code: def testProductTypeInferenceNumpy(self):
      inputs = np.array([4, 5], dtype=np.int64)
      outputs = np.array(([6, 7], [7, 8]), dtype=np.int64)
      prog = test_programs.synthetic_pattern_variable_program(
          include_types=False
      )
      typed = type_inference.infer_types(prog, [inputs], NP_BACKEND)
      expected_prog = test_programs.synthetic_pattern_variable_program()
      self.assertSameTypes(expected_prog, typed)
      alloc = allocation_strategy.optimize(typed)
      lowered = lowering.lower_function_calls(alloc)
      self.assertAllEqual(
          outputs, _execute(lowered, inputs, 15, NP_BACKEND)
      )
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  import six
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.auto_batching import allocation_strategy
  from tensorflow_probability.python.experimental.auto_batching import instructions
  from tensorflow_probability.python.experimental.auto_batching import lowering
  from tensorflow_probability.python.experimental.auto_batching import numpy_backend
  from tensorflow_probability.python.experimental.auto_batching import test_programs
  from tensorflow_probability.python.experimental.auto_batching import tf_backend
  from tensorflow_probability.python.experimental.auto_batching import type_inference
  from tensorflow_probability.python.experimental.auto_batching import virtual_machine
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 3 for calling the TypeInferenceTest obj's underlying member method code with example usage: obj.testProductTypeInferenceNumpy() without return types