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weighting refactory

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Co-authored-by: Dario Coscia <dariocos99@gmail.com>
This commit is contained in:
giovanni
2025-09-01 11:00:14 +02:00
committed by Giovanni Canali
parent c42bdd575c
commit 96402baf20
12 changed files with 214 additions and 388 deletions
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26
tests/test_weighting/test_self_adaptive_weighting.py
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@@ -12,26 +12,28 @@ problem.discretise_domain(10)
model = FeedForward(len(problem.input_variables), len(problem.output_variables))
@pytest.mark.parametrize("k", [10, 100, 1000])
def test_constructor(k):
SelfAdaptiveWeighting(k=k)
@pytest.mark.parametrize("update_every_n_epochs", [10, 100, 1000])
def test_constructor(update_every_n_epochs):
SelfAdaptiveWeighting(update_every_n_epochs=update_every_n_epochs)
# Should fail if k is not an integer
# Should fail if update_every_n_epochs is not an integer
with pytest.raises(AssertionError):
SelfAdaptiveWeighting(k=1.5)
SelfAdaptiveWeighting(update_every_n_epochs=1.5)
# Should fail if k is not > 0
# Should fail if update_every_n_epochs is not > 0
with pytest.raises(AssertionError):
SelfAdaptiveWeighting(k=0)
SelfAdaptiveWeighting(update_every_n_epochs=0)
# Should fail if k is not > 0
# Should fail if update_every_n_epochs is not > 0
with pytest.raises(AssertionError):
SelfAdaptiveWeighting(k=-3)
SelfAdaptiveWeighting(update_every_n_epochs=-3)
@pytest.mark.parametrize("k", [2, 3])
def test_train_aggregation(k):
weighting = SelfAdaptiveWeighting(k=k)
@pytest.mark.parametrize("update_every_n_epochs", [1, 3])
def test_train_aggregation(update_every_n_epochs):
weighting = SelfAdaptiveWeighting(
update_every_n_epochs=update_every_n_epochs
)
solver = PINN(problem=problem, model=model, weighting=weighting)
trainer = Trainer(solver=solver, max_epochs=5, accelerator="cpu")
trainer.train()