code: def loglike_vectorized(z):
      a = np.array(
          [
              -0.5
              * sum(
                  [
                      ((xi - 0.7 + i * 0.001) / 0.1) ** 2
                      for i, xi in enumerate(x)
                  ]
              )
              for x in z
          ]
      )
      b = np.array(
          [
              -0.5
              * sum(
                  [
                      ((xi - 0.3 - i * 0.001) / 0.1) ** 2
                      for i, xi in enumerate(x)
                  ]
              )
              for x in z
          ]
      )
      return np.logaddexp(a, b)
  
imports: import numpy
  from ultranest.mlfriends import ScalingLayer, AffineLayer, MLFriends
  from ultranest import ReactiveNestedSampler
  from ultranest.stepsampler import RegionMHSampler, CubeMHSampler, CubeSliceSampler, RegionSliceSampler, SpeedVariableRegionSliceSampler, RegionBallSliceSampler
  from ultranest.stepsampler import generate_region_random_direction, ellipsoid_bracket, crop_bracket_at_unit_cube
  from ultranest.pathsampler import SamplingPathStepSampler
  from ultranest.stepsampler import select_random_livepoint, IslandPopulationRandomLivepointSelector
  from numpy.testing import assert_allclose
label_desc: Use image node_id 1 for calling a global function with example usage: loglike_vectorized(z) and returns: np