DirectML
nn-morse
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| DirectML | nn-morse | |
|---|---|---|
| 26 | 1 | |
| 1,944 | 40 | |
| 4.9% | - | |
| 7.6 | 10.0 | |
| 3 days ago | about 1 year 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.
DirectML
- Microsoft DirectML: high-performance DirectX 12 library for ML
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AMD Radeon RX 7600 XT Linux Performance
Only reason I am using the DirectML fork of Automatic1111 is because I am on Windows and pytorch hasn't caught up to RocM 6.
DirectML is fully supported path on Windows and is support by Microsoft et al. (https://github.com/microsoft/DirectML).
Everyone is moving off Cuda as quickly as possible not because the other are better, per se, but because it is easier and cheaper.
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Train issue on AMD card
See: https://github.com/microsoft/DirectML/issues/400
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'Everyone and Their Dog is Buying GPUs,' Musk Says as AI Startup Details Emerge
ONNX (https://onnx.ai/ https://github.com/onnx/onnx) is an alternative to the basic CUDA model, using Direct-ML ( https://learn.microsoft.com/en-us/windows/ai/directml/dml-intro https://github.com/microsoft/DirectML), which is a microsoft-backed open approach. That is what has allowed AMD cards, even slightly older ones, to join in on the machine learning fun.
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AMD ROCm: A Wasted Opportunity
It's really shocking that AMD fails to extend support natively.
Workarounds such as DirectML claim to be the answer in unifying people with NVIDIA or AMD GPUs, but thus far it hasn't, with issues such as [this](https://github.com/microsoft/DirectML/issues/58) constantly popping up.
As nicolaslem points out, Arch does have community packages for ROCm, but that, unsurprisingly fails to lend support to many consumer GPUs. The best community support I have come across are [rocm-opencl](https://copr.fedorainfracloud.org/coprs/mystro256/rocm-openc... [rocm-hip](https://copr.fedorainfracloud.org/coprs/mystro256/rocm-hip/) for Fedora maintained by [mystro256](https://github.com/Mystro256), who is a single AMD employee.Thanks to him, my AMD GPU (Radeon 6800XT) hasn't completely gone to waste, and I was able to tinker with some things (Gaming isn't really up my alley).
Lately however, after beginning to work on DGX V100s and A100s, and using my older laptop with a GTX 1650, it was apparent how simple setting up CUDA was, and how easily I could experiment with it on my consumer card. Many have spoken about similar stories, and here's mine. Really hope AMD does a whole lot more, and doesn't exclusively keep their powerful GPUs for gaming.
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nn-morse neural network mentioned in ftroop by VK6MIK
You can use a NVidia gpu or the cpu to do the training but the cpu training is very very slow. For AMD graphics cards like the AMD Radeon VII the only solution is pytorch_directml but unfortunately there appears to be a bug that stops it working nn-morse and torch-directml memory leak? · Issue #355
- Trying to get my computer set up for ML
- ROCm installation on Acer Aspire 3
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Microsoft’s PyTorch-DirectML Release-2 Now Works with Python Versions 3.6, 3.7, 3.8, and Includes Support for GPU Device Selection to Train Machine Learning Models
Github: https://github.com/microsoft/DirectML
- Dying Light 2 is 30 fps on Series S 😴
nn-morse
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nn-morse neural network mentioned in ftroop by VK6MIK
This is the open source nn-morse software I mentioned in ftroop The repo is here https://github.com/pd0wm/nn-morse and it's described in this blog post https://blog.willemmelching.nl/random/2020/05/10/morse/
What are some alternatives?
onnx - Open standard for machine learning interoperability
NCRFpp - NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.
text2image-gui - Somewhat modular text2image GUI, initially just for Stable Diffusion
Muzero-unplugged - Pytorch Implementation of MuZero Unplugged for gym environment. This algorithm is capable of supporting a wide range of action and observation spaces, including both discrete and continuous variations.
civitai - A repository of models, textual inversions, and more
morse - Morse code translator
pymorse - A simple python script to convert morse code into characters and characters into morse code.
Muzero - Pytorch Implementation of MuZero for gym environment. It support any Discrete , Box and Box2D configuration for the action space and observation space.
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.