code: def mean_or_pmean(n_devices, x, axis=None):
      """Computes the mean of a distributed value ``x``.
  
      Args:
        n_devices: Number of devices.
        x: Distributed array.
        axis: Axis along which to compute means; can only be ``0`` or ``None``.
  
      Returns:
        A local array.
      """
      if (
          fastmath.backend_name() == "tensorflow-numpy"
          and n_devices > 1
      ):
          if axis not in (None, 0):
              raise ValueError("axis can only be None or 0")
          x = fastmath.pmap(fastmath.psum)(x)[0] / n_devices
          if axis is None:
              x = jnp.mean(x)
          return x
      else:
          return jnp.mean(x, axis=axis)
  
imports: import jax
  import numpy
  from trax import fastmath
  from trax.fastmath import numpy
  from trax.layers import base
label_desc: Use image node_id 1 for calling a global function with example usage: mean_or_pmean(n_devices, x, axis) and returns: x, jnp