clean up

Author: patrickvonplaten

test_corrections.txt

@@ -41,7 +41,7 @@
 )
 from diffusers.utils import floats_tensor, load_image, load_numpy, nightly, slow, torch_device
 from diffusers.utils.import_utils import is_accelerate_available
-from diffusers.utils.testing_utils import require_torch_gpu, print_tensor_test
+from diffusers.utils.testing_utils import require_torch_gpu
 
 from ...test_pipelines_common import PipelineTesterMixin
 
@@ -284,12 +284,11 @@ def test_stable_diffusion_depth2img_default_case(self):
         image = pipe(**inputs).images
         image_slice = image[0, -3:, -3:, -1]
 
-#        assert image.shape == (1, 32, 32, 3)
-#        if torch_device == "mps":
-#            expected_slice = np.array([0.6071, 0.5035, 0.4378, 0.5776, 0.5753, 0.4316, 0.4513, 0.5263, 0.4546])
-#        else:
-        print_tensor_test(image_slice)
-        expected_slice = np.array([0.6312, 0.4984, 0.4154, 0.4788, 0.5535, 0.4599, 0.4017, 0.5359, 0.4716])
+        assert image.shape == (1, 32, 32, 3)
+        if torch_device == "mps":
+            expected_slice = np.array([0.6071, 0.5035, 0.4378, 0.5776, 0.5753, 0.4316, 0.4513, 0.5263, 0.4546])
+        else:
+            expected_slice = np.array([0.6312, 0.4984, 0.4154, 0.4788, 0.5535, 0.4599, 0.4017, 0.5359, 0.4716])
 
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
 
@@ -307,11 +306,10 @@ def test_stable_diffusion_depth2img_negative_prompt(self):
         image_slice = image[0, -3:, -3:, -1]
 
         assert image.shape == (1, 32, 32, 3)
-#        if torch_device == "mps":
-#            expected_slice = np.array([0.5825, 0.5135, 0.4095, 0.5452, 0.6059, 0.4211, 0.3994, 0.5177, 0.4335])
-#        else:
-        print_tensor_test(image_slice)
-        expected_slice = np.array([0.6296, 0.5125, 0.3890, 0.4456, 0.5955, 0.4621, 0.3810, 0.5310, 0.4626])
+        if torch_device == "mps":
+            expected_slice = np.array([0.5825, 0.5135, 0.4095, 0.5452, 0.6059, 0.4211, 0.3994, 0.5177, 0.4335])
+        else:
+            expected_slice = np.array([0.6296, 0.5125, 0.3890, 0.4456, 0.5955, 0.4621, 0.3810, 0.5310, 0.4626])
 
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
 
@@ -330,11 +328,10 @@ def test_stable_diffusion_depth2img_multiple_init_images(self):
 
         assert image.shape == (2, 32, 32, 3)
 
-#        if torch_device == "mps":
-#            expected_slice = np.array([0.6501, 0.5150, 0.4939, 0.6688, 0.5437, 0.5758, 0.5115, 0.4406, 0.4551])
-#        else:
-        print_tensor_test(image_slice)
-        expected_slice = np.array([0.6267, 0.5232, 0.6001, 0.6738, 0.5029, 0.6429, 0.5364, 0.4159, 0.4674])
+        if torch_device == "mps":
+            expected_slice = np.array([0.6501, 0.5150, 0.4939, 0.6688, 0.5437, 0.5758, 0.5115, 0.4406, 0.4551])
+        else:
+            expected_slice = np.array([0.6267, 0.5232, 0.6001, 0.6738, 0.5029, 0.6429, 0.5364, 0.4159, 0.4674])
 
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
 
@@ -386,11 +383,10 @@ def test_stable_diffusion_depth2img_pil(self):
         image = pipe(**inputs).images
         image_slice = image[0, -3:, -3:, -1]
 
-#        if torch_device == "mps":
-#            expected_slice = np.array([0.53232, 0.47015, 0.40868, 0.45651, 0.4891, 0.4668, 0.4287, 0.48822, 0.47439])
-#        else:
-        expected_slice = np.array([0.6312, 0.4984, 0.4154, 0.4788, 0.5535, 0.4599, 0.4017, 0.5359, 0.4716])
-        print_tensor_test(image_slice)
+        if torch_device == "mps":
+            expected_slice = np.array([0.53232, 0.47015, 0.40868, 0.45651, 0.4891, 0.4668, 0.4287, 0.48822, 0.47439])
+        else:
+            expected_slice = np.array([0.6312, 0.4984, 0.4154, 0.4788, 0.5535, 0.4599, 0.4017, 0.5359, 0.4716])
 
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3