use max to test difference

tests/pipelines/versatile_diffusion/test_versatile_diffusion_dual_guided.py

@@ -76,7 +76,7 @@ class VersatileDiffusionDualGuidedPipelineIntegrationTests(unittest.TestCase):
             output_type="numpy",
         ).images
 
-        assert np.abs(image - new_image).sum() < 1e-5, "Models don't have the same forward pass"
+        assert np.abs(image - new_image).max() < 1e-5, "Models don't have the same forward pass"
 
     def test_inference_dual_guided(self):
         pipe = VersatileDiffusionDualGuidedPipeline.from_pretrained("shi-labs/versatile-diffusion")

tests/pipelines/versatile_diffusion/test_versatile_diffusion_mega.py

@@ -77,7 +77,7 @@ class VersatileDiffusionMegaPipelineIntegrationTests(unittest.TestCase):
             output_type="numpy",
         ).images
 
-        assert np.abs(image - new_image).sum() < 1e-5, "Models don't have the same forward pass"
+        assert np.abs(image - new_image).max() < 1e-5, "Models don't have the same forward pass"
 
     def test_inference_dual_guided_then_text_to_image(self):
         pipe = VersatileDiffusionPipeline.from_pretrained("shi-labs/versatile-diffusion", torch_dtype=torch.float16)

tests/pipelines/versatile_diffusion/test_versatile_diffusion_text_to_image.py

@@ -64,7 +64,7 @@ class VersatileDiffusionTextToImagePipelineIntegrationTests(unittest.TestCase):
             prompt=prompt, generator=generator, guidance_scale=7.5, num_inference_steps=2, output_type="numpy"
         ).images
 
-        assert np.abs(image - new_image).sum() < 1e-5, "Models don't have the same forward pass"
+        assert np.abs(image - new_image).max() < 1e-5, "Models don't have the same forward pass"
 
     def test_inference_text2img(self):
         pipe = VersatileDiffusionTextToImagePipeline.from_pretrained(