message: Add test showing conversion from an intermediate input array.
diff: @@ -177,6 +177,38 @@ class FromSessionTest(test_util.TensorFlowTestCase):
  'Quantization input stats are not available for input tensors '
  '\'inputB\'.', str(error.exception))
  + def testIntermediateInputArray(self):
  + """Convert a model from an intermediate input array."""
  + in_tensor_init = array_ops.placeholder(
  + shape=[1, 16, 16, 3], dtype=dtypes.float32)
  + in_tensor_final = in_tensor_init + in_tensor_init
  + out_tensor = in_tensor_final + in_tensor_final
  + sess = session.Session()
  +
  + # Convert model and ensure model is not None.
  + converter = lite.TFLiteConverter.from_session(sess, [in_tensor_final],
  + [out_tensor])
  + tflite_model = converter.convert()
  + self.assertTrue(tflite_model)
  +
  + # Check values from converted model.
  + interpreter = Interpreter(model_content=tflite_model)
  + interpreter.allocate_tensors()
  +
  + input_details = interpreter.get_input_details()
  + self.assertEqual(1, len(input_details))
  + self.assertEqual('add', input_details[0]['name'])
  + self.assertEqual(np.float32, input_details[0]['dtype'])
  + self.assertTrue(([1, 16, 16, 3] == input_details[0]['shape']).all())
  + self.assertEqual((0., 0.), input_details[0]['quantization'])
  +
  + output_details = interpreter.get_output_details()
  + self.assertEqual(1, len(output_details))
  + self.assertEqual('add_1', output_details[0]['name'])
  + self.assertEqual(np.float32, output_details[0]['dtype'])
  + self.assertTrue(([1, 16, 16, 3] == output_details[0]['shape']).all())
  + self.assertEqual((0., 0.), output_details[0]['quantization'])
  +
  def testSizeNoneInvalid(self):
  in_tensor = array_ops.placeholder(dtype=dtypes.float32)
  out_tensor = in_tensor + in_tensor
  