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GPU training doesn't work? #108
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with such conda environment GPU training is working for me on linux with nvidia GPU, hope it helps… nv2 i installed from github and edited setup.py to bump version of keras |
The most recent N2V version requires TF2. Could you try this combination:
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And I add the "X:\anaconda3\envs\n2v_env\Library\bin" to the system path. It works very well on Win10. |
Got a new GPU and can only use super slow tensorflow==2.2 or slow tensorflow==1.15
Edit: found a solution for CUDA 11.5 + Tensorflow 1.15 that is fast
cf. https://github.com/NVIDIA/tensorflow sidenote: this is on Ubuntu 20.04 Edit 2: for Tensorflow 1.15., adding this to the notebook is useful to prevent annoying warnings and excessive memory allocation:
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The environment version I am using is TF2, on Win11 and Anaconda. |
Hi, thanks for your nice code.
When I'm training the model, it trains on cpu, not gpu, which makes the training quite slow.
I've installed tensorflow-gpu 1.14.0 and keras 2.2.5. And the environment works fine with other project (other projects can train on gpu). I wonder is there any configuration we need to set explicitly to make gpu work? Thanks!
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