def data_aug()

in train.py [0:0]

• 10 lines of code
• 6 McCabe index (conditional complexity)

def data_aug(xx, nprng=None, yy=None):
    """just hflip"""
    if nprng is None:
        nprng = np.random
    xx = xx.reshape(dataset.orig_shape)
    if yy is None:
        yy = sample_augmentation_type(2, size=xx.shape[0], nprng=nprng)
    assert yy.shape[0] == xx.shape[0]
    # n = len(xx)
    # xx = np.pad(xx, [[0, 0], [4, 4], [4, 4], [0, 0]], mode='reflect')
    xx = [np.fliplr(x) if y else x for x, y in zip(xx, yy)]
    # ii = nprng.randint(low=0, high=4 * 2 + 1, size=n)
    # jj = nprng.randint(low=0, high=4 * 2 + 1, size=n)
    # xx = [x[i:i + 32, j:j + 32] for x, i, j in zip(xx, ii, jj)]
    xx = np.asarray(xx).reshape(dataset.shape)
    return xx