code: def _maybe_float32(o):
      if o.dtype == np.float64:
          return _as_float32_array(o)
      return o
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import numpy
  import tensorflow
  from tf_agents.environments import wrappers
  from tf_agents.specs import array_spec
  from tf_agents.trajectories import time_step
label_desc: Use image node_id 1 for calling a global function with example usage: _maybe_float32(o) and returns: o, _as_float32_array