code: def test_undefined_shape_single_output(self):
      W = np.ones((3, 3))
      input_features = [("data", datatypes.Array(3))]
      output_features = [("probs", None)]
      builder = NeuralNetworkBuilder(input_features, output_features)
      builder.add_inner_product(
          name="ip1",
          W=W,
          b=None,
          input_channels=3,
          output_channels=3,
          has_bias=False,
          input_name="data",
          output_name="probs",
      )
      mlmodel = MLModel(builder.spec)
      data = np.ones((3,))
      data_dict = {"data": data}
      probs = mlmodel.predict(data_dict)["probs"]
      self.assertTrue(np.allclose(probs, np.ones(3) * 3))
  
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 2 for calling the BasicNumericCorrectnessTest obj's underlying member method code with example usage: obj.test_undefined_shape_single_output() without return types