class_docstr: Indicates a position within a `_CheckpointRestoreCoordinator`.
class_docstr_tok: ["Indicates","a","position","within","a","`","_CheckpointRestoreCoordinator","`","."]
docstr: Creates a saveable using the _serialize_to_tensor method.
docstr_tok: ["Creates","a","saveable","using","the","_serialize_to_tensor","method","."]
code: def _create_serialize_to_tensor_saveable(self, saveable_factories):
      """Creates a saveable using the _serialize_to_tensor method."""
      # Extract the saveable name from the checkpoint key. This will be used as
      # the cache key or the name to pass to the saveable factory.
      suffix = saveable_compat.get_saveable_name(self.trackable) or ""
      saveable_name = (
          _extract_saveable_name(
              self.object_proto.attributes[0].checkpoint_key
          )
          + suffix
      )
  
      # Try to find the cached saveable (only in graph mode).
      if not context.executing_eagerly():
          existing_op = self._checkpoint.restore_ops_by_name.get(
              saveable_name, None
          )
          if existing_op is not None:
              return [existing_op], {}
  
          saveables_cache = self._checkpoint.saveables_cache.setdefault(
              self.trackable, {}
          )
          if saveable_name in saveables_cache:
              return [], {saveable_name: saveables_cache[saveable_name]}
  
      saveable = saveable_factories[
          trackable_utils.SERIALIZE_TO_TENSORS_NAME
      ](name=saveable_name)
      if not context.executing_eagerly():
          saveables_cache[saveable_name] = saveable
      return [], {saveable_name: saveable}
  
imports: import collections
  from tensorflow.python.checkpoint import checkpoint_view
  from tensorflow.python.checkpoint import functional_saver
  from tensorflow.python.checkpoint import save_util_v1
  from tensorflow.python.checkpoint import saveable_compat
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_io_ops
  from tensorflow.python.ops import io_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.saved_model import registration
  from tensorflow.python.trackable import base
  from tensorflow.python.trackable import constants
  from tensorflow.python.trackable import python_state
  from tensorflow.python.trackable import trackable_utils
  from tensorflow.python.training.saving import saveable_object_util
  from tensorflow.python.util import object_identity
label_desc: Use image node_id 7 for calling the CheckpointPosition obj's underlying member method code with example usage: obj._create_serialize_to_tensor_saveable(saveable_factories) and returns: list,  dict, list,  dict, list,  dict