From b43e653882c2a35441629322cde3b266e203cdcb Mon Sep 17 00:00:00 2001 From: jdeschamps <6367888+jdeschamps@users.noreply.github.com> Date: Thu, 6 Jun 2024 17:21:56 +0200 Subject: [PATCH] (chore): remove tests from erroneous merge --- tests/config/test_inference_model.py | 52 ---------------------------- 1 file changed, 52 deletions(-) diff --git a/tests/config/test_inference_model.py b/tests/config/test_inference_model.py index 0ecf22b46..1f7637b36 100644 --- a/tests/config/test_inference_model.py +++ b/tests/config/test_inference_model.py @@ -115,55 +115,3 @@ def test_set_3d(minimum_inference: dict): assert "Z" in pred.axes assert len(pred.tile_size) == 3 assert len(pred.tile_overlap) == 3 - - -@pytest.mark.parametrize( - "transforms", - [ - [ - {"name": SupportedTransform.NORMALIZE.value}, - ], - ], -) -def test_passing_supported_transforms(minimum_inference: dict, transforms): - """Test that list of supported transforms can be passed.""" - minimum_inference["transforms"] = transforms - InferenceConfig(**minimum_inference) - - -def test_cannot_pass_n2v_manipulate(minimum_inference: dict): - """Test that passing N2V pixel manipulate transform raises an error.""" - minimum_inference["transforms"] = [ - {"name": SupportedTransform.N2V_MANIPULATE.value}, - ] - with pytest.raises(ValueError): - InferenceConfig(**minimum_inference) - - -def test_passing_empty_transforms(minimum_inference: dict): - """Test that empty list of transforms can be passed.""" - minimum_inference["transforms"] = [] - InferenceConfig(**minimum_inference) - - -def test_passing_incorrect_element(minimum_inference: dict): - """Test that incorrect element in the list of transforms raises an error ( - e.g. passing un object rather than a string).""" - minimum_inference["transforms"] = [ - {"name": get_all_transforms()[SupportedTransform.NDFLIP.value]()}, - ] - with pytest.raises(ValueError): - InferenceConfig(**minimum_inference) - - -def test_mean_and_std_in_normalize(minimum_inference: dict): - """Test that mean and std are added to the Normalize transform.""" - minimum_inference["image_mean"] = [10.4] - minimum_inference["image_std"] = [3.2] - minimum_inference["transforms"] = [ - {"name": SupportedTransform.NORMALIZE.value}, - ] - - data = InferenceConfig(**minimum_inference) - assert data.transforms[0].image_means == [10.4] - assert data.transforms[0].image_stds == [3.2]