make clip name shorter

src/diffusers/schedulers/scheduling_ddim.py

@@ -28,7 +28,7 @@ class DDIMScheduler(SchedulerMixin, ConfigMixin):
         beta_schedule="linear",
         trained_betas=None,
         timestep_values=None,
-        clip_predicted_sample=True,
+        clip_sample=True,
         tensor_format="np",
     ):
         super().__init__()
@@ -40,7 +40,7 @@ class DDIMScheduler(SchedulerMixin, ConfigMixin):
         )
         self.timesteps = int(timesteps)
         self.timestep_values = timestep_values  # save the fixed timestep values for BDDM
-        self.clip_sample = clip_predicted_sample
+        self.clip_sample = clip_sample
 
         if beta_schedule == "linear":
             self.betas = linear_beta_schedule(timesteps, beta_start=beta_start, beta_end=beta_end)

src/diffusers/schedulers/scheduling_ddpm.py

@@ -29,7 +29,7 @@ class DDPMScheduler(SchedulerMixin, ConfigMixin):
         trained_betas=None,
         timestep_values=None,
         variance_type="fixed_small",
-        clip_predicted_sample=True,
+        clip_sample=True,
         tensor_format="np",
     ):
         super().__init__()
@@ -41,11 +41,11 @@ class DDPMScheduler(SchedulerMixin, ConfigMixin):
             trained_betas=trained_betas,
             timestep_values=timestep_values,
             variance_type=variance_type,
-            clip_predicted_sample=clip_predicted_sample,
+            clip_sample=clip_sample,
         )
         self.timesteps = int(timesteps)
         self.timestep_values = timestep_values  # save the fixed timestep values for BDDM
-        self.clip_sample = clip_predicted_sample
+        self.clip_sample = clip_sample
         self.variance_type = variance_type
 
         if trained_betas is not None:
@@ -124,7 +124,7 @@ class DDPMScheduler(SchedulerMixin, ConfigMixin):
         pred_original_sample = (sample - beta_prod_t ** (0.5) * residual) / alpha_prod_t ** (0.5)
 
         # 3. Clip "predicted x_0"
-        if self.clip_predicted_sample:
+        if self.clip_sample:
             pred_original_sample = self.clip(pred_original_sample, -1, 1)
 
         # 4. Compute coefficients for pred_original_sample x_0 and current sample x_t

tests/test_scheduler.py

@@ -172,7 +172,7 @@ class DDPMSchedulerTest(SchedulerCommonTest):
             "beta_end": 0.02,
             "beta_schedule": "linear",
             "variance_type": "fixed_small",
-            "clip_predicted_sample": True,
+            "clip_sample": True,
         }
 
         config.update(**kwargs)
@@ -195,8 +195,8 @@ class DDPMSchedulerTest(SchedulerCommonTest):
             self.check_over_configs(variance_type=variance)
 
     def test_clip_image(self):
-        for clip_predicted_sample in [True, False]:
-            self.check_over_configs(clip_predicted_sample=clip_predicted_sample)
+        for clip_sample in [True, False]:
+            self.check_over_configs(clip_sample=clip_sample)
 
     def test_time_indices(self):
         for t in [0, 500, 999]:
@@ -251,7 +251,7 @@ class DDIMSchedulerTest(SchedulerCommonTest):
             "beta_start": 0.0001,
             "beta_end": 0.02,
             "beta_schedule": "linear",
-            "clip_predicted_sample": True,
+            "clip_sample": True,
         }
 
         config.update(**kwargs)
@@ -270,8 +270,8 @@ class DDIMSchedulerTest(SchedulerCommonTest):
             self.check_over_configs(beta_schedule=schedule)
 
     def test_clip_image(self):
-        for clip_predicted_sample in [True, False]:
-            self.check_over_configs(clip_predicted_sample=clip_predicted_sample)
+        for clip_sample in [True, False]:
+            self.check_over_configs(clip_sample=clip_sample)
 
     def test_time_indices(self):
         for t in [1, 10, 49]: