How to Force Keras to use CPU to Run Script?

The reason for such a demand:

My main training program was using the GPU fully. But I needed to get a prediction with another previously trained model urgently. I tried to use the GPU but I got OOM. Therefore, using CPU for the predicting job should be a good solution, and it did solve the problem!

Generally there are two ways: a short/lazy one and a lengthy but graceful one.

Option I:

If you want to force Keras to use CPU

import os
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" 
os.environ["CUDA_VISIBLE_DEVICES"] = ""

before Keras / Tensorflow is imported.

Option II:

A rather graceful and separable way of doing this is to use

import tensorflow as tf
from keras import backend as K

num_cores = 4

if GPU:
    num_GPU = 1
    num_CPU = 1
if CPU:
    num_CPU = 1
    num_GPU = 0

config = tf.ConfigProto(intra_op_parallelism_threads=num_cores,\
        inter_op_parallelism_threads=num_cores, allow_soft_placement=True,\
        device_count = {'CPU' : num_CPU, 'GPU' : num_GPU})
session = tf.Session(config=config)
K.set_session(session)

Here with booleans GPU and CPU you can specify whether to use a GPU or GPU when running your code.

The only thing to note is that you’ll need tensorflow-gpu and cuda/cudnn installed because you’re always giving the option of using a GPU.

Reference

» Can Keras with Tensorflow backend be forced to use CPU or GPU at will? - Stack Overflow

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