code: def test_evaluating_multiple_outputs():
      input_data = AA([1], np.float32)
  
      a = C.input_variable(shape=input_data.shape, name="a")
      a_plus_1 = a + 1
      out1 = ((a_plus_1 + 2) - 1) + 1
      out2 = ((a_plus_1 + 4) - 1) + 2
      z = C.combine([out1, out2])
  
      # create batch
      input_data.shape = (1, 1) + input_data.shape
  
      res = z.eval({a: input_data})
  
      expected_forward_out1 = [[4.0]]
      expected_forward_out2 = [[7.0]]
      assert np.array_equal(res[out1.output], expected_forward_out1)
      assert np.array_equal(res[out2.output], expected_forward_out2)
  
imports: import numpy
  import os
  import pytest
  import cntk
  from .ops_test_utils import compare_lists_of_np_arrays, AA, cntk_device
  from cntk.io import MinibatchSource, CTFDeserializer, StreamDefs, StreamDef
label_desc: Use image node_id 9 for calling a global function with example usage: test_evaluating_multiple_outputs() without return types