Update FlowMatch docstrings to mention correct output classes (huggingface#10788)

update

Author: a-r-r-o-w

src/diffusers/schedulers/scheduling_flow_match_euler_discrete.py

@@ -349,13 +349,14 @@ def step(
             generator (`torch.Generator`, *optional*):
                 A random number generator.
             return_dict (`bool`):
-                Whether or not to return a [`~schedulers.scheduling_euler_discrete.EulerDiscreteSchedulerOutput`] or
-                tuple.
+                Whether or not to return a
+                [`~schedulers.scheduling_flow_match_euler_discrete.FlowMatchEulerDiscreteSchedulerOutput`] or tuple.
 
         Returns:
-            [`~schedulers.scheduling_euler_discrete.EulerDiscreteSchedulerOutput`] or `tuple`:
-                If return_dict is `True`, [`~schedulers.scheduling_euler_discrete.EulerDiscreteSchedulerOutput`] is
-                returned, otherwise a tuple is returned where the first element is the sample tensor.
+            [`~schedulers.scheduling_flow_match_euler_discrete.FlowMatchEulerDiscreteSchedulerOutput`] or `tuple`:
+                If return_dict is `True`,
+                [`~schedulers.scheduling_flow_match_euler_discrete.FlowMatchEulerDiscreteSchedulerOutput`] is returned,
+                otherwise a tuple is returned where the first element is the sample tensor.
         """
 
         if (
@@ -366,7 +367,7 @@ def step(
             raise ValueError(
                 (
                     "Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
-                    " `EulerDiscreteScheduler.step()` is not supported. Make sure to pass"
+                    " `FlowMatchEulerDiscreteScheduler.step()` is not supported. Make sure to pass"
                     " one of the `scheduler.timesteps` as a timestep."
                 ),
             )

src/diffusers/schedulers/scheduling_flow_match_heun_discrete.py

@@ -228,13 +228,14 @@ def step(
             generator (`torch.Generator`, *optional*):
                 A random number generator.
             return_dict (`bool`):
-                Whether or not to return a [`~schedulers.scheduling_Heun_discrete.HeunDiscreteSchedulerOutput`] or
-                tuple.
+                Whether or not to return a
+                [`~schedulers.scheduling_flow_match_heun_discrete.FlowMatchHeunDiscreteSchedulerOutput`] tuple.
 
         Returns:
-            [`~schedulers.scheduling_Heun_discrete.HeunDiscreteSchedulerOutput`] or `tuple`:
-                If return_dict is `True`, [`~schedulers.scheduling_Heun_discrete.HeunDiscreteSchedulerOutput`] is
-                returned, otherwise a tuple is returned where the first element is the sample tensor.
+            [`~schedulers.scheduling_flow_match_heun_discrete.FlowMatchHeunDiscreteSchedulerOutput`] or `tuple`:
+                If return_dict is `True`,
+                [`~schedulers.scheduling_flow_match_heun_discrete.FlowMatchHeunDiscreteSchedulerOutput`] is returned,
+                otherwise a tuple is returned where the first element is the sample tensor.
         """
 
         if (
@@ -245,7 +246,7 @@ def step(
             raise ValueError(
                 (
                     "Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
-                    " `HeunDiscreteScheduler.step()` is not supported. Make sure to pass"
+                    " `FlowMatchHeunDiscreteScheduler.step()` is not supported. Make sure to pass"
                     " one of the `scheduler.timesteps` as a timestep."
                 ),
             )