class_docstr: Represents an initialization operation restored from a SavedModel.
  
  Without this object re-export of imported 1.x SavedModels would omit the
  original SavedModel's initialization procedure.
  
  Created when `tf.saved_model.load` loads a TF 1.x-style SavedModel with an
  initialization op. This object holds a function that runs the
  initialization. It does not require any manual user intervention;
  `tf.saved_model.save` will see this object and automatically add it to the
  exported SavedModel, and `tf.saved_model.load` runs the initialization
  function automatically.
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code: def _initialize(self):
      return self._init_fn(
          *[path.asset_path for path in self._asset_paths]
      )
  
imports: import functools
  from tensorflow.python.eager import context
  from tensorflow.python.eager import lift_to_graph
  from tensorflow.python.eager import wrap_function
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.saved_model import function_deserialization
  from tensorflow.python.saved_model import loader_impl
  from tensorflow.python.saved_model import signature_serialization
  from tensorflow.python.saved_model.pywrap_saved_model import metrics
  from tensorflow.python.trackable import asset
  from tensorflow.python.trackable import autotrackable
  from tensorflow.python.trackable import resource
  from tensorflow.python.training import monitored_session
  from tensorflow.python.training import saver
  from tensorflow.python.util import nest
label_desc: Use image node_id 3 for calling the _Initializer obj's underlying member method code with example usage: obj._initialize() and returns: self