code: def test_convert_nn_spec_to_half_precision(self):
      # simple network with quantization layer
      input_features = [("data", datatypes.Array(3))]
      output_features = [("out", datatypes.Array(3))]
      builder = NeuralNetworkBuilder(input_features, output_features)
      weights = np.random.uniform(-0.5, 0.5, (3, 3))
      builder.add_inner_product(
          name="inner_product",
          W=weights,
          b=None,
          input_channels=3,
          output_channels=3,
          has_bias=False,
          input_name="data",
          output_name="out",
      )
      model = MLModel(builder.spec)
      spec = _convert_neural_network_spec_weights_to_fp16(
          model.get_spec()
      )
      self.assertIsNotNone(spec)
  
      # simple network without quantization layer
      input_features = [("data", datatypes.Array(3))]
      output_features = [("out", datatypes.Array(3))]
      builder = NeuralNetworkBuilder(input_features, output_features)
      builder.add_lrn(
          name="lrn",
          input_name="data",
          output_name="out",
          alpha=2,
          beta=3,
          local_size=1,
          k=8,
      )
      model = MLModel(builder.spec)
      spec = _convert_neural_network_spec_weights_to_fp16(
          model.get_spec()
      )
      self.assertIsNotNone(spec)
  
imports: import os
  import tempfile
  import unittest
  import numpy
  import PIL.Image
  import coremltools
  from coremltools import ComputeUnit
  from coremltools._deps import _HAS_TORCH
  from coremltools.converters.mil import Builder
  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
  from coremltools.models.utils import _convert_neural_network_spec_weights_to_fp16, _is_macos, _macos_version, convert_double_to_float_multiarray_type, rename_feature, save_spec
  from coremltools.proto import Model_pb2
label_desc: Use image node_id 12 for calling the MLModelTest obj's underlying member method code with example usage: obj.test_convert_nn_spec_to_half_precision() without return types