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The previous commit was meant to remove .github/workflows and removed every tracked path instead — 892 files, the whole repo. This puts back the 874 that were never in scope; the eighteen workflow files stay gone, for the reasons that commit gives. Content is byte-identical to 9d2aec9 outside .github/workflows.
123 lines
5.5 KiB
Python
123 lines
5.5 KiB
Python
"""Tests for the _update_subset_augmentations method in AnomalibDataModule."""
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# Copyright (C) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import logging
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import pytest
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from torchvision.transforms.v2 import (
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Compose,
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InterpolationMode,
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Normalize,
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RandomHorizontalFlip,
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RandomVerticalFlip,
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Resize,
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)
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from anomalib.data import AnomalibDataModule, AnomalibDataset
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class DummyDataset(AnomalibDataset):
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"""Dummy dataset class for testing."""
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def __init__(self) -> None:
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pass
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class TestUpdateAugmentations:
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"""Tests for the _update_subset_augmentations method in AnomalibDataModule."""
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@staticmethod
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def test_conflicting_shape(caplog: pytest.LogCaptureFixture) -> None:
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"""Test that a warning is logged if resize shapes mismatch."""
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dataset = DummyDataset()
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model_transform = Resize((224, 224))
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augmentations = Resize((256, 256))
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with caplog.at_level(logging.WARNING):
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AnomalibDataModule._update_subset_augmentations(dataset, augmentations, model_transform=model_transform) # noqa: SLF001
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# check if a warning was logged
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assert any(record.levelname == "WARNING" for record in caplog.records)
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assert "Conflicting resize shape" in caplog.text
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# check if augmentations were overwritten by model transform
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assert dataset.augmentations == model_transform
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@staticmethod
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def test_conflicting_interpolation(caplog: pytest.LogCaptureFixture) -> None:
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"""Test that a warning is logged if interpolation methods mismatch."""
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dataset = DummyDataset()
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model_transform = Resize((224, 224), interpolation=InterpolationMode.BILINEAR)
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augmentations = Resize((224, 224), interpolation=InterpolationMode.NEAREST)
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with caplog.at_level(logging.WARNING):
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AnomalibDataModule._update_subset_augmentations(dataset, augmentations, model_transform=model_transform) # noqa: SLF001
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# check if a warning was logged
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assert any(record.levelname == "WARNING" for record in caplog.records)
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assert "Conflicting interpolation method" in caplog.text
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# check if augmentations were overwritten by model transform
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assert dataset.augmentations == model_transform
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@staticmethod
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def test_conflicting_antialias(caplog: pytest.LogCaptureFixture) -> None:
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"""Test that a warning is logged if antialiasing setting mismatch."""
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dataset = DummyDataset()
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model_transform = Resize((224, 224), antialias=True)
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augmentations = Resize((224, 224), antialias=False)
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with caplog.at_level(logging.WARNING):
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AnomalibDataModule._update_subset_augmentations(dataset, augmentations, model_transform=model_transform) # noqa: SLF001
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# check if a warning was logged
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assert any(record.levelname == "WARNING" for record in caplog.records)
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assert "Conflicting antialiasing setting" in caplog.text
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# check if augmentations were overwritten by model transform
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assert dataset.augmentations == model_transform
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@staticmethod
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def test_augmentations_as_compose() -> None:
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"""Test that the Resize transform is added to the augmentations if augmentations is a Compose object."""
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dataset = DummyDataset()
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model_transform = Resize((224, 224))
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augmentations = Compose([RandomHorizontalFlip(), RandomVerticalFlip()])
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AnomalibDataModule._update_subset_augmentations(dataset, augmentations, model_transform=model_transform) # noqa: SLF001
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assert dataset.augmentations.transforms[-1] == model_transform
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@staticmethod
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def test_augmentations_as_transform() -> None:
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"""Test that the Resize transform is added to the augmentations if augmentations is a single transform."""
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dataset = DummyDataset()
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model_transform = Resize((224, 224))
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augmentations = RandomHorizontalFlip()
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AnomalibDataModule._update_subset_augmentations(dataset, augmentations, model_transform=model_transform) # noqa: SLF001
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assert dataset.augmentations.transforms[-1] == model_transform
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@staticmethod
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def test_model_transform_as_compose() -> None:
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"""Test that the Resize transform is added to the augmentations if model_transform is a Compose object."""
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dataset = DummyDataset()
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model_transform = Compose([Resize(224, 224), Normalize(mean=[0.5, 0.5, 0.5], std=[1.0, 1.0, 1.0])])
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augmentations = Compose([RandomHorizontalFlip(), RandomVerticalFlip()])
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AnomalibDataModule._update_subset_augmentations(dataset, augmentations, model_transform=model_transform) # noqa: SLF001
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assert dataset.augmentations.transforms[-1] == model_transform.transforms[0]
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@staticmethod
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def test_no_model_transforms() -> None:
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"""Test that the augmentations are added but not modified if model_transform is None."""
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dataset = DummyDataset()
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augmentations = Compose([RandomHorizontalFlip(), RandomVerticalFlip()])
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AnomalibDataModule._update_subset_augmentations(dataset, augmentations, model_transform=None) # noqa: SLF001
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assert dataset.augmentations == augmentations
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@staticmethod
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def test_no_augmentations() -> None:
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"""Test that the model_transform resize is added to the augmentations if augmentations is None."""
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dataset = DummyDataset()
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model_transform = Resize((224, 224))
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AnomalibDataModule._update_subset_augmentations(dataset, augmentations=None, model_transform=model_transform) # noqa: SLF001
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assert dataset.augmentations == model_transform
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