def test_flush_writes_to_stream(self, mocker):
logger = TrainingLogger()
stream = mocker.Mock()
stream_handler = StreamHandler('epoch',
stream=stream,
fmt='* {values}')
logger.register_handler('handler', stream_handler)
logger.register_value('value', ['handler'])
with logger.scope():
logger.log_value('value', 1)
logger.log_value('value', 0.1)
stream.write.assert_called_once_with('* value 0.1000\n')
assert stream.flush.call_count == 1
def test_instant_values_displayed(self, mocker):
logger = TrainingLogger()
stream = mocker.Mock()
stream_handler = StreamHandler('batch',
stream=stream,
fmt='* {values}')
logger.register_handler('handler', stream_handler)
logger.register_value('value', ['handler'], average=True)
for i, x in logger.scope_enumerate(range(1, 4)):
logger.log_value('value', x)
assert stream.write.call_count == 3
stream.write.assert_has_calls([
mocker.call('* value 1.0000 (1.0000)\n'),
mocker.call('* value 2.0000 (1.5000)\n'),
mocker.call('* value 3.0000 (2.0000)\n'),
])
def setup_logging(args):
logger = TrainingLogger()
# Create handlers
logger.register_handler("val_batch", StreamHandler(prefix='Val: ', scope='batch'))
logger.register_handler("val_epoch", StreamHandler(fmt="* {epoch} epochs done: {values}", scope='epoch',
display_instant=False))
logger.register_handler("test_std", StreamHandler(fmt="Testing: [{step}/{total}]\t{values}",
scope='batch'))
logger.register_handler("test_end", StreamHandler(fmt="* Testing results: {values}", scope='epoch',
display_instant=False))
logger.register_handler("train_epoch", StreamHandler(fmt="* Train epoch {epoch} done: {values}", scope='epoch'))
logger.register_handler("train_batch", StreamHandler(prefix='Train: ', scope='batch'))
logger.register_handler("tb", TensorboardHandler(scope='epoch', summary_writer=args.writer))
logger.register_handler("tb_global", TensorboardHandler(scope='global', summary_writer=args.writer))
logger.register_handler("val_csv", CSVHandler(scope='epoch', csv_path=(args.result_path / 'val.csv'),
index_col='epoch'))
logger.register_handler("train_csv", CSVHandler(scope='epoch', csv_path=(args.result_path / 'train.csv'),
index_col='epoch'))
# Create logged values
logger.register_value("train/acc", ['train_batch', 'tb_global'], average=True, display_name='clip')
logger.register_value("train/loss", ['train_batch', 'tb_global'], average=True, display_name='loss')
logger.register_value("train/kd_loss", ['train_batch', 'tb_global'], average=True, display_name='loss')
logger.register_value("train/epoch_acc", ['train_epoch', 'tb', 'train_csv'], display_name='clip')
logger.register_value("train/epoch_loss", ['train_epoch', 'tb', 'train_csv'], display_name='loss')
logger.register_value_group("lr/.*", ['tb'])
logger.register_value("time/train_data", ['train_batch'], average=True, display_name='data time')
logger.register_value("time/train_step", ['train_batch'], average=True, display_name='time')
logger.register_value("time/train_epoch", ['train_epoch'], display_name='Train epoch time')
logger.register_value("val/acc", ['val_batch', 'val_epoch', 'tb', 'val_csv'], average=True, display_name='clip')
logger.register_value("val/video", ['val_batch', 'val_epoch', 'tb', 'val_csv'], average=False, display_name='video')
logger.register_value("val/loss", ['val_batch', 'tb', 'val_csv'], average=True, display_name='loss')
logger.register_value("val/generalization_error", ['val_epoch', 'tb', 'val_csv'],
display_name='Train Val accuracy gap')
logger.register_value("time/val_data", ['val_batch'], average=True, display_name='data time')
logger.register_value("time/val_step", ['val_batch'], average=True, display_name='time')
logger.register_value("time/val_epoch", ['val_epoch'], average=False, display_name='Validation time')
logger.register_value("test/acc", ['test_std', 'test_end', 'tb'], average=True, display_name='clip')
logger.register_value("test/video", ['test_std', 'test_end', 'tb'], average=False, display_name='video')
return logger