Fix UniPC tests and remove some test warnings (#2396)

* Change solver_type to match the previous tests.

* Prevent warnings about scale_model_inputs

* Prevent console log about division by zero.

tests/test_scheduler.py

@@ -287,6 +287,11 @@ class SchedulerCommonTest(unittest.TestCase):
             elif num_inference_steps is not None and not hasattr(scheduler, "set_timesteps"):
                 kwargs["num_inference_steps"] = num_inference_steps
 
+            # Make sure `scale_model_input` is invoked to prevent a warning
+            if scheduler_class != VQDiffusionScheduler:
+                _ = scheduler.scale_model_input(sample, 0)
+                _ = new_scheduler.scale_model_input(sample, 0)
+
             # Set the seed before step() as some schedulers are stochastic like EulerAncestralDiscreteScheduler, EulerDiscreteScheduler
             if "generator" in set(inspect.signature(scheduler.step).parameters.keys()):
                 kwargs["generator"] = torch.manual_seed(0)
@@ -597,7 +602,7 @@ class SchedulerCommonTest(unittest.TestCase):
                 continue
 
             scheduler_config = self.get_scheduler_config()
-            scheduler = scheduler_class(**scheduler_config, trained_betas=np.array([0.0, 0.1]))
+            scheduler = scheduler_class(**scheduler_config, trained_betas=np.array([0.1, 0.3]))
 
             with tempfile.TemporaryDirectory() as tmpdirname:
                 scheduler.save_pretrained(tmpdirname)
@@ -2648,6 +2653,7 @@ class UniPCMultistepSchedulerTest(SchedulerCommonTest):
             "beta_end": 0.02,
             "beta_schedule": "linear",
             "solver_order": 2,
+            "solver_type": "bh1",
         }
 
         config.update(**kwargs)