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
// condition among the workers that share the same filesystem. If the
// directory already exists by the time this worker gets around to creating
// 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:
