code: def make_euclidean_hyperplane(data, indices, rng_state):
      left_index = tau_rand_int(rng_state) % indices.shape[0]
      right_index = tau_rand_int(rng_state) % indices.shape[0]
      right_index += left_index == right_index
      right_index = right_index % indices.shape[0]
      left = indices[left_index]
      right = indices[right_index]
  
      # Compute the normal vector to the hyperplane (the vector between
      # the two points) and the offset from the origin
      hyperplane_offset = 0.0
      hyperplane_vector = np.empty(data.shape[1], dtype=np.float32)
  
      for d in range(data.shape[1]):
          hyperplane_vector[d] = data[left, d] - data[right, d]
          hyperplane_offset -= (
              hyperplane_vector[d]
              * (data[left, d] + data[right, d])
              / 2.0
          )
  
      return hyperplane_vector, hyperplane_offset
  
imports: import numpy
  import numba
  from pynndescent.utils import tau_rand_int, norm
label_desc: Use image node_id 2 for calling a global function with example usage: make_euclidean_hyperplane(data, indices, rng_state) and returns: hyperplane_vector,  hyperplane_offset