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.
code: def __del__(self):
      try:
          # Outer race condition: on program exit, the destruction context may be
          # deleted before this __del__ is called. At this point we can safely
          # exit without calling _destroy_resource() and let Python handle things.
          with self._destruction_context():
              # Inner race condition: possible between this and `ScopedTFFunction`
              # whereby if an entire garbage collection chain containing both
              # objects is moved to unreachable during the same garbage collection
              # cycle, the __del__ for `ScopedTFFunction` can be collected before
              # this method is called. In that case, we can't do much but
              # continue.
              self._destroy_resource()
      except Exception:  # pylint: disable=broad-except
          # Silence all error logs that occur when attempting to destroy this
          # resource.
          pass
  
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 13 for calling the CapturableResource obj's underlying member method code with example usage: obj.__del__() without return types