cifar_load_data.py

# Load MNIST data copied by SageMaker
def load_data(input_path):
    # Adapted from https://github.com/keras-team/keras/blob/master/keras/datasets/fashion_mnist.py

    # Training and validation files
    files = ['training/train-y', 'training/train-x',
             'validation/test-y', 'validation/test-x']
    # Load training labels
    with open(input_path+files[0], 'rb') as lbpath:
        y_train = pickle.load(lbpath, encoding='bytes')
    # Load training samples
    with open(input_path+files[1], 'rb') as imgpath:
        x_train = pickle.load(imgpath, encoding='bytes')
    # Load validation labels
    with open(input_path+files[2], 'rb') as lbpath:
        y_test = pickle.load(lbpath, encoding='bytes')
    # Load validation samples
    with open(input_path+files[3], 'rb') as imgpath:
        x_test = pickle.load(imgpath, encoding='bytes')
    print("Files loaded")
    return (x_train, y_train), (x_test, y_test)