code: def mpi_moments(arr, axis=0, comm=None, keepdims=False):
      """
      calculates the mean and std of an array, using MPI
  
      :param arr: (np.ndarray)
      :param axis: (int or tuple or list) the axis to run the moments over
      :param comm: (MPI Communicators) if None, MPI.COMM_WORLD
      :param keepdims: (bool) keep the other dimensions intact
      :return: (np.ndarray or Number) the result of the moments
      """
      arr = np.asarray(arr)
      assert arr.ndim > 0
      mean, count = mpi_mean(arr, axis=axis, comm=comm, keepdims=True)
      sqdiffs = np.square(arr - mean)
      meansqdiff, count1 = mpi_mean(
          sqdiffs, axis=axis, comm=comm, keepdims=True
      )
      assert count1 == count
      std = np.sqrt(meansqdiff)
      if not keepdims:
          newshape = mean.shape[:axis] + mean.shape[axis + 1 :]
          mean = mean.reshape(newshape)
          std = std.reshape(newshape)
      return mean, std, count
  
imports: from mpi4py import MPI
  import numpy
  from stable_baselines.common.misc_util import zipsame
label_desc: Use image node_id 2 for calling a global function with example usage: mpi_moments(arr, axis, comm, keepdims) and returns: mean,  std,  count