def test_batch_metrics_visdom(self, mock_visdom, mock_writer, _): mock_writer.return_value = Mock() mock_writer.return_value.add_scalar = Mock() state = { torchbearer.MODEL: nn.Sequential(nn.Conv2d(3, 3, 3)), torchbearer.EPOCH: 0, torchbearer.METRICS: { 'test': 1 }, torchbearer.BATCH: 0, torchbearer.TRAIN_STEPS: 0 } tboard = TensorBoard(visdom=True, write_batch_metrics=True, write_epoch_metrics=False) tboard.on_start(state) tboard.on_start_epoch(state) tboard.on_step_training(state) mock_writer.return_value.add_scalar.assert_called_once_with( 'test', 1, 0, main_tag='batch') mock_writer.return_value.add_scalar.reset_mock() tboard.on_step_validation(state) mock_writer.return_value.add_scalar.assert_called_once_with( 'test', 1, 0, main_tag='batch') tboard.on_end_epoch(state) tboard.on_end(state)
def test_batch_metrics(self, mock_board): mock_board.return_value = Mock() mock_board.return_value.add_scalar = Mock() state = {torchbearer.EPOCH: 0, torchbearer.METRICS: {'test': 1}, torchbearer.BATCH: 0} tboard = TensorBoard(write_batch_metrics=True, write_epoch_metrics=False) tboard.on_start_epoch(state) tboard.on_step_training(state) mock_board.return_value.add_scalar.assert_called_once_with('batch/test', 1, 0) mock_board.return_value.add_scalar.reset_mock() tboard.on_step_validation(state) mock_board.return_value.add_scalar.assert_called_once_with('batch/test', 1, 0)
def test_batch_metrics(self, mock_board): mock_board.return_value = Mock() mock_board.return_value.add_scalar = Mock() state = { torchbearer.EPOCH: 0, torchbearer.METRICS: { 'test': 1 }, torchbearer.BATCH: 0 } tboard = TensorBoard(write_batch_metrics=True, write_epoch_metrics=False) tboard.on_start_epoch(state) tboard.on_step_training(state) mock_board.return_value.add_scalar.assert_called_once_with( 'batch/test', 1, 0) mock_board.return_value.add_scalar.reset_mock() tboard.on_step_validation(state) mock_board.return_value.add_scalar.assert_called_once_with( 'batch/test', 1, 0)