koila
merged_depth
| koila | merged_depth | |
|---|---|---|
| 7 | 3 | |
| 1,817 | 45 | |
| - | - | |
| 6.8 | 1.8 | |
| 20 days ago | over 2 years ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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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
merged_depth
- [P] Monocular Depth Estimation - I ran a number of fairly well-known pre-trained models and looked at the average
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Monocular Depth Estimation - Running multiple pre-trained models and looking at the average
Project Link: https://github.com/p-ranav/merged_depth
- I ran 4 pre-trained depth estimation models and looked at the average
What are some alternatives?
TorchGA - Train PyTorch Models using the Genetic Algorithm with PyGAD
AdaBins - Official implementation of Adabins: Depth Estimation using adaptive bins
torchsynth - A GPU-optional modular synthesizer in pytorch, 16200x faster than realtime, for audio ML researchers.
Cam-Hackers - Hack Cameras CCTV FREE
bittensor - Internet-scale Neural Networks
magicavoxel-shaders - A collection of shaders for MagicaVoxel to generate geometry, noise, patterns, and simplify common and repetitive tasks.
gpt-j-api-huggingface
mildlyoverfitted - Paper implementations from scratch and machine learning tutorials
tributary - Streaming reactive and dataflow graphs in Python
OpenSeeFace - Robust realtime face and facial landmark tracking on CPU with Unity integration
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.
Jetson-Nano-Ubuntu-20-image - Jetson Nano with Ubuntu 20.04 image