Remove commented out code (#4187)

* Remove commented out code

* [MONAI] python code formatting

Signed-off-by: monai-bot <[email protected]>

Co-authored-by: deepsource-autofix[bot] <62050782+deepsource-autofix[bot]@users.noreply.github.com>
Co-authored-by: monai-bot <[email protected]>

Author: deepsource-autofix[bot]

monai/apps/deepedit/transforms.py

@@ -688,8 +688,6 @@ def __call__(self, data):
         current_shape = d[self.ref_image].shape[1:]
         original_shape = d["image_meta_dict"]["spatial_shape"]
 
-        # original_shape = np.roll(original_shape, 1)
-
         factor = np.divide(current_shape, original_shape)
         all_guidances = {}
         for key_label in d[self.guidance].keys():

tests/test_bending_energy.py

@@ -60,7 +60,6 @@ def test_ill_shape(self):
             loss.forward(torch.ones((1, 3), device=device))
         with self.assertRaisesRegex(ValueError, "Expecting 3-d, 4-d or 5-d"):
             loss.forward(torch.ones((1, 4, 5, 5, 5, 5), device=device))
-        # spatial_dim < 5
         with self.assertRaisesRegex(ValueError, "All spatial dimensions"):
             loss.forward(torch.ones((1, 3, 4, 5, 5), device=device))
         with self.assertRaisesRegex(ValueError, "All spatial dimensions"):

tests/test_data_stats.py

@@ -137,7 +137,6 @@ class TestDataStats(unittest.TestCase):
     def test_value(self, input_param, input_data, expected_print):
         transform = DataStats(**input_param)
         _ = transform(input_data)
-        # self.assertEqual(transform.output, expected_print)
 
     @parameterized.expand([TEST_CASE_8])
     def test_file(self, input_data, expected_print):

tests/test_data_statsd.py

@@ -161,7 +161,6 @@ class TestDataStatsd(unittest.TestCase):
     def test_value(self, input_param, input_data, expected_print):
         transform = DataStatsd(**input_param)
         _ = transform(input_data)
-        # self.assertEqual(transform.printer.output, expected_print)
 
     @parameterized.expand([TEST_CASE_9])
     def test_file(self, input_data, expected_print):

tests/test_focal_loss.py

@@ -67,11 +67,8 @@ def test_consistency_with_cross_entropy_2d_no_reduction(self):
             b = output1.cpu().detach().numpy()
             error = np.abs(a - b)
             max_error = np.maximum(error, max_error)
-            # if np.all(np.abs(a - b) > max_error):
-            #     max_error = np.abs(a - b)
 
         assert np.allclose(max_error, 0)
-        # self.assertAlmostEqual(max_error, 0.0, places=3)
 
     def test_consistency_with_cross_entropy_2d_onehot_label(self):
         """For gamma=0 the focal loss reduces to the cross entropy loss"""

tests/test_fourier.py

@@ -21,8 +21,6 @@
 from tests.utils import SkipIfBeforePyTorchVersion, SkipIfNoModule
 
 TEST_CASES = [((128, 64),), ((64, 48, 80),)]
-# for shape in ((128, 64), (64, 48, 80)):
-#     TEST_CASES.append(shape)
 
 
 @SkipIfBeforePyTorchVersion((1, 8))

tests/test_print_transform_backends.py

@@ -22,6 +22,5 @@ def test_get_number_of_conversions(self):
 
 
 if __name__ == "__main__":
-    # unittest.main()
     a = TestPrintTransformBackends()
     a.test_get_number_of_conversions()

tests/test_rand_cucim_dict_transform.py

@@ -91,12 +91,10 @@ class TestRandCuCIMDict(unittest.TestCase):
     )
     def test_tramsforms_numpy_single(self, params, input, expected):
         input = {"image": np.copy(input)}
-        # apply_prob=1.0
         output = RandCuCIMd(keys="image", apply_prob=1.0, **params)(input)["image"]
         self.assertTrue(output.dtype == expected.dtype)
         self.assertTrue(isinstance(output, np.ndarray))
         cp.testing.assert_allclose(output, expected)
-        # apply_prob=0.0
         output = RandCuCIMd(keys="image", apply_prob=0.0, **params)(input)["image"]
         self.assertTrue(output.dtype == input["image"].dtype)
         self.assertTrue(isinstance(output, np.ndarray))
@@ -117,12 +115,10 @@ def test_tramsforms_numpy_single(self, params, input, expected):
     def test_tramsforms_numpy_batch(self, params, input, expected):
         input = {"image": np.copy(input[cp.newaxis, ...])}
         expected = expected[cp.newaxis, ...]
-        # apply_prob=1.0
         output = RandCuCIMd(keys="image", apply_prob=1.0, **params)(input)["image"]
         self.assertTrue(output.dtype == expected.dtype)
         self.assertTrue(isinstance(output, np.ndarray))
         cp.testing.assert_allclose(output, expected)
-        # apply_prob=0.0
         output = RandCuCIMd(keys="image", apply_prob=0.0, **params)(input)["image"]
         self.assertTrue(output.dtype == input["image"].dtype)
         self.assertTrue(isinstance(output, np.ndarray))
@@ -143,12 +139,10 @@ def test_tramsforms_numpy_batch(self, params, input, expected):
     def test_tramsforms_cupy_single(self, params, input, expected):
         input = {"image": cp.asarray(input)}
         expected = cp.asarray(expected)
-        # apply_prob=1.0
         output = RandCuCIMd(keys="image", apply_prob=1.0, **params)(input)["image"]
         self.assertTrue(output.dtype == expected.dtype)
         self.assertTrue(isinstance(output, cp.ndarray))
         cp.testing.assert_allclose(output, expected)
-        # apply_prob=0.0
         output = RandCuCIMd(keys="image", apply_prob=0.0, **params)(input)["image"]
         self.assertTrue(output.dtype == input["image"].dtype)
         self.assertTrue(isinstance(output, cp.ndarray))
@@ -169,12 +163,10 @@ def test_tramsforms_cupy_single(self, params, input, expected):
     def test_tramsforms_cupy_batch(self, params, input, expected):
         input = {"image": cp.asarray(input)[cp.newaxis, ...]}
         expected = cp.asarray(expected)[cp.newaxis, ...]
-        # apply_prob=1.0
         output = RandCuCIMd(keys="image", **params)(input)["image"]
         self.assertTrue(output.dtype == expected.dtype)
         self.assertTrue(isinstance(output, cp.ndarray))
         cp.testing.assert_allclose(output, expected)
-        # apply_prob=0.0
         output = RandCuCIMd(keys="image", apply_prob=0.0, **params)(input)["image"]
         self.assertTrue(output.dtype == input["image"].dtype)
         self.assertTrue(isinstance(output, cp.ndarray))

tests/test_rand_cucim_transform.py

@@ -90,13 +90,11 @@ class TestRandCuCIM(unittest.TestCase):
         ]
     )
     def test_tramsforms_numpy_single(self, params, input, expected):
-        # apply_prob=1.0
         input = np.copy(input)
         output = RandCuCIM(apply_prob=1.0, **params)(input)
         self.assertTrue(output.dtype == expected.dtype)
         self.assertTrue(isinstance(output, np.ndarray))
         cp.testing.assert_allclose(output, expected)
-        # apply_prob=0.0
         output = RandCuCIM(apply_prob=0.0, **params)(input)
         self.assertTrue(output.dtype == input.dtype)
         self.assertTrue(isinstance(output, np.ndarray))
@@ -117,12 +115,10 @@ def test_tramsforms_numpy_single(self, params, input, expected):
     def test_tramsforms_numpy_batch(self, params, input, expected):
         input = np.copy(input[cp.newaxis, ...])
         expected = expected[cp.newaxis, ...]
-        # apply_prob=1.0
         output = RandCuCIM(apply_prob=1.0, **params)(input)
         self.assertTrue(output.dtype == expected.dtype)
         self.assertTrue(isinstance(output, np.ndarray))
         cp.testing.assert_allclose(output, expected)
-        # apply_prob=0.0
         output = RandCuCIM(apply_prob=0.0, **params)(input)
         self.assertTrue(output.dtype == input.dtype)
         self.assertTrue(isinstance(output, np.ndarray))
@@ -143,12 +139,10 @@ def test_tramsforms_numpy_batch(self, params, input, expected):
     def test_tramsforms_cupy_single(self, params, input, expected):
         input = cp.asarray(input)
         expected = cp.asarray(expected)
-        # apply_prob=1.0
         output = RandCuCIM(apply_prob=1.0, **params)(input)
         self.assertTrue(output.dtype == expected.dtype)
         self.assertTrue(isinstance(output, cp.ndarray))
         cp.testing.assert_allclose(output, expected)
-        # apply_prob=0.0
         output = RandCuCIM(apply_prob=0.0, **params)(input)
         self.assertTrue(output.dtype == input.dtype)
         self.assertTrue(isinstance(output, cp.ndarray))
@@ -169,12 +163,10 @@ def test_tramsforms_cupy_single(self, params, input, expected):
     def test_tramsforms_cupy_batch(self, params, input, expected):
         input = cp.asarray(input)[cp.newaxis, ...]
         expected = cp.asarray(expected)[cp.newaxis, ...]
-        # apply_prob=1.0
         output = RandCuCIM(**params)(input)
         self.assertTrue(output.dtype == expected.dtype)
         self.assertTrue(isinstance(output, cp.ndarray))
         cp.testing.assert_allclose(output, expected)
-        # apply_prob=0.0
         output = RandCuCIM(apply_prob=0.0, **params)(input)
         self.assertTrue(output.dtype == input.dtype)
         self.assertTrue(isinstance(output, cp.ndarray))