def test_num_sanity_val_steps(tmpdir, limit_val_batches):
"""
Test that the number of sanity check batches is clipped to `limit_val_batches`.
"""
model = EvalModelTemplate()
model.validation_step = model.validation_step__multiple_dataloaders
model.validation_epoch_end = model.validation_epoch_end__multiple_dataloaders
num_sanity_val_steps = 4
trainer = Trainer(
default_root_dir=tmpdir,
num_sanity_val_steps=num_sanity_val_steps,
limit_val_batches=limit_val_batches,
max_steps=1,
)
assert trainer.num_sanity_val_steps == num_sanity_val_steps
with patch.object(trainer.evaluation_loop,
'evaluation_step',
wraps=trainer.evaluation_loop.evaluation_step) as mocked:
val_dataloaders = model.val_dataloader__multiple_mixed_length()
trainer.fit(model, val_dataloaders=val_dataloaders)
assert mocked.call_count == sum(
min(num_sanity_val_steps, num_batches)
for num_batches in trainer.num_val_batches)
def test_num_sanity_val_steps(tmpdir, limit_val_batches):
""" Test that the number of sanity check batches is clipped to limit_val_batches. """
model = EvalModelTemplate()
model.validation_step = model.validation_step__multiple_dataloaders
model.validation_epoch_end = model.validation_epoch_end__multiple_dataloaders
num_sanity_val_steps = 4
trainer = Trainer(
default_root_dir=tmpdir,
num_sanity_val_steps=num_sanity_val_steps,
limit_val_batches=limit_val_batches,
max_steps=1,
)
assert trainer.num_sanity_val_steps == num_sanity_val_steps
val_dataloaders = model.val_dataloader__multiple_mixed_length()
