code: def random(X, n_components=2, random_state=None):
      
      random_state = check_random_state(random_state)
      return random_state.normal(0, 1e-2, (X.shape[0], n_components))
docs: 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