GPU Computing

If you have a CUDA compatible graphics card installed, you can utilize your GPU for this CNN example by placing the following piece of code on top of your IDE:

import os
os.environ['THEANO_FLAGS'] = 'device=gpu0, assert_no_cpu_op=raise, on_unused_input=ignore, floatX=float32'

We do recommend however to first try this example on your regular CPU.

Let's first import and prepare the data.

We use a 32 x 32 input size considering this is the actual size of the image:

from keras.datasets import cifar10
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution2D, MaxPooling2D
from keras.optimizers import SGD
from keras.utils import np_utils

batch_size = 32
nb_classes = 10
nb_epoch = 5 #these are the number of epochs, watch out because it might set your #cpu/gpu on fire.


# input image dimensions
img_rows, img_cols = 32, 32
# the CIFAR10...