def test_invalid_input_experiment(self):
r"""Raise exception when input `experiment` is invalid."""
msg1 = (
'Must raise `FileNotFoundError`, `TypeError` or `ValueError` when '
'input `experiment` is invalid.')
msg2 = 'Inconsistent error message.'
examples = (False, True, 0, 1, -1, 0.0, 1.0, math.nan, -math.nan,
math.inf, -math.inf,
0j, 1j, '', 'I-DO-NOT-EXIST', b'', (), [], {}, set(),
object(), lambda x: x, type, None, NotImplemented, ...)
for invalid_input in examples:
with self.assertRaises((FileNotFoundError, TypeError, ValueError),
msg=msg1) as ctx_man:
BaseConfig.load(experiment=invalid_input)
if isinstance(ctx_man.exception, FileNotFoundError):
file_path = os.path.join(lmp.path.DATA_PATH, invalid_input,
'config.json')
self.assertEqual(ctx_man.exception.args[0],
f'File {file_path} does not exist.',
msg=msg2)
elif isinstance(ctx_man.exception, TypeError):
self.assertEqual(ctx_man.exception.args[0],
'`experiment` must be an instance of `str`.',
msg=msg2)
else:
self.assertEqual(ctx_man.exception.args[0],
'`experiment` must not be empty.',
msg=msg2)
def test_invalid_json(self):
r"""Raise `JSONDecodeError` when configuration is invalid."""
msg = (
'Must raise `JSONDecodeError` when configuration is not in JSON '
'format.')
test_path = os.path.join(self.__class__.test_dir, 'config.json')
try:
# Create test file.
with open(test_path, 'w', encoding='utf-8') as output_file:
output_file.write('Invalid JSON format.')
with self.assertRaises(json.JSONDecodeError, msg=msg):
BaseConfig.load(experiment=self.__class__.experiment)
finally:
# Clean up test file.
os.remove(test_path)
def test_load_result(self):
r"""Load result must be consistent."""
msg = 'Inconsistent load result.'
examples = (
{
'batch_size': 111,
'checkpoint_step': 222,
'd_emb': 333,
'd_hid': 444,
'dataset': 'hello',
'dropout': 0.42069,
'epoch': 555,
'experiment': 'world',
'is_uncased': True,
'learning_rate': 0.69420,
'max_norm': 6.9,
'max_seq_len': 666,
'min_count': 777,
'model_class': 'HELLO',
'num_linear_layers': 888,
'num_rnn_layers': 999,
'optimizer_class': 'WORLD',
'seed': 101010,
'tokenizer_class': 'hello world',
},
{
'batch_size': 101010,
'checkpoint_step': 999,
'd_emb': 888,
'd_hid': 777,
'dataset': 'world',
'dropout': 0.69420,
'epoch': 666,
'experiment': 'hello',
'is_uncased': True,
'learning_rate': 0.42069,
'max_norm': 4.20,
'max_seq_len': 555,
'min_count': 444,
'model_class': 'hello world',
'num_linear_layers': 333,
'num_rnn_layers': 222,
'optimizer_class': 'WORLD',
'seed': 111,
'tokenizer_class': 'HELLO',
},
)
for attributes in examples:
test_path = os.path.join(self.__class__.test_dir, 'config.json')
try:
# Create test file.
with open(test_path, 'w', encoding='utf-8') as output_file:
json.dump(attributes, output_file)
config = BaseConfig.load(experiment=self.__class__.experiment)
self.assertIsInstance(config, BaseConfig)
for attr_key, attr_value in attributes.items():
self.assertTrue(hasattr(config, attr_key), msg=msg)
self.assertIsInstance(getattr(config, attr_key),
type(attr_value),
msg=msg)
self.assertEqual(getattr(config, attr_key),
attr_value,
msg=msg)
finally:
# Clean up test file.
os.remove(test_path)