85 lines
2.2 KiB
Python
85 lines
2.2 KiB
Python
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import pytest
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from tests.base import SimpleModule
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from pytorch_lightning.trainer import Trainer
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@pytest.mark.parametrize('max_epochs', [1, 2, 3])
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def test_val_check_interval_1(tmpdir, max_epochs):
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class TestModel(SimpleModule):
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def __init__(self):
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super().__init__()
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self.train_epoch_calls = 0
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self.val_epoch_calls = 0
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def on_train_epoch_start(self) -> None:
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self.train_epoch_calls += 1
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def on_validation_epoch_start(self) -> None:
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if not self.trainer.running_sanity_check:
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self.val_epoch_calls += 1
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model = TestModel()
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trainer = Trainer(
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max_epochs=max_epochs,
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val_check_interval=1.0,
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logger=False,
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)
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trainer.fit(model)
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assert model.val_epoch_calls == max_epochs
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@pytest.mark.parametrize('max_epochs', [1, 2, 3])
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def test_val_check_interval_quarter(tmpdir, max_epochs):
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class TestModel(SimpleModule):
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def __init__(self):
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super().__init__()
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self.train_epoch_calls = 0
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self.val_epoch_calls = 0
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def on_train_epoch_start(self) -> None:
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self.train_epoch_calls += 1
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def on_validation_epoch_start(self) -> None:
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if not self.trainer.running_sanity_check:
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self.val_epoch_calls += 1
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model = TestModel()
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trainer = Trainer(
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max_epochs=max_epochs,
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val_check_interval=0.25,
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logger=False,
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)
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trainer.fit(model)
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assert model.val_epoch_calls == max_epochs * 4
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@pytest.mark.parametrize('max_epochs', [1, 2, 3])
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def test_val_check_interval_third(tmpdir, max_epochs):
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class TestModel(SimpleModule):
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def __init__(self):
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super().__init__()
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self.train_epoch_calls = 0
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self.val_epoch_calls = 0
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def on_train_epoch_start(self) -> None:
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self.train_epoch_calls += 1
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def on_validation_epoch_start(self) -> None:
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if not self.trainer.running_sanity_check:
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self.val_epoch_calls += 1
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model = TestModel()
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trainer = Trainer(
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max_epochs=max_epochs,
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val_check_interval=0.33,
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logger=False,
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)
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trainer.fit(model)
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assert model.val_epoch_calls == max_epochs * 3
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