class_docstr: Holds a Tensor which a tf.function can capture.
  
  `CapturableResource`s are discovered by traversing the graph of object
  attributes, e.g. during `tf.saved_model.save`. They are excluded from the
  scope-based tracking of `TrackableResource`; generally things that require
  initialization should inherit from `TrackableResource` instead of
  `CapturableResource` directly.
docstr: Returns the resource handle associated with this Resource.
docstr_tok: ["Returns","the","resource","handle","associated","with","this","Resource","."]
code: def resource_handle(self):
      """Returns the resource handle associated with this Resource."""
      if self._resource_handle is None:
          with ops.device(self._resource_device):
              self._resource_handle = self._create_resource()
      return self._resource_handle
  
imports: import contextlib
  import copy
  import weakref
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.trackable import base
  from tensorflow.python.util import tf_contextlib
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 10 for calling the CapturableResource obj's underlying member method code with example usage: obj.resource_handle() and returns: self