code: def test_rename_input(self):
      rename_feature(
          self.spec, "feature_1", "renamed_feature", rename_inputs=True
      )
      model = MLModel(self.spec)
      preds = model.predict({"renamed_feature": 1.0, "feature_2": 1.0})
      self.assertIsNotNone(preds)
      self.assertEqual(preds["output"], 3.1)
      # reset the spec for next run
      rename_feature(
          self.spec, "renamed_feature", "feature_1", rename_inputs=True
      )
  
imports: import coremltools
  import pytest
  import unittest
  import tempfile
  import numpy
  from coremltools.proto import Model_pb2
  import PIL.Image
  from coremltools.models.utils import rename_feature, save_spec, _macos_version, _convert_neural_network_spec_weights_to_fp16, _is_macos, convert_double_to_float_multiarray_type
  from coremltools.models import MLModel, datatypes
  from coremltools.models.neural_network import NeuralNetworkBuilder
  from coremltools.models.neural_network.utils import make_image_input, make_nn_classifier
label_desc: Use image node_id 5 for calling the MLModelTest obj's underlying member method code with example usage: obj.test_rename_input() without return types