Creates a uniformly distributed random array with the given `mean` and `std`.

    Args:
        shape: The desired shape
        mean: The desired mean (Default value = 128)
        std: The desired std (Default value = 20)

    Returns: Random numpy array of given `shape` uniformly distributed with desired `mean` and `std`.

def random_array(shape, mean=128., std=20.):
    """Creates a uniformly distributed random array with the given `mean` and `std`.

    Args:
        shape: The desired shape
        mean: The desired mean (Default value = 128)
        std: The desired std (Default value = 20)

    Returns: Random numpy array of given `shape` uniformly distributed with desired `mean` and `std`.
    """
    x = np.random.random(shape)
    # normalize around mean=0, std=1
    x = (x - np.mean(x)) / (np.std(x) + K.epsilon())
    # and then around the desired mean/std
    x = (x * std) + mean
    return x