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 ...

Get Large Scale Machine Learning with Python now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.