Cleanup pass for flaky Slow Tests for Stable diffusion (huggingface#4415)

* update expected slice so img2img compile tests pass

* use default attn processor

* use default attn processor and update expected slice value to pass test

* use default attn processor

* set default attn processor and update expected slice

* set default attn processor and change precision for check

* set unet to use default attn processor

Author: DN6

tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py

@@ -63,17 +63,17 @@ def _test_img2img_compile(in_queue, out_queue, timeout):
 
         pipe = StableDiffusionImg2ImgPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", safety_checker=None)
         pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
+        pipe.unet.set_default_attn_processor()
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
-
         pipe.unet.to(memory_format=torch.channels_last)
         pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
 
         image = pipe(**inputs).images
         image_slice = image[0, -3:, -3:, -1].flatten()
 
         assert image.shape == (1, 512, 768, 3)
-        expected_slice = np.array([0.0593, 0.0607, 0.0851, 0.0582, 0.0636, 0.0721, 0.0751, 0.0981, 0.0781])
+        expected_slice = np.array([0.0606, 0.0570, 0.0805, 0.0579, 0.0628, 0.0623, 0.0843, 0.1115, 0.0806])
 
         assert np.abs(expected_slice - image_slice).max() < 1e-3
     except Exception:

tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint.py

@@ -64,6 +64,7 @@ def _test_inpaint_compile(in_queue, out_queue, timeout):
         pipe = StableDiffusionInpaintPipeline.from_pretrained(
             "runwayml/stable-diffusion-inpainting", safety_checker=None
         )
+        pipe.unet.set_default_attn_processor()
         pipe.scheduler = PNDMScheduler.from_config(pipe.scheduler.config)
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
@@ -75,8 +76,7 @@ def _test_inpaint_compile(in_queue, out_queue, timeout):
         image_slice = image[0, 253:256, 253:256, -1].flatten()
 
         assert image.shape == (1, 512, 512, 3)
-        expected_slice = np.array([0.0425, 0.0273, 0.0344, 0.1694, 0.1727, 0.1812, 0.3256, 0.3311, 0.3272])
-
+        expected_slice = np.array([0.0689, 0.0699, 0.0790, 0.0536, 0.0470, 0.0488, 0.041, 0.0508, 0.04179])
         assert np.abs(expected_slice - image_slice).max() < 3e-3
     except Exception:
         error = f"{traceback.format_exc()}"
@@ -382,6 +382,7 @@ def test_stable_diffusion_inpaint_fp16(self):
         pipe = StableDiffusionInpaintPipeline.from_pretrained(
             "runwayml/stable-diffusion-inpainting", torch_dtype=torch.float16, safety_checker=None
         )
+        pipe.unet.set_default_attn_processor()
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
         pipe.enable_attention_slicing()
@@ -391,8 +392,7 @@ def test_stable_diffusion_inpaint_fp16(self):
         image_slice = image[0, 253:256, 253:256, -1].flatten()
 
         assert image.shape == (1, 512, 512, 3)
-        expected_slice = np.array([0.1350, 0.1123, 0.1350, 0.1641, 0.1328, 0.1230, 0.1289, 0.1531, 0.1687])
-
+        expected_slice = np.array([0.1509, 0.1245, 0.1672, 0.1655, 0.1519, 0.1226, 0.1462, 0.1567, 0.2451])
         assert np.abs(expected_slice - image_slice).max() < 5e-2
 
     def test_stable_diffusion_inpaint_pndm(self):
@@ -485,6 +485,7 @@ def test_stable_diffusion_inpaint_strength_test(self):
             "runwayml/stable-diffusion-inpainting", safety_checker=None
         )
         pipe.scheduler = LMSDiscreteScheduler.from_config(pipe.scheduler.config)
+        pipe.unet.set_default_attn_processor()
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
         pipe.enable_attention_slicing()
@@ -497,11 +498,12 @@ def test_stable_diffusion_inpaint_strength_test(self):
         assert image.shape == (1, 512, 512, 3)
 
         image_slice = image[0, 253:256, 253:256, -1].flatten()
-        expected_slice = np.array([0.0021, 0.2350, 0.3712, 0.0575, 0.2485, 0.3451, 0.1857, 0.3156, 0.3943])
-        assert np.abs(expected_slice - image_slice).max() < 3e-3
+        expected_slice = np.array([0.2728, 0.2803, 0.2665, 0.2511, 0.2774, 0.2586, 0.2391, 0.2392, 0.2582])
+        assert np.abs(expected_slice - image_slice).max() < 1e-3
 
     def test_stable_diffusion_simple_inpaint_ddim(self):
         pipe = StableDiffusionInpaintPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", safety_checker=None)
+        pipe.unet.set_default_attn_processor()
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
         pipe.enable_attention_slicing()
@@ -512,9 +514,8 @@ def test_stable_diffusion_simple_inpaint_ddim(self):
         image_slice = image[0, 253:256, 253:256, -1].flatten()
 
         assert image.shape == (1, 512, 512, 3)
-        expected_slice = np.array([0.5157, 0.6858, 0.6873, 0.4619, 0.6416, 0.6898, 0.3702, 0.5960, 0.6935])
-
-        assert np.abs(expected_slice - image_slice).max() < 6e-4
+        expected_slice = np.array([0.3757, 0.3875, 0.4445, 0.4353, 0.3780, 0.4513, 0.3965, 0.3984, 0.4362])
+        assert np.abs(expected_slice - image_slice).max() < 1e-3
 
     def test_download_local(self):
         filename = hf_hub_download("runwayml/stable-diffusion-inpainting", filename="sd-v1-5-inpainting.ckpt")

tests/pipelines/stable_diffusion/test_stable_diffusion_panorama.py

@@ -299,14 +299,14 @@ def test_stable_diffusion_panorama_k_lms(self):
             "stabilityai/stable-diffusion-2-base", safety_checker=None
         )
         pipe.scheduler = LMSDiscreteScheduler.from_config(pipe.scheduler.config)
+        pipe.unet.set_default_attn_processor()
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
         pipe.enable_attention_slicing()
 
         inputs = self.get_inputs()
         image = pipe(**inputs).images
         image_slice = image[0, -3:, -3:, -1].flatten()
-
         assert image.shape == (1, 512, 2048, 3)
 
         expected_slice = np.array(
@@ -325,7 +325,7 @@ def test_stable_diffusion_panorama_k_lms(self):
             ]
         )
 
-        assert np.abs(expected_slice - image_slice).max() < 1e-3
+        assert np.abs(expected_slice - image_slice).max() < 1e-2
 
     def test_stable_diffusion_panorama_intermediate_state(self):
         number_of_steps = 0

tests/pipelines/stable_diffusion_2/test_stable_diffusion.py

@@ -344,6 +344,7 @@ def test_stable_diffusion_attention_slicing(self):
         pipe = StableDiffusionPipeline.from_pretrained(
             "stabilityai/stable-diffusion-2-base", torch_dtype=torch.float16
         )
+        pipe.unet.set_default_attn_processor()
         pipe = pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
 
@@ -359,6 +360,7 @@ def test_stable_diffusion_attention_slicing(self):
 
         # disable slicing
         pipe.disable_attention_slicing()
+        pipe.unet.set_default_attn_processor()
         inputs = self.get_inputs(torch_device, dtype=torch.float16)
         image = pipe(**inputs).images
 

tests/pipelines/stable_diffusion_2/test_stable_diffusion_depth.py

@@ -417,6 +417,7 @@ def test_stable_diffusion_depth2img_pipeline_k_lms(self):
         pipe = StableDiffusionDepth2ImgPipeline.from_pretrained(
             "stabilityai/stable-diffusion-2-depth", safety_checker=None
         )
+        pipe.unet.set_default_attn_processor()
         pipe.scheduler = LMSDiscreteScheduler.from_config(pipe.scheduler.config)
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)