook. If I install the module via “conda install” it is.
      1.       Pip install abc -> not working
      2.       python -m pip install abc -> not working

•       conda install abc -> working

1. Currently I want to use spacy. For that I need to install some language model (python -m spacy download abc), which is then not accessible in the notebook.

2. Is it possible to trigger a shutdown of the vm after a notebook execution finished, similar to databricks notebooks?
3. Is it possible to use jupyter lab extensions? After activating the extension manager I get an error message in the extension tab :
   1. Error communicating with server extension. Consult the documentation for how to ensure that it is enabled. Reason given: Error: 500 (Internal Server Error)
   2. I tried the docs and the suggested commands. Didn’t help.

I suggested to the Partner to look into the tutorial with the 1^st experiment as mentioned on our site, in order to maybe train themselves with an already tested operation:

https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-1st-experiment-sdk-train

The Partner replied that they take another route. In our tutorial the Jupyter Notebooks are run in the Azure ML Notebooks section. But the Partner is starting the jupyter lab through the compute section of Azure ML and do their dev setup (conda env, module installations etc.) through jupyter lab terminal.

Is this particular practice atypical or not the best one?

For any suggestions or contact info to people that might be interested in this topic, I would like to thank you in advance.

Thanks,

Sorin

[#2]

@sorinM

Trying to create the bot using my own code.