Installing on Linux

PyPose can be installed and used on various Linux distributions. Depending on your system and compute requirements, your experience with PyPose on Linux may vary in terms of processing time. It is recommended, but not required, that your Linux system has an NVIDIA GPU in order to harness the full power of PyPose’s CUDA support.

Prerequisites

Python

Python 3.7 or greater is generally installed by default on any of our supported Linux distributions, which meets our recommendation.

Tip: By default, you will have to use the command python3 to run Python. If you want to use just the command python, instead of python3, you can symlink python to the python3 binary.

However, if you want to install another version, there are multiple ways:

• APT
• Python website

If you decide to use APT, you can run the following command to install it:

sudo apt install python

It is recommended that you use Python 3.6, 3.7 or 3.8, which can be installed via any of the mechanisms above .

Package Manager

To install the PyPose binaries, you will need to use one of two supported package managers: Anaconda or pip.

pip

Python 3

While Python 3.x is installed by default on Linux, pip is not installed by default.

sudo apt install python3-pip

Tip: If you want to use just the command pip, instead of pip3, you can symlink pip to the pip3 binary.

Installation

pip

No CUDA

To install PyPose via pip, and do not have a CUDA-capable system or do not require CUDA, in the above selector, choose OS: Linux, Package: Pip and CUDA: None. Then, run the command that is presented to you.

With CUDA

To install PyPose via pip, and do have a CUDA-capable system, in the above selector, choose OS: Linux, Package: Pip and the CUDA version suited to your machine. Often, the latest CUDA version is better. Then, run the command that is presented to you.

Verification

To ensure that PyPose was installed correctly, we can verify the installation by running sample PyPose code. Here we will construct a randomly initialized tensor.

>>> import torch, pypose as pp

>>> # A random so(3) LieTensor
>>> r = pp.randn_so3(2, requires_grad=True)
    so3Type LieTensor:
    tensor([[ 0.1606,  0.0232, -1.5516],
            [-0.0807, -0.7184, -0.1102]], requires_grad=True)

Additionally, to check if your GPU driver and CUDA is enabled and accessible by PyPose, run the following commands to return whether or not the CUDA driver is enabled:

import torch
torch.cuda.is_available()

Building from source

For the majority of PyPose users, installing from a pre-built binary via a package manager will provide the best experience. However, there are times when you may want to install the bleeding edge PyPose code, whether for testing or actual development on the PyPose core. To install the latest PyPose code, you will need to build PyPose from source.