def testInvalidConstructor(self): message = ( 'If input_tensors and output_tensors are None, both ' 'input_arrays_with_shape and output_arrays must be defined.') # `output_arrays` is not defined. with self.assertRaises(ValueError) as error: lite.TocoConverter(None, None, [], input_arrays_with_shape=[('input', [3, 9])]) self.assertEqual(message, str(error.exception)) # `input_arrays_with_shape` is not defined. with self.assertRaises(ValueError) as error: lite.TocoConverter(None, [], None, output_arrays=['output']) self.assertEqual(message, str(error.exception))
def testValidConstructor(self): converter = lite.TocoConverter(None, None, None, input_arrays_with_shape=[('input', [3, 9])], output_arrays=['output']) self.assertFalse(converter._has_valid_tensors()) self.assertEqual(converter.get_input_arrays(), ['input']) with self.assertRaises(ValueError) as error: converter._set_batch_size(1) self.assertEqual( 'The batch size cannot be set for this model. Please use ' 'input_shapes parameter.', str(error.exception)) converter = lite.TocoConverter(None, ['input_tensor'], ['output_tensor']) self.assertTrue(converter._has_valid_tensors())