framework-reproducibility
RealESRScaler
framework-reproducibility | RealESRScaler | |
---|---|---|
5 | 2 | |
418 | 53 | |
1.2% | - | |
5.8 | 10.0 | |
7 months ago | about 1 year ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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framework-reproducibility
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Tensorflow: I'm getting different results from the same code depending on where I run it. [D]
Even with a fixed seed there's no guarantee that you'll get the exact same results due to the fact that most floating operations are not deterministic when parallelized. You can enable determinism flags in your framework to try and mitigate that, but results may still vary depending on your model and how you're running it.
- Same seed, different images
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Dealing with non-deterministic result
Setting the seed alone is not enough because there will be a randomness resulted from GPU operations (there is some way to eliminate randomness due to GPU operations like https://github.com/NVIDIA/framework-determinism, but I cannot make it work with the current latest version of TF). Another workaround is not using GPU, but the training time does not make sense as I need to iterate fast, trying new idea.
- No Bee, it's you...
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[D] Do you yourself write 100% reproducible ML code?
check out https://github.com/NVIDIA/framework-determinism, which should allow you to make fully reproducible to the bit code that runs on GPU. i've contributed to this repo and the author is extremely helpful.
RealESRScaler
What are some alternatives?
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
QualityScaler - QualityScaler - image/video deeplearning upscaling for any GPU
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
RealScaler - RealScaler - image/video AI upscaler app (Real-ESRGAN)
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
NiceScaler - Images & Video DeepLearning Upscaler
FluidFrames.RIFE - FluidFrames.RIFE | video AI frame-generation app
Tsuki - Manga uncensoring scripts using DeepCreamPy & HentAI combined with custom scripts
onnx-web - web UI for GPU-accelerated ONNX pipelines like Stable Diffusion, even on Windows and AMD