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())