def test_logger():
logger = Logger()
logger('iteration', 1)
logger('learning_rate', 1e-3)
logger('train_loss', 0.12)
logger('eval_loss', 0.14)
logger('iteration', 2)
logger('learning_rate', 5e-4)
logger('train_loss', 0.11)
logger('eval_loss', 0.13)
logger('iteration', 3)
logger('learning_rate', 1e-4)
logger('train_loss', 0.09)
logger('eval_loss', 0.10)
def check(logs):
assert len(logs) == 4
assert list(logs.keys()) == [
'iteration', 'learning_rate', 'train_loss', 'eval_loss'
]
assert logs['iteration'] == [1, 2, 3]
assert np.allclose(logs['learning_rate'], [1e-3, 5e-4, 1e-4])
assert np.allclose(logs['train_loss'], [0.12, 0.11, 0.09])
assert np.allclose(logs['eval_loss'], [0.14, 0.13, 0.10])
check(logger.logs)
logger.dump()
logger.dump(border='-' * 50)
logger.dump(keys=['iteration'])
logger.dump(keys=['iteration', 'train_loss'])
logger.dump(index=0)
logger.dump(index=[1, 2])
logger.dump(index=0)
logger.dump(keys=['iteration', 'eval_loss'], index=1)
logger.dump(keys=['iteration', 'learning_rate'], indent=1)
logger.dump(keys=['iteration', 'train_loss'],
index=[0, 2],
indent=1,
border='#' * 50)
f = Path('./logger_file')
logger.save(f)
f = f.with_suffix('.pkl')
assert f.exists()
logs = pickle_load(f)
check(logs)
f.unlink()
assert not f.exists()
logger.clear()
assert len(logger.logs) == 0
def test_logger(self):
logger = Logger(name='logger')
logger.log('iteration', 1)
logger.log('learning_rate', 1e-3)
logger.log('training_loss', 0.12)
logger.log('evaluation_loss', 0.14)
logger.log('iteration', 2)
logger.log('learning_rate', 5e-4)
logger.log('training_loss', 0.11)
logger.log('evaluation_loss', 0.13)
logger.log('iteration', 3)
logger.log('learning_rate', 1e-4)
logger.log('training_loss', 0.09)
logger.log('evaluation_loss', 0.10)
# Test dump, because dump will call print, impossible to use assert
logger.dump()
logger.dump(keys=None, index=None, indent=1)
logger.dump(keys=None, index=None, indent=2)
logger.dump(keys=['iteration', 'evaluation_loss'],
index=None,
indent=0)
logger.dump(keys=None, index=0, indent=0)
logger.dump(keys=None, index=2, indent=0)
logger.dump(keys=None, index=[0, 2], indent=0)
logger.dump(keys=['iteration', 'training_loss'],
index=[0, 2],
indent=0)
# Test save function
file = './test_logger_file'
logger.save(file=file)
assert os.path.exists(file)
# Load file
logging = Logger.load(file)
assert len(logging) == 4
assert 'iteration' in logging
assert 'learning_rate' in logging
assert 'training_loss' in logging
assert 'evaluation_loss' in logging
assert np.allclose(logging['iteration'], [1, 2, 3])
assert np.allclose(logging['learning_rate'], [1e-3, 5e-4, 1e-4])
assert np.allclose(logging['training_loss'], [0.12, 0.11, 0.09])
assert np.allclose(logging['evaluation_loss'], [0.14, 0.13, 0.1])
# Delete the temp logger file
os.unlink(file)