code: def set_soft_device_placement(enabled):
      """Enable or disable soft device placement.
  
      If enabled, ops can be placed on different devices than the device explicitly
      assigned by the user. This potentially has a large performance cost due to an
      increase in data communication between devices.
  
      Some cases where soft_device_placement would modify device assignment are:
        1. no GPU/TPU implementation for the OP
        2. no GPU devices are known or registered
        3. need to co-locate with reftype input(s) which are from CPU
        4. an OP can not be compiled by XLA.  Common for TPU which always requires
             the XLA compiler.
  
      For TPUs, if this option is true, a feature called automatic outside
      compilation is enabled. Automatic outside compilation will move uncompilable
      ops within a TPU program to instead run on the host. This can be used when
      encountering compilation failures due to unsupported ops.
  
      Note: by default soft device placement is enabled when running in eager mode
      (for convenience) and disabled in graph mode (for performance).
  
      Args:
        enabled: A boolean indicating whether to enable soft placement.
      """
      context.context().soft_device_placement = enabled
  
imports: from typing import Union
  from tensorflow.python.eager import context
  from tensorflow.python.framework import errors
  from tensorflow.python.util import _pywrap_determinism
  from tensorflow.python.util import _pywrap_tensor_float_32_execution
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 12 for calling a global function with example usage: set_soft_device_placement(enabled) without return types