def load_np_arrays(files='original'):
    # nb: path assumes that we call this function from project root  
    train_imgs_f = 'train-images.npy'
    train_labels_f = 'train-labels.npy'

    if files == 'expanded':
        train_imgs_f = 'expanded-' + train_imgs_f 
        train_labels_f = 'expanded-' + train_labels_f 

    X_train = np.load(os.path.join('data', train_imgs_f))
    y_train = np.load(os.path.join('data', train_labels_f))
    X_test = np.load(os.path.join('data', 'test-images.npy'))

    return (X_train, y_train, X_test)
a.__mul__(b) <==> b*a
dataset/ETHPy150Open jrmontag/mnist-sklearn/utils.py/load_np_arrays--crossover with--dataset/ETHPy150Open CountZer0/PipelineConstructionSet/python/maya/site-packages/pymel-1.0.5/extras/completion/py/pymel/util/arrays.py/Array.__rmul__