code: def _accelerate(f, n_devices):
      """Returns an accelerated version of ``f`` running on ``n_devices``."""
      if n_devices == 0:  # no accelerators - run on CPU
          return fastmath.jit(
              f, device=jax.local_devices(backend="cpu")[0]
          )
  
      if n_devices == 1:
          return fastmath.jit(f)
  
      return fastmath.pmap(f, axis_name="batch")
  
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 4 for calling a global function with example usage: _accelerate(f, n_devices) and returns: fastmath, fastmath, fastmath