def train(datasets, model, loss, optimizer, meters, args):
task = (ClassificationTask()
.set_num_epochs(args.num_epochs)
.set_loss(loss)
.set_model(model)
.set_optimizer(optimizer)
.set_meters(meters))
for phase in ["train", "test"]:
task.set_dataset(datasets[phase], phase)
hooks = [LossLrMeterLoggingHook(log_freq=args.print_freq)]
# show progress
hooks.append(ProgressBarHook())
if not args.skip_tensorboard:
try:
from tensorboardX import SummaryWriter
tb_writer = SummaryWriter(log_dir=args.video_dir + "/tensorboard")
hooks.append(TensorboardPlotHook(tb_writer))
except ImportError:
print("tensorboardX not installed, skipping tensorboard hooks")
checkpoint_dir = f"{args.video_dir}/checkpoint/classy_checkpoint_{time.time()}"
os.mkdir(checkpoint_dir)
hooks.append(CheckpointHook(checkpoint_dir, input_args={}))
task = task.set_hooks(hooks)
trainer = LocalTrainer(use_gpu=args.cuda, num_dataloader_workers=args.num_workers)
trainer.train(task)
def configure_hooks(args, config):
hooks = [LossLrMeterLoggingHook(args.log_freq), ModelComplexityHook()]
# Make a folder to store checkpoints and tensorboard logging outputs
suffix = datetime.now().isoformat()
base_folder = f"{Path(__file__).parent}/output_{suffix}"
if args.checkpoint_folder == "":
args.checkpoint_folder = base_folder + "/checkpoints"
os.makedirs(args.checkpoint_folder, exist_ok=True)
logging.info(f"Logging outputs to {base_folder}")
logging.info(f"Logging checkpoints to {args.checkpoint_folder}")
if not args.skip_tensorboard:
try:
from torch.utils.tensorboard import SummaryWriter
os.makedirs(Path(base_folder) / "tensorboard", exist_ok=True)
tb_writer = SummaryWriter(log_dir=Path(base_folder) /
"tensorboard")
hooks.append(TensorboardPlotHook(tb_writer))
except ImportError:
logging.warning(
"tensorboard not installed, skipping tensorboard hooks")
args_dict = vars(args)
args_dict["config"] = config
hooks.append(
CheckpointHook(args.checkpoint_folder,
args_dict,
checkpoint_period=args.checkpoint_period))
if args.profiler:
hooks.append(ProfilerHook())
if args.show_progress:
hooks.append(ProgressBarHook())
if args.visdom_server != "":
hooks.append(VisdomHook(args.visdom_server, args.visdom_port))
return hooks
def test_progress_bar(self, mock_is_master: mock.MagicMock,
mock_progressbar_pkg: mock.MagicMock) -> None:
"""
Tests that the progress bar is created, updated and destroyed correctly.
"""
mock_progress_bar = mock.create_autospec(progressbar.ProgressBar,
instance=True)
mock_progressbar_pkg.ProgressBar.return_value = mock_progress_bar
mock_is_master.return_value = True
task = get_test_classy_task()
task.prepare()
task.advance_phase()
num_batches = task.num_batches_per_phase
# make sure we are checking at least one batch
self.assertGreater(num_batches, 0)
# create a progress bar hook
progress_bar_hook = ProgressBarHook()
# progressbar.ProgressBar should be init-ed with num_batches
progress_bar_hook.on_phase_start(task)
mock_progressbar_pkg.ProgressBar.assert_called_once_with(num_batches)
mock_progress_bar.start.assert_called_once_with()
mock_progress_bar.start.reset_mock()
mock_progressbar_pkg.ProgressBar.reset_mock()
# on_step should update the progress bar correctly
for i in range(num_batches):
progress_bar_hook.on_step(task)
mock_progress_bar.update.assert_called_once_with(i + 1)
mock_progress_bar.update.reset_mock()
# check that even if on_step is called again, the progress bar is
# only updated with num_batches
for _ in range(num_batches):
progress_bar_hook.on_step(task)
mock_progress_bar.update.assert_called_once_with(num_batches)
mock_progress_bar.update.reset_mock()
# finish should be called on the progress bar
progress_bar_hook.on_phase_end(task)
mock_progress_bar.finish.assert_called_once_with()
mock_progress_bar.finish.reset_mock()
# check that even if the progress bar isn't created, the code doesn't
# crash
progress_bar_hook = ProgressBarHook()
try:
progress_bar_hook.on_step(task)
progress_bar_hook.on_phase_end(task)
except Exception as e:
self.fail(
"Received Exception when on_phase_start() isn't called: {}".
format(e))
mock_progressbar_pkg.ProgressBar.assert_not_called()
# check that a progress bar is not created if is_master() returns False
mock_is_master.return_value = False
progress_bar_hook = ProgressBarHook()
try:
progress_bar_hook.on_phase_start(task)
progress_bar_hook.on_step(task)
progress_bar_hook.on_phase_end(task)
except Exception as e:
self.fail(
"Received Exception when is_master() is False: {}".format(e))
self.assertIsNone(progress_bar_hook.progress_bar)
mock_progressbar_pkg.ProgressBar.assert_not_called()
