code: def _test_model(self, model, input_dict, output_ref, delta=1e-2):
      preds = model.predict(input_dict)
      for name in output_ref:
          ref_val = output_ref[name]
          val = preds[name]
          self.assertTrue(np.allclose(val, ref_val, rtol=delta))
  
imports: import numpy
  import pytest
  import unittest
  import coremltools
  from coremltools import ComputeUnit
  from coremltools.converters.mil.mil.types.type_mapping import np_val_to_py_type
  from coremltools.models import MLModel, datatypes
  from coremltools.models.neural_network import NeuralNetworkBuilder
  from coremltools.models.neural_network.quantization_utils import _convert_array_to_nbit_quantized_bytes, quantize_weights
  from coremltools.models.utils import _is_macos, _macos_version
label_desc: Use image node_id 3 for calling the ControlFlowCorrectnessTest obj's underlying member method code with example usage: obj._test_model(model, input_dict, output_ref, delta) without return types