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README.md

DLRM Jupyter demo notebooks

This folder contains the demo notebooks for DLRM. The most convenient way to use these notebooks is via using a docker container, which provides a self-contained, isolated and re-producible environment for all experiments. Refer to the Quick Start Guide section of the Readme documentation for a comprehensive guide.

First, clone the repository:

git clone https://github.com/NVIDIA/DeepLearningExamples
cd DeepLearningExamples/PyTorch/Recommendation/DLRM

Notebook list

1. Pytorch_DLRM_pyt_train_and_inference.ipynb: training and inference demo

To execute this notebook, first build the DLRM container:

docker build . -t nvidia_dlrm_pyt

Make a directory for storing DLRM data and start a docker containerexport PYTHONPATH=/workspace/dlrm with:

mkdir -p data
docker run --runtime=nvidia -it --rm --ipc=host  -v ${PWD}/data:/data nvidia_dlrm_pyt bash

Within the docker interactive bash session, start Jupyter with

export PYTHONPATH=/workspace/dlrm
jupyter notebook --ip 0.0.0.0 --port 8888

Then open the Jupyter GUI interface on your host machine at http://localhost:8888. Within the container, this demo notebook is located at /workspace/dlrm/notebooks.

2. DLRM_Triton_inference_demo.ipynb: inference demo with the NVIDIA Triton Inference server.

To execute this notebook, first build the following inference container:

docker build -t dlrm-inference . -f triton/Dockerfile

Start in interactive docker session with:

docker run -it --rm --gpus device=0 --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 --net=host -v <PATH_TO_SAVED_MODEL>:/models -v <PATH_TO_EXPORT_MODEL>:/repository dlrm-inference bash

where:

  • PATH_TO_SAVED_MODEL: directory containing the trained DLRM models.

  • PATH_TO_EXPORT_MODEL: directory which will contain the converted model to be used with the NVIDIA Triton inference server.

Within the docker interactive bash session, start Jupyter with

export PYTHONPATH=/workspace/dlrm
jupyter notebook --ip 0.0.0.0 --port 8888

Then open the Jupyter GUI interface on your host machine at http://localhost:8888. Within the container, this demo notebook is located at /workspace/dlrm/notebooks.