keras用cpu加速,为什么Keras模仿“裸露”？ CPU更快？

古城微笑少年丶 2022-08-30 11:16 180阅读 0赞

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Running a Keras model... the bad thing is that it is faster not to use CPU extentions (it should be the other way around).

Look at the output below.

Is there a config file where I can set inter\_op\_parallelism option ?

Using TensorFlow backend.

2018-10-18 17:21:32.620461: I tensorflow/core/platform/cpu\_feature\_guard.cc:141\] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA

2018-10-18 17:21:32.621535: I tensorflow/core/common\_runtime/process\_util.cc:69\] Creating new thread pool with default inter op setting: 2. Tune using inter\_op\_parallelism\_threads for best performance.

Results: -33.20 (23.69) MSE

real 2m55.990s

user 4m8.784s

sys 3m50.192s

Using TensorFlow backend.

2018-10-18 17:25:04.773578: I tensorflow/core/platform/cpu\_feature\_guard.cc:140\] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA

Results: -32.57 (23.16) MSE

real 1m48.847s

user 2m15.792s

sys 0m13.440s

解决方案

Here you are the code I'm using with keras, just put it on the top of your code.

from keras import backend as K

import tensorflow as tf

NUM\_PARALLEL\_EXEC\_UNITS = 6

config = tf.ConfigProto(intra\_op\_parallelism\_threads = NUM\_PARALLEL\_EXEC\_UNITS,

inter\_op\_parallelism\_threads = 1,

allow\_soft\_placement = True,