def test_skip_on_fast_dev_run_tuner(tmpdir, tuner_alg):
"""Test that tuner algorithms are skipped if fast dev run is enabled."""
model = BoringModel()
model.lr = 0.1 # avoid no-lr-found exception
trainer = Trainer(
default_root_dir=tmpdir,
max_epochs=2,
auto_scale_batch_size=(tuner_alg == "batch size scaler"),
auto_lr_find=(tuner_alg == "learning rate finder"),
fast_dev_run=True,
)
expected_message = f"Skipping {tuner_alg} since fast_dev_run is enabled."
with pytest.warns(UserWarning, match=expected_message):
trainer.tune(model)
def test_init_optimizers_resets_lightning_optimizers(tmpdir):
"""Test that the Trainer resets the `lightning_optimizers` list everytime new optimizers get initialized."""
def compare_optimizers():
assert trainer.strategy._lightning_optimizers[
0].optimizer is trainer.optimizers[0]
model = BoringModel()
model.lr = 0.2
trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, auto_lr_find=True)
trainer.tune(model)
compare_optimizers()
trainer.fit(model)
compare_optimizers()
trainer.fit_loop.max_epochs = 2 # simulate multiple fit calls
trainer.fit(model)
compare_optimizers()
