Comments (5)
@AziziShekoofeh Thanks and I also appreciate your contribute by sharing your experiences.
In my understand, the package neuralgym does not require any cuDNN related libraries. It implicitly requires cuDNN when import tensorflow.
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@AziziShekoofeh Can you obtain results with nvidia-smi
?
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you mean the versions and so on? yes, nvidia-smi is working.
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@AziziShekoofeh Ok. I guess the problem is with TensorFlow-GPU. Please have a reference at issues like this one.
Can you successfully train other code/models with tensorflow? I wonder if the problem is on my side or tensorflow/environment side.
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Thanks for your prompt responses. Yes, I could.
Anyway, I find the proper combination finally, I am writing it for other people reference,
my previous setting [It was fine during the test but I had an issue with test]:
cuDNN v7.1.4
CUDA 9.0
Nvidia Driver 384.130
TF 1.4
my current setting and upgrades:
cuDNN v7.2.x
CUDA 9.0
Nvidia Driver 396.54
TF 1.4
I think the neuralgym needs cuDNN v7.2.x or higher [I don't know in which part exactly this dependency is happening], and the Nvidia driver should be 396.54 or higher.
Anyway, many thanks for the response and the useful package.
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Related Issues (13)
- i want to read 16 bit file
- load matrices or csv files HOT 1
- tensorflow 2.0 HOT 4
- 'tensorflow._api.v2.image' has no attribute 'resize_bilinear' HOT 3
- Requirement file is empty
- error in running training code for generative image inpainting training code HOT 3
- Failed to get_gpus() when total number of GPUs > 4 HOT 1
- epoch, step, pse setting HOT 5
- problem about np.get_gpus() HOT 1
- [BUG] Data loading error - wrong image resize HOT 1
- No variables to train issue
- Module name referenced instead of member in data_from_fnames.py HOT 1
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