def test_torch_nn_loss() :
trainer = DefaultTrainer(
optimizer=optimizer,
scheduler=scheduler,
model=model,
criterion=loss_fn,
experiment_logger=experiment_logger
)
def test_construct_from_dict():
trainer = DefaultTrainer(
optimizer=optimizer,
scheduler=scheduler,
model=model,
criterion=loss_fn,
experiment_logger=experiment_logger
)
def test_construct_from_tuple() :
model = DummyModel()
loss_fn = DummyLossFN()
trainer = DefaultTrainer(
optimizer=optimizer,
scheduler=scheduler,
model=model,
criterion=loss_fn,
experiment_logger=experiment_logger
)
def test_broken_construct_from_tuple_2() :
with pytest.warns(UserWarning) as e:
## default trainer only warns
loss_fn = BrokenDummyLossFN()
trainer = DefaultTrainer(
optimizer=optimizer,
scheduler=scheduler,
model=model,
criterion=loss_fn,
experiment_logger=experiment_logger
)
with pytest.raises(TypeError) as e:
## using strict trainer raises type error
loss_fn = BrokenDummyLossFN()
trainer = StrictCustomTrainer(
optimizer=optimizer,
scheduler=scheduler,
model=model,
criterion=loss_fn,
experiment_logger=experiment_logger
)