code: def gen_data(num_classes, num_samples, dim):
      np.random.seed(0)
      covs = np.array(
          [
              [[0.0, -1.0], [2.5, 0.7]],
              [[3.0, -1.5], [1.2, 0.3]],
              [[2, 0], [0.0, 1.5]],
          ]
      )
      X = np.r_[
          np.dot(np.random.randn(num_samples, dim), covs[0])
          + np.array([0, 10]),
          np.dot(np.random.randn(num_samples, dim), covs[1])
          + np.array([-10, -10]),
          np.dot(np.random.randn(num_samples, dim), covs[2])
          + np.array([10, -10]),
      ]
      Y = np.hstack(
          (
              np.zeros(num_samples),
              np.ones(num_samples),
              2 * np.ones(num_samples),
          )
      )
      return X, Y
  
label_desc: Use image node_id 1 for calling a global function with example usage: gen_data(num_classes, num_samples, dim) and returns: X,  Y