From 9a229ab1d3efc5c5b4a0a2bad963d03ce799a80c Mon Sep 17 00:00:00 2001 From: YunLiu <55491388+KumoLiu@users.noreply.github.com> Date: Mon, 22 Apr 2024 18:23:39 +0800 Subject: [PATCH 1/4] fix #7692 Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com> --- monai/losses/perceptual.py | 1 + 1 file changed, 1 insertion(+) diff --git a/monai/losses/perceptual.py b/monai/losses/perceptual.py index 02493f412b..a5e4d7f9e5 100644 --- a/monai/losses/perceptual.py +++ b/monai/losses/perceptual.py @@ -125,6 +125,7 @@ def __init__( self.perceptual_function = LPIPS(pretrained=pretrained, net=network_type, verbose=False) self.is_fake_3d = is_fake_3d self.fake_3d_ratio = fake_3d_ratio + self.channel_wise=channel_wise def _calculate_axis_loss(self, input: torch.Tensor, target: torch.Tensor, spatial_axis: int) -> torch.Tensor: """ From 4e94519a5d6dbfdfc154eacf458c02d5cc671ae9 Mon Sep 17 00:00:00 2001 From: YunLiu <55491388+KumoLiu@users.noreply.github.com> Date: Mon, 22 Apr 2024 18:53:52 +0800 Subject: [PATCH 2/4] fix flake8 Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com> --- monai/losses/perceptual.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/monai/losses/perceptual.py b/monai/losses/perceptual.py index a5e4d7f9e5..a8ae90993a 100644 --- a/monai/losses/perceptual.py +++ b/monai/losses/perceptual.py @@ -125,7 +125,7 @@ def __init__( self.perceptual_function = LPIPS(pretrained=pretrained, net=network_type, verbose=False) self.is_fake_3d = is_fake_3d self.fake_3d_ratio = fake_3d_ratio - self.channel_wise=channel_wise + self.channel_wise = channel_wise def _calculate_axis_loss(self, input: torch.Tensor, target: torch.Tensor, spatial_axis: int) -> torch.Tensor: """ From 20b17dbebd48f201c708702715617a4c496b5953 Mon Sep 17 00:00:00 2001 From: YunLiu <55491388+KumoLiu@users.noreply.github.com> Date: Mon, 22 Apr 2024 21:40:39 +0800 Subject: [PATCH 3/4] fix ci Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com> --- tests/test_clip_intensity_percentiles.py | 16 ++++++++-------- tests/test_clip_intensity_percentilesd.py | 18 +++++++++--------- 2 files changed, 17 insertions(+), 17 deletions(-) diff --git a/tests/test_clip_intensity_percentiles.py b/tests/test_clip_intensity_percentiles.py index f584a0bb41..01820e7115 100644 --- a/tests/test_clip_intensity_percentiles.py +++ b/tests/test_clip_intensity_percentiles.py @@ -31,7 +31,7 @@ def test_hard_clipping_two_sided(self, p): result = hard_clipper(im) lower, upper = percentile(im, (5, 95)) expected = clip(convert_to_tensor(im), lower, upper) - assert_allclose(result, p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result, p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_hard_clipping_one_sided_high(self, p): @@ -40,7 +40,7 @@ def test_hard_clipping_one_sided_high(self, p): result = hard_clipper(im) lower, upper = percentile(im, (0, 95)) expected = clip(im, lower, upper) - assert_allclose(result, p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result, p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_hard_clipping_one_sided_low(self, p): @@ -49,7 +49,7 @@ def test_hard_clipping_one_sided_low(self, p): result = hard_clipper(im) lower, upper = percentile(im, (5, 100)) expected = clip(im, lower, upper) - assert_allclose(result, p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result, p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_soft_clipping_two_sided(self, p): @@ -89,7 +89,7 @@ def test_channel_wise(self, p): for i, c in enumerate(im): lower, upper = percentile(c, (5, 95)) expected = clip(c, lower, upper) - assert_allclose(result[i], p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result[i], p(expected), type_test="tensor", rtol=1e-4, atol=0) def test_ill_sharpness_factor(self): with self.assertRaises(ValueError): @@ -121,7 +121,7 @@ def test_hard_clipping_two_sided(self, p): result = hard_clipper(im) lower, upper = percentile(im, (5, 95)) expected = clip(im, lower, upper) - assert_allclose(result, p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result, p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_hard_clipping_one_sided_high(self, p): @@ -130,7 +130,7 @@ def test_hard_clipping_one_sided_high(self, p): result = hard_clipper(im) lower, upper = percentile(im, (0, 95)) expected = clip(im, lower, upper) - assert_allclose(result, p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result, p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_hard_clipping_one_sided_low(self, p): @@ -139,7 +139,7 @@ def test_hard_clipping_one_sided_low(self, p): result = hard_clipper(im) lower, upper = percentile(im, (5, 100)) expected = clip(im, lower, upper) - assert_allclose(result, p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result, p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_soft_clipping_two_sided(self, p): @@ -179,7 +179,7 @@ def test_channel_wise(self, p): for i, c in enumerate(im): lower, upper = percentile(c, (5, 95)) expected = clip(c, lower, upper) - assert_allclose(result[i], p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result[i], p(expected), type_test="tensor", rtol=1e-4, atol=0) if __name__ == "__main__": diff --git a/tests/test_clip_intensity_percentilesd.py b/tests/test_clip_intensity_percentilesd.py index 97c08f9f4e..e36ca76670 100644 --- a/tests/test_clip_intensity_percentilesd.py +++ b/tests/test_clip_intensity_percentilesd.py @@ -32,8 +32,8 @@ def test_hard_clipping_two_sided(self, p): im = p(self.imt) result = hard_clipper({key: im}) lower, upper = percentile(im, (5, 95)) - expected = clip(convert_to_tensor(im), lower, upper) - assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-7, atol=0) + expected = clip(im, lower, upper) + assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_hard_clipping_one_sided_high(self, p): @@ -43,7 +43,7 @@ def test_hard_clipping_one_sided_high(self, p): result = hard_clipper({key: im}) lower, upper = percentile(im, (0, 95)) expected = clip(im, lower, upper) - assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_hard_clipping_one_sided_low(self, p): @@ -53,7 +53,7 @@ def test_hard_clipping_one_sided_low(self, p): result = hard_clipper({key: im}) lower, upper = percentile(im, (5, 100)) expected = clip(im, lower, upper) - assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_soft_clipping_two_sided(self, p): @@ -97,7 +97,7 @@ def test_channel_wise(self, p): for i, c in enumerate(im): lower, upper = percentile(c, (5, 95)) expected = clip(c, lower, upper) - assert_allclose(result[key][i], p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result[key][i], p(expected), type_test="tensor", rtol=1e-4, atol=0) def test_ill_sharpness_factor(self): key = "img" @@ -135,7 +135,7 @@ def test_hard_clipping_two_sided(self, p): result = hard_clipper({key: im}) lower, upper = percentile(im, (5, 95)) expected = clip(im, lower, upper) - assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_hard_clipping_one_sided_high(self, p): @@ -145,7 +145,7 @@ def test_hard_clipping_one_sided_high(self, p): result = hard_clipper({key: im}) lower, upper = percentile(im, (0, 95)) expected = clip(im, lower, upper) - assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_hard_clipping_one_sided_low(self, p): @@ -155,7 +155,7 @@ def test_hard_clipping_one_sided_low(self, p): result = hard_clipper({key: im}) lower, upper = percentile(im, (5, 100)) expected = clip(im, lower, upper) - assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-4, atol=0) @parameterized.expand([[p] for p in TEST_NDARRAYS]) def test_soft_clipping_two_sided(self, p): @@ -199,7 +199,7 @@ def test_channel_wise(self, p): for i, c in enumerate(im): lower, upper = percentile(c, (5, 95)) expected = clip(c, lower, upper) - assert_allclose(result[key][i], p(expected), type_test="tensor", rtol=1e-7, atol=0) + assert_allclose(result[key][i], p(expected), type_test="tensor", rtol=1e-4, atol=0) if __name__ == "__main__": From 0cedb84b942b3c4f128877ec55f90a50af350418 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 22 Apr 2024 13:41:23 +0000 Subject: [PATCH 4/4] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- tests/test_clip_intensity_percentilesd.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/test_clip_intensity_percentilesd.py b/tests/test_clip_intensity_percentilesd.py index e36ca76670..fa727b6adb 100644 --- a/tests/test_clip_intensity_percentilesd.py +++ b/tests/test_clip_intensity_percentilesd.py @@ -19,7 +19,6 @@ from monai.transforms import ClipIntensityPercentilesd from monai.transforms.utils import soft_clip from monai.transforms.utils_pytorch_numpy_unification import clip, percentile -from monai.utils.type_conversion import convert_to_tensor from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, NumpyImageTestCase3D, assert_allclose