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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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