I have a shared machine with 64 cores on which I have a big pipeline of Keras functions that I want to run. The thing is that it seems that Keras automatically uses all the cores available and I can't do that.
I use Python and I want to run 67 neural networks in a for loop. I would like to use half of the available cores.
I can't find any way of limiting the number of cores in Keras... Do you have any clue?
As @Yu-Yang suggested, I used this line before each fit I do :
from keras import backend as K
K.set_session(K.tf.Session(config=K.tf.ConfigProto(intra_op_parallelism_threads=32, inter_op_parallelism_threads=32)))
Check the CPU usage (htop) :
来源：https://stackoverflow.com/questions/46421258/limit-number-of-cores-used-in-keras