README.md

• Documentation
• Installation
• Get Assets
• Google Cloud Instance Setup

Installation Guide

Set up a fresh Python environment:

conda create -n bayes3d python=3.9
conda activate bayes3d

Install compatible versions JAX and Torch:

pip install --upgrade torch==2.2.0 torchvision==0.17.0+cu118 --index-url https://download.pytorch.org/whl/cu118
pip install --upgrade jax[cuda11_local]==0.4.20 -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

Bayes3D is built on top of GenJAX, which is currently hosted in a private Python package repository. To configure your machine to access GenJAX:

• File an issue asking @sritchie to give you access.
• Install the Google Cloud command line tools.
• Follow the instructions on the installation page
• run gcloud auth application-default login as described in this guide.

Then run the following command to configure pip to use these new gcloud commands:

pip install keyring keyrings.google-artifactregistry-auth

Finally, install Bayes3D:

pip install bayes3d --extra-index-url https://us-west1-python.pkg.dev/probcomp-caliban/probcomp/simple/

Download model and data assets:

wget -q -O - https://raw.githubusercontent.com/probcomp/bayes3d/main/download.sh | bash

Test

Run python demo.py to test installation setup.

Common issues

Error:

fatal error: EGL/egl.h: No such file or directory
    #include <EGL/egl.h>

fatal error: GL/glu.h: No such file or directory
    #include <GL/glu.h>

Run:

sudo apt-get install mesa-common-dev libegl1-mesa-dev libglfw3-dev libgl1-mesa-dev libglu1-mesa-dev

Error:

[F glutil.cpp:338] eglInitialize() failed
Aborted (core dumped)

Reinstall NVIDIA drivers with sudo apt-get install nvidia-driver-XXX. Check version of driver using nvidia-smi.

Error:

ImportError: libcupti.so.11.7: cannot open shared object file: No such file or directory

Run:

pip install torch==2.0.0+cu118 torchvision==0.15.1+cu118 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu118

Error:

raise RuntimeError("Ninja is required to load C++ extensions")

Run:

sudo apt-get update
sudo apt-get install ninja-build

To check your CUDA version:

nvcc --version

GCP Setup

• Start new VM instance (see link). Select GPU - NVIDIA V100 and Machine Type 8vCPU 4 Core 30GB.

-From the VM instances page, searched for public image c2-deeplearning-pytorch-2-0-gpu-v20230925-debian-11-py310. Increase storage to 1000GB.

• Note that public image names get updated frequently, so it is possible you may not find the one mentioned above. To find the latest public image, go to the public list, and look for an image as close to the one above (Debian 11, CUDA 11.8, Python 3.10, Pytorch 2.0 etc.).

• SSH into instance and when prompted, install the NVIDIA drivers.

• Follow installation guide.

License

Distributed under the Apache 2.0 license. See LICENSE.