openpilot
tinygrad
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openpilot | tinygrad | |
---|---|---|
838 | 17 | |
47,150 | 23,232 | |
1.7% | 4.8% | |
10.0 | 9.9 | |
about 20 hours ago | 2 days ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
openpilot
- I need some help understanding video uploads.
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Thomas Massie Failed to Stop "Kill Switch" Mandate That Could Disable Vehicles
Indeed. Comma.ai [1] does this [2] in a very open way.
Unfortunately existing manufacturers are unlikely to implement this in a complete local-first way.
[1] https://comma.ai
[2] https://github.com/commaai/openpilot/blob/master/selfdrive/m...
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Ask HN: Who is hiring? (November 2023)
See our open source driving agent on GitHub: https://github.com/commaai/openpilot
- Beginners Guide: Subaru Vehicles with Eyesight
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cv.c: experimental computer library in C; A Robot's guide to seeing the world -- introductory guide to CV
Hello! I was absolutely enthralled by Computer Vision when I came across some of Geohotz's streams about developing Comma.ai (a self-driving company) and I decided to delve into Computer Vision about a week back. I began by working on Aadv1k/cv.c which was meant to "imitate" OpenCV, as the phrasing goes "You Learn by building" I would be lying if I said this program is decent, it is not. I havent optimized much of it and this is like my 3rd C project :P Here is what all I got working (I will continue work on this), the only dependency here is STB * Smoothing * Gaussian blur * Median filter * Bilateral Filter * Box Filter * Edge detection * Unsharp mask * Laplacian Filter (Difference of Gaussian) * Sobel operator * Color * Greyscale * Thresholding * Global * Otsu's Method
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Can I use my Galaxy S10+ with my 2016 CR-V to run Flowpilot?
1.) Will this system work with my car? 2016 CR-Vs show up under the list of cars, but it says touring trim and I do not have the touring trim. I have found resources that state that any trim will still work with this and I am wondering if my car still has the actuators or ability to work with these systems.
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2020 Sierra/GMC CAN ids
Finally, worse comes to worse, manually extracting the DBC and parsing it using Cabana.
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Best Setup for Remote Control?
It's probably best you search for the Retropilot Discord. This is beyond what the normal comma.ai people or community try to do.
- If you have a Comma Three and a 2023 Corolla or 2023 Prius, comma is looking for testers for a "Toyota B Harness"
tinygrad
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AMD Unveils Ryzen 8000G Series Processors: Zen 4 APUs for Desktop with Ryzen AI
Not sure if I completely understand what "Ryzen AI" does, but Tinygrad for example has some limited support for RDNA3[0]. It isn't quite there yet in matters of performance though, as you can read in the comments of that file.
There's also a small tutorial by AMD on how to use the WMMA intrinsic[1] using AMD's hipcc[2] compiler. Documentation is sparse kinda sparse, but the instruction set is not huge. The RDNA3 ISA guide[3] might also be helpful (and only a fraction of the pages are relevant.)
0. https://github.com/tinygrad/tinygrad/blob/master/extra/gemm/...
1. https://gpuopen.com/learn/wmma_on_rdna3/
2. https://github.com/ROCm/HIPCC
3. https://www.amd.com/content/dam/amd/en/documents/radeon-tech...
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Beyond Backpropagation - Higher Order, Forward and Reverse-mode Automatic Differentiation for Tensorken
This post describes how I added automatic differentiation to Tensorken. Tensorken is my attempt to build a fully featured yet easy-to-understand and hackable implementation of a deep learning library in Rust. It takes inspiration from the likes of PyTorch, Tinygrad, and JAX.
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[D] What is a good way to maintain code readability and code quality while scaling up complexity in libraries like Hugging Face?
what do you think about tinygrad? I think its a good example of growing and well written, (partially) well documented library with many close to reference implementations
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💻 7 Open-Source DevTools That Save Time You Didn't Know to Exist ⌛🚀
🌟 Support on GitHub Website: https://tinygrad.org/
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Decomposing Language Models into Understandable Components
Try to get something like tinygrad[1] running locally, that way you can tweak things a bit run it again and see how it performs. While doing this you'll pick up most of the concepts and get a feeling of how things work. Also, take a look at projects like llama.cpp[2], you don't have to fully understand what's going on here, tho.
You may need some intermediate knowledge of linear algebra and this thing called "data science" nowadays, which is pretty much knowing how to mangle data and visualize it.
Try creating a small model on your own, it doesn't have to be super fancy just make sure it does something you want it to do. And then ... you'll probably could go on your own then.
- Stable Diffusion in pure C/C++
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There is no hard takeoff
lol, you should see me bash my own code. I'm even more mean.
https://github.com/tinygrad/tinygrad/blob/master/examples/hl...
have a bunch of bounties on it, we're getting 94%+ now! mostly not me who wrote this, see history. have to switch to float16 and add Winograd convs still. we have a branch with multigpu too.
goal is to beat an A100 in speed on a tinybox.
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MatX: Faster Chips for LLMs
AMD drivers are a higher priority but he also made tinygrad https://github.com/tinygrad/tinygrad
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[Project] Whisper Implementation in Rust using burn
I temporarily switched from Rust to Python for machine learning, but quickly became fed up with Python's annoying versioning issues and runtime errors. I looked for a better path to machine learning and discovered burn, a deep learning framework for Rust. As my first burn project I decided to port OpenAI's Whisper transcription model. The project can be found at Gadersd/whisper-burn: A Rust implementation of OpenAI's Whisper model using the burn framework (github.com). I based it on the excellently concise tinygrad implementation that can be found here. The tinygrad version begrudgingly uses Torch's stft which I ported into a pure Rust short time Fourier transform along with the mel scale frequency conversion matrix function because I am curious and just a bit masochistic.
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Onnx Runtime: “Cross-Platform Accelerated Machine Learning”
Be better to use https://github.com/tinygrad/tinygrad as an intermediary framework?
What are some alternatives?
sunnypilot - sunnypilot is a fork of comma.ai's openpilot, an open source driver assistance system. sunnypilot offers the user a unique driving experience for over 260 supported car makes and models with modified behaviors of driving assist engagements. sunnypilot complies with comma.ai's safety rules as accurately as possible.
carla - Open-source simulator for autonomous driving research.
opendbc - democratize access to car decoder rings
dragonpilot - dragonpilot - 基於 openpilot 的開源駕駛輔助系統
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
netron - Visualizer for neural network, deep learning and machine learning models
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
openpilot - DOES NOT SUPPORT COMMA 3X - Stock Additions (0.8.14): 3/automatic following distance profiles, customizable fork params with opEdit, and a smoother longitudinal experience for TSS2 Toyotas
materialize - The data warehouse for operational workloads.
opendbc - democratize access to car decoder rings