This document is relevant for: Inf1, Inf2, Trn1, Trn1n

Jupyter Notebook QuickStart#

SSH Tunnel to the Inf1/Trn1 instance#

The Jupyter notebook can be run via a browser on port 8888 by default. For simplicity we will use ssh port forwarding from your machine to the instance.

ssh -i "<pem file>" <user>@<instance DNS name> -L 8888:

On an Ubuntu image the user will be ubuntu@, while on AL2 you should use ec2-user@

This additional argument forwards connections to port 8888 on your machine to the new Inf1/Trn1 instance.

Starting the Jupyter Notebook on the instance#

From your ssh prompt on the Inf1/Trn1 instance run

jupyter notebook

You should see logging in your ssh session similar to:

[I 21:53:11.729 NotebookApp] Using EnvironmentKernelSpecManager...
[I 21:53:11.730 NotebookApp] Started periodic updates of the kernel list (every 3 minutes).
[I 21:53:11.867 NotebookApp] Loading IPython parallel extension
[I 21:53:11.884 NotebookApp] JupyterLab beta preview extension loaded from /home/ubuntu/anaconda3/lib/python3.6/site-packages/jupyterlab
[I 21:53:11.884 NotebookApp] JupyterLab application directory is /home/ubuntu/anaconda3/share/jupyter/lab
[I 21:53:12.002 NotebookApp] [nb_conda] enabled
[I 21:53:12.004 NotebookApp] Serving notebooks from local directory: /home/ubuntu/tutorial
[I 21:53:12.004 NotebookApp] 0 active kernels
[I 21:53:12.004 NotebookApp] The Jupyter Notebook is running at:
[I 21:53:12.004 NotebookApp] http://localhost:8888/?token=f9ad4086afd3c91f33d5587781f9fd8143b4cafbbf121a16
[I 21:53:12.004 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[W 21:53:12.004 NotebookApp] No web browser found: could not locate runnable browser.

Copy/paste this URL into your browser when you connect for the first time, to login with a token: http://localhost:8888/?token=f9ad4086afd3c91f33d5587781f9fd8143b4cafbbf121a16&token=f9ad4086afd3c91f33d5587781f9fd8143b4cafbbf121a16

[I 21:53:12.004 NotebookApp] Starting initial scan of virtual environments...
[I 21:53:13.507 NotebookApp] Found new kernels in environments: conda_tensorflow2_p27, conda_aws_neuron_mxnet_p36, conda_anaconda3, conda_tensorflow_p27, conda_chainer_p27, conda_python3, conda_tensorflow_p36, conda_aws_neuron_tensorflow_p36, conda_mxnet_p27, **conda_my_notebook_env**, conda_tensorflow2_p36, conda_pytorch_p27, conda_python2, conda_chainer_p36, conda_mxnet_p36, conda_pytorch_p36

Running the Jupyter Notebook from your local browser#

If you copy and paste the link that looks like http://localhost:8888/?token=f9ad4086afd3c91f33d5587781f9fd8143b4cafbbf121a16&token=f9ad4086afd3c91f33d5587781f9fd8143b4cafbbf121a16 into your local browser the Notebook navigation pane should pop up.

This works because ssh is forwarding you local port 8888 through to the Inf1/Trn1 instance port 8888 where the notebook is running. Note that our new conda environment is visible as “kernel” with the “conda_” prefix (highlighted)

  1. In notebook browser select the tutorial.

  2. This will pop up a new tab. In that tab use the menus:

Kernel → Change Kernel → Environment (conda_my_notebook_env)

  1. Start reading through the self documenting notebook tutorial


If your jupyter notebook does not start please try the following:

mv ~/.jupyter ~/.jupyter.old
mkdir -p ~/.jupyter
echo "c.NotebookApp.iopub_data_rate_limit = 10000000000" > ~/.jupyter/

# Instal Jupyter notebook kernel
 pip install ipykernel
 python3 -m ipykernel install --user --name aws_neuron_venv_pytorch --display-name "Python Neuronx"
 pip install jupyter notebook
 pip install environment_kernels

jupyter notebook

This document is relevant for: Inf1, Inf2, Trn1, Trn1n