def test_invalid_num_lines_leads_to_disabling_progress_bar(num_lines, caplog):
for _ in ProgressBar(TEST_RANGE, num_lines=num_lines):
pass
assert len(caplog.records) == 1
record = next(iter(caplog.records))
assert record.levelno == logging.WARNING
def test_invalid_total_leads_to_disabling_progress_bar(total, caplog):
for _ in ProgressBar(TEST_RANGE, total=total):
pass
assert len(caplog.records) == 1
record = next(iter(caplog.records))
assert record.levelno == logging.WARNING
def test_can_print_by_default__with_enumerate_and_total(caplog):
for _ in ProgressBar(enumerate(TEST_RANGE), total=3.0):
pass
assert caplog.record_tuples == [('nncf', 20, ' █████ | 1 / 3'),
('nncf', 20, ' ██████████ | 2 / 3'),
('nncf', 20, ' ████████████████ | 3 / 3')]
def test_can_print_by_default(caplog):
for _ in ProgressBar(TEST_RANGE):
pass
assert caplog.record_tuples == [('nncf', 20, ' █████ | 1 / 3'),
('nncf', 20, ' ██████████ | 2 / 3'),
('nncf', 20, ' ████████████████ | 3 / 3')]
def test_can_iterate_with_warning_for_iterable_without_len(caplog):
for _ in ProgressBar(enumerate(TEST_RANGE)):
pass
assert len(caplog.records) == 1
record = next(iter(caplog.records))
assert record.levelno == logging.WARNING
def test_can_print_collections_bigger_than_num_lines(caplog):
for _ in ProgressBar(range(11), num_lines=3):
pass
assert caplog.record_tuples == [
('nncf', 20, ' ███████ | 5 / 11'),
('nncf', 20, ' ██████████████ | 10 / 11'),
('nncf', 20, ' ████████████████ | 11 / 11')
]
def test_can_print_with_another_logger(caplog):
name = "test"
logger = logging.getLogger(name)
logger.setLevel(logging.INFO)
for _ in ProgressBar(enumerate(TEST_RANGE), logger=logger, total=2):
pass
assert caplog.record_tuples == [('test', 20, ' ████████ | 1 / 2'),
('test', 20, ' ████████████████ | 2 / 2')]
def test_can_print_collections_less_than_num_lines(caplog):
desc = 'desc'
for _ in ProgressBar(TEST_RANGE, desc=desc, num_lines=4):
pass
assert caplog.record_tuples == [
('nncf', 20, 'desc █████ | 1 / 3'),
('nncf', 20, 'desc ██████████ | 2 / 3'),
('nncf', 20, 'desc ████████████████ | 3 / 3')
]
def _run_model_inference(self, data_loader, num_init_steps, device):
for i, loaded_item in ProgressBar(
enumerate(data_loader),
total=num_init_steps,
desc=self.progressbar_description,
):
if num_init_steps is not None and i >= num_init_steps:
break
args_kwargs_tuple = data_loader.get_inputs(loaded_item)
self._infer_batch(args_kwargs_tuple, device)
def _run_model_inference(self, data_loader, num_init_steps, device):
num_bn_forget_steps = self.num_bn_forget_steps
def set_bn_momentum(module, momentum_value):
module.momentum = momentum_value
def save_original_bn_momenta(module):
self.original_momenta_values[module] = module.momentum
def restore_original_bn_momenta(module):
module.momentum = self.original_momenta_values[module]
with training_mode_switcher(self.model, is_training=True):
self.model.apply(
self._apply_to_batchnorms(save_original_bn_momenta))
self.model.apply(
self._apply_to_batchnorms(
partial(set_bn_momentum,
momentum_value=self.momentum_bn_forget)))
for i, loaded_item in enumerate(data_loader):
if num_bn_forget_steps is not None and i >= num_bn_forget_steps:
break
args_kwargs_tuple = data_loader.get_inputs(loaded_item)
self._infer_batch(args_kwargs_tuple, device)
self.model.apply(
self._apply_to_batchnorms(restore_original_bn_momenta))
for i, loaded_item in ProgressBar(
enumerate(data_loader),
total=num_init_steps,
desc=self.progressbar_description):
if num_init_steps is not None and i >= num_init_steps:
break
args_kwargs_tuple = data_loader.get_inputs(loaded_item)
self._infer_batch(args_kwargs_tuple, device)
def test_type_error_happens_for_iteration_none(caplog):
with pytest.raises(TypeError):
for _ in ProgressBar(None):
pass
def test_can_iterate_over_empty_iterable(caplog):
for _ in ProgressBar([]):
pass
assert caplog.record_tuples == []
def test_can_limit_number_of_iterations(caplog):
for _ in ProgressBar(TEST_RANGE, total=2):
pass
assert caplog.record_tuples == [('nncf', 20, ' ████████ | 1 / 2'),
('nncf', 20, ' ████████████████ | 2 / 2')]