Example Notebooks

We have collection of Jupyter example notebooks that are based on different datasets to provide end-to-end examples for NVIDIA Merlin. These example notebooks demonstrate how to use NVTabular with TensorFlow, PyTorch, and HugeCTR. Each example provides additional details about the end-to-end workflow, which includes ETL, Training, and Inference.

Running the Example Notebooks

Docker containers are available from the NVIDIA GPU Cloud. Access the catalog of containers at http://ngc.nvidia.com/catalog/containers.

All the training containers include NVTabular for feature engineering. Choose the container that provides the modeling library that you prefer:

Merlin Training (modeling with HugeCTR)
Merlin TensorFlow Training
Merlin PyTorch Training

All the inference containers include NVTabular so that workflows can be read and they all include Triton Inference Server for deploying models to production and serving recommendations. Choose the container that can read models from the modeling library that you used:

Merlin Inference (HugeCTR models)
Merlin TensorFlow Inference
Merlin PyTorch Inference

To run the example notebooks using Docker containers, perform the following steps:

Pull and start the container by running the following command:
```
docker run --gpus all --rm -it \
  -p 8888:8888 -p 8797:8787 -p 8796:8786 --ipc=host \
  <docker container> /bin/bash
```
If you are running on Docker version lower than 19.03, change --gpus all to --runtime=nvidia.

The container opens a shell when the run command execution is completed. Your shell prompt should look similar to the following example:
```
root@2efa5b50b909:
```
Install JupyterLab with pip by running the following command:
```
pip install jupyterlab
```
For more information, see the JupyterLab Installation Guide.

Start the JupyterLab server by running the following command:

jupyter-lab --allow-root --ip='0.0.0.0'

View the messages in your terminal to identify the URL for JupyterLab. The messages in your terminal show similar lines to the following example:

Or copy and paste one of these URLs:
   http://2efa5b50b909:8888/lab?token=9b537d1fda9e4e9cadc673ba2a472e247deee69a6229ff8d
or http://127.0.0.1:8888/lab?token=9b537d1fda9e4e9cadc673ba2a472e247deee69a6229ff8d

Open a browser and use the 127.0.0.1 URL provided in the messages by JupyterLab.
After you log in to JupyterLab, navigate to the /merlin/examples directory to try out the example notebooks.