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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(X, n_components=2, random_state=None):
 """Initialize an embedding using samples from an isotropic Gaussian. Parameters X: np.ndarray The data matrix. n_components: int The dimension of the embedding space. random_state: Union[int, RandomState] If the value is an int, random_state is the seed used by the random number generator. If the value is a RandomState instance, then it will be used as the random number generator. If the value is None, the random number generator is the RandomState instance used by `np.random`. Returns ------- initialization: np.ndarray """

    random_state = check_random_state(random_state)
    return random_state.normal(0, 1e-2, (X.shape[0], n_components))