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The scenario is:

  1. I run keras in notebookA.
  2. I run keras in notebookB.
  3. I got InternalError: Blas GEMV launch failed when I start training my model in notebookB.

I know there is similar question here TensorFlow: InternalError: Blas SGEMM launch failed and I can solve this by closing another notebook (notebookA) which was using the gpu).

But I'd like to know is there anyway to run keras with tensorflow backend in multiple notebooks simultaneously? Or it's no way to achieve this for now?

I tried to use the settings below in each notebook but it didn't work (got the same error).

import tensorflow as tf
from keras.backend.tensorflow_backend import set_session
config = tf.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.3
set_session(tf.Session(config=config))

Thank you very much!

talonmies
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gf_tw
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  • Can you tell which os you‘re on? I‘m on ubuntu and never experienced this error before even with gpu sessions in more than one notebook. – dennis-w Mar 08 '18 at 18:40
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    Hi, I'm using windows10 with tensorflow1.4, cuda8 and cudnn6. So it looks like this error came from the OS... By the way, I can run keras(tensorflow) and pytorch simultaneously without any problem. – gf_tw Mar 09 '18 at 05:44
  • repeatable issue on windows, azure data science virtual machine – denfromufa May 25 '18 at 15:35

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