7d90bd15cf2112db4881429c909aa6104749b870,examples/tensorflow_mnist_estimator.py,,main,#Any#,129

Before Change

    train_data = mnist.train.images  // Returns np.array
    train_labels = np.asarray(mnist.train.labels, dtype=np.int32)
    eval_data = mnist.test.images  // Returns np.array
    eval_labels = np.asarray(mnist.test.labels, dtype=np.int32)

    // Horovod: pin GPU to be used to process local rank (one GPU per process)
    config = tf.ConfigProto()
    config.gpu_options.allow_growth = True

After Change

    // it, ignore the resulting exception and continue.
    cache_dir = os.path.join(os.path.expanduser("~"), ".keras", "datasets")
    if not os.path.exists(cache_dir):
        try:
            os.mkdir(cache_dir)
        except OSError as e:
            if e.errno == errno.EEXIST and os.path.isdir(cache_dir):
                pass
            else:
                raise

    // Download and load MNIST dataset.
    (train_data, train_labels), (eval_data, eval_labels) = \
        keras.datasets.mnist.load_data("MNIST-data-%d" % hvd.rank())

    // The shape of downloaded data is (-1, 28, 28), hence we need to reshape it

Instances