class_docstr: Wraps a device specification (DeviceSpec or str) with merge functionality.
  
  When called, this class will merge a node_def with its own spec. It also
  exposes a `shortcut_string_merge` method which can significantly improve
  performance of device placement.
class_docstr_tok: ["Wraps","a","device","specification","(","DeviceSpec","or","str",")","with","merge","functionality",".","When","called",",","this","class","will","merge","a","node_def","with","its","own","spec",".","It","also","exposes","a","`","shortcut_string_merge","`","method","which","can","significantly","improve","performance","of","device","placement","."]
docstr: Indicate whether the wrapped spec is empty.
  
  In the degenerate case where self._spec is an empty specification, a caller
  may wish to skip a merge step entirely. (However this class does not have
  enough information to make that determination.)
  
  Returns:
    A boolean indicating whether a device merge will be trivial.
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code: def is_null_merge(self):
      """Indicate whether the wrapped spec is empty.
  
      In the degenerate case where self._spec is an empty specification, a caller
      may wish to skip a merge step entirely. (However this class does not have
      enough information to make that determination.)
  
      Returns:
        A boolean indicating whether a device merge will be trivial.
      """
      return not bool(self._spec.to_string())
  
file_path: tensorflow/tensorflow/python/framework/device.py
imports: from tensorflow.python import tf2
  from tensorflow.python.framework import device_spec
label_desc: Use image node_id 5 for calling the MergeDevice obj's underlying member method code with example usage: obj.is_null_merge() and returns: unknown