fix dpm related slow test failure (#6680)

fix
Co-authored-by: yiyixuxu <yixu310@gmail,com>

tests/pipelines/stable_diffusion/test_stable_diffusion.py

@@ -836,7 +836,10 @@ class StableDiffusionPipelineSlowTests(unittest.TestCase):
 
     def test_stable_diffusion_dpm(self):
         sd_pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", safety_checker=None)
-        sd_pipe.scheduler = DPMSolverMultistepScheduler.from_config(sd_pipe.scheduler.config)
+        sd_pipe.scheduler = DPMSolverMultistepScheduler.from_config(
+            sd_pipe.scheduler.config,
+            final_sigmas_type="sigma_min",
+        )
         sd_pipe = sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
 

tests/pipelines/stable_diffusion_2/test_stable_diffusion.py

@@ -627,7 +627,9 @@ class StableDiffusion2PipelineNightlyTests(unittest.TestCase):
 
     def test_stable_diffusion_dpm(self):
         sd_pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base").to(torch_device)
-        sd_pipe.scheduler = DPMSolverMultistepScheduler.from_config(sd_pipe.scheduler.config)
+        sd_pipe.scheduler = DPMSolverMultistepScheduler.from_config(
+            sd_pipe.scheduler.config, final_sigmas_type="sigma_min"
+        )
         sd_pipe.set_progress_bar_config(disable=None)
 
         inputs = self.get_inputs(torch_device)

tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py

@@ -323,7 +323,9 @@ class StableDiffusion2VPredictionPipelineIntegrationTests(unittest.TestCase):
         TODO: update this test after making DPM compatible with V-prediction!
         """
         scheduler = DPMSolverMultistepScheduler.from_pretrained(
-            "stabilityai/stable-diffusion-2", subfolder="scheduler"
+            "stabilityai/stable-diffusion-2",
+            subfolder="scheduler",
+            final_sigmas_type="sigma_min",
         )
         sd_pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2", scheduler=scheduler)
         sd_pipe = sd_pipe.to(torch_device)