How to run jupyter lab in a conda environment on a google compute engine (Deep Learning VM)?

Question

• I made a conda environment in my Deep Learning VM. When I ssh to it (clicking SSH button of my instance in the VM instances page) and type source activate <environment_name> it gets activated correctly in the shell.

• I successfully connect to jupyter lab from my local machine as explained from the docs

How can I use jupyter in a specific conda environment on this VM ?

The accepted way to run jupyter in a specific conda environment seems to be

Activate a conda environment in your terminal using source activate <environment_name> before you run jupyter notebook.

but the Deep Learning VM docs say

A Jupyter Lab session is started when your Deep Learning VM instance is initialized

so that I cannot source activate before the creation of the jupyter lab session.

Any ideas ?

• run a standard jupyter notebook myself instead of using the jupyter lab provided by the VM ?
• activate the environment in startup scripts of the VM before the creation of the jupyter lab ?

Answer 1

Please try out the below steps:

1. source activate < env_name >

2. conda install ipykernel

3. ipython kernel install --name < env_name > --user

After this, launch your python code from hub.colfaxresearch.com and select Kernel --> Change Kernel --> < env_name >

Answer 2

The only way we've found to make it see all your environments(conda and new python environments) is to run a new jupyter lab instance.

• When connecting over SSH map the 8888 or any other port instead of 8080 gcloud compute ssh ... -L 8888:localhost:8888
• After connecting run jupyter lab from console. The default port is 8888.

This is one of the ugliest issues I've seen with GCE so far!