Is physics still maintained?

Yes, active. Last change 19 days ago.

New, little track record. 0 stars, 1 months old. Look at the code and the owner before running it.

gitmanual

Reading the repo

Opening the box…

How to install on Linux

takshsoni01-hub/physics

Massively parallel rigidbody physics simulation on accelerator hardware.

Python

Difficulty: Easy
Time: about 5 min
Stars: ★ 0
Activity: Updated this month

Before you start

Is it free?: YesOpen source (Apache-2.0).
Still maintained?: Yes, activeLast change 19 days ago.
Can I trust it?: New, little track record0 stars, 1 months old. Look at the code and the owner before running it.

Saved setup from 3 h ago

Will it work on Linux?

Yes, it runs on Linux

You'll build it yourself with Python.

Your system

macOS Windows Linux

4 steps on Linux

Download setup.sh

Then run bash setup.sh. It stops at the first error and is safe to run again. Servers and tests aren't started; it lists them at the end. Read it first.

Clone the repository

git clone https://github.com/takshsoni01-hub/physics.git
cd physics

Install the required runtimes

Python >=3.11

sudo apt install python3 python3.11 python3-venv  # Debian/Ubuntu

Install dependencies

python -m venv .venv
source .venv/bin/activate
pip install -e .

4
Run the tests
```
pytest
```

From the README: Quickstart: Colab in the Cloud

Explore Brax easily and quickly through a series of colab notebooks:

Brax Basics introduces the Brax API, and shows how to simulate basic physics primitives.
Brax Training introduces Brax's training algorithms, and lets you train your own policies directly within the colab. It also demonstrates loading and saving policies.
Brax Training with MuJoCo XLA - MJX demonstrates training in Brax using the MJX physics simulator.
Brax Training with PyTorch on GPU demonstrates how Brax can be used in other ML frameworks for fast training, in this case PyTorch.

Did you get it running?

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