code: def test_nn_set_training_input(self):
      builder = self.create_base_builder()
  
      builder.set_mean_squared_error_loss(
          name="mse", input_feature=("output", datatypes.Array(3))
      )
  
      builder.set_adam_optimizer(
          AdamParams(
              lr=1e-2, batch=10, beta1=0.9, beta2=0.999, eps=1e-8
          )
      )
      builder.set_epochs(20, allowed_set=[10, 20, 30])
  
      model_path = os.path.join(
          self.model_dir, "updatable_creation.mlmodel"
      )
      print(model_path)
      save_spec(builder.spec, model_path)
  
      mlmodel = MLModel(model_path)
      self.assertTrue(mlmodel is not None)
      spec = mlmodel.get_spec()
      self.assertEqual(spec.description.trainingInput[0].name, "input")
      self.assertEqual(
          spec.description.trainingInput[0].type.WhichOneof("Type"),
          "multiArrayType",
      )
      self.assertEqual(
          spec.description.trainingInput[1].name, "output_true"
      )
      self.assertEqual(
          spec.description.trainingInput[1].type.WhichOneof("Type"),
          "multiArrayType",
      )
  
imports: import os
  import shutil
  import tempfile
  import unittest
  import numpy
  import coremltools.models.datatypes
  from coremltools.models import MLModel
  from coremltools.models.neural_network import AdamParams, NeuralNetworkBuilder, SgdParams, quantization_utils
  from coremltools.models.pipeline import PipelineClassifier, PipelineRegressor
  from coremltools.models.utils import save_spec
label_desc: Use image node_id 11 for calling the MLModelUpdatableTest obj's underlying member method code with example usage: obj.test_nn_set_training_input() without return types