koila
torchsynth
koila | torchsynth | |
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7 | 2 | |
1,817 | 319 | |
- | 1.6% | |
6.8 | 6.1 | |
20 days ago | 12 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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koila
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How to fix CUDA out of memory with Koila?
but I always get CUDA out of memory . Long story short I found koila which should fix this issue, but I'm not sure how to add this to my code. in their page they have (input, label) = lazy(input, label, batch=0) but i kinda feel lost. can you help me please.
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Pytorch CUDA out of memory persists after lowering batch size and clearing gpu cache
Having 53760 neurons takes much memory. Try adding more Conv2D layers or play with stride. Also, try .detach() to data and labels after training. Lastly, I would suggest to take a look at https://github.com/rentruewang/koila. Have not tried yet but it should be helpful.
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[D] Would the 8gb VRAM of the 3060ti mean that some models in computer vision cannot be trained with it at all?
Tools like this can help: https://github.com/rentruewang/koila
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[P] Dynamic batching for GPT-J API
You could take a look at how these guys are determining memory batch size limits... https://github.com/rentruewang/koila
- Koila: Prevent PyTorch's out of memory error with lazy evaluation
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Solve PyTorch's `CUDA error: out of memory` in 1 line of code
Project Link
- Show HN: Solve `CUDA error: out of memory` in one line of code
torchsynth
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Is there any AI sound generator that is not voice?
One Billion Audio Sounds from GPU-enabled Modular Synthesis - Synthesizing modular synths. Code here.
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Massively Parallel Rendering of Complex Closed-Form Implicit Surfaces (2020)
https://www.cv-foundation.org/openaccess/content_cvpr_2016/p...
This concept has not (yet) been applied in audio ML. We have a paper in submission---will be on ArXiv soon---where we share a GPU-enabled modular synthesizer that is 16000x faster than realtime, concurrently released with a 1-billion audio sample corpus that is 100x larger than any audio dataset in the literature. Here's the code: https://github.com/torchsynth/torchsynth
What are some alternatives?
TorchGA - Train PyTorch Models using the Genetic Algorithm with PyGAD
bittensor - Internet-scale Neural Networks
gpt-j-api-huggingface
FastFold - Optimizing AlphaFold Training and Inference on GPU Clusters
tributary - Streaming reactive and dataflow graphs in Python
merged_depth - Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
thrash-protect - Simple-Stupid user-space program doing "kill -STOP" and "kill -CONT" to protect from thrashing. It works a bit like the ABS break on the car.
ADOP