class_docstr: Trackable class for captured constants.
class_docstr_tok: ["Trackable","class","for","captured","constants","."]
code: def _deserialize_from_proto(
      cls, object_proto, operation_attributes, **kwargs
  ):
      tensor_proto = operation_attributes[
          object_proto.constant.operation
      ]["value"].tensor
      ndarray = tensor_util.MakeNdarray(tensor_proto)
      if dtypes.as_dtype(tensor_proto.dtype) == dtypes.string:
          with ops.device("CPU"):
              # String operations should be done on the CPU.
              imported_constant = constant_op.constant(ndarray)
      else:
          imported_constant = constant_op.constant(ndarray)
      return imported_constant
  
file_path: tensorflow-upstream/tensorflow/python/eager/polymorphic_function/saved_model_utils.py
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.saved_model import registration
  from tensorflow.python.trackable import base
label_desc: Use image node_id 4 for calling the TrackableConstant obj's underlying member method code with example usage: obj._deserialize_from_proto(cls, object_proto, operation_attributes) and returns: imported_constant