Autofix Ruff W (not W605) (mostly whitespace)

1 files changed, 6 insertions, 6 deletions

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index e374aeb8..7e50f1ab 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -34,7 +34,7 @@ def apply_optimizations():
 

     ldm.modules.diffusionmodules.model.nonlinearity = silu

     ldm.modules.diffusionmodules.openaimodel.th = sd_hijack_unet.th

-    

+

     optimization_method = None

 

     can_use_sdp = hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention) # not everyone has torch 2.x to use sdp

@@ -92,12 +92,12 @@ def fix_checkpoint():
 def weighted_loss(sd_model, pred, target, mean=True):

     #Calculate the weight normally, but ignore the mean

     loss = sd_model._old_get_loss(pred, target, mean=False)

-    

+

     #Check if we have weights available

     weight = getattr(sd_model, '_custom_loss_weight', None)

     if weight is not None:

         loss *= weight

-    

+

     #Return the loss, as mean if specified

     return loss.mean() if mean else loss

 

@@ -105,7 +105,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs):
     try:

         #Temporarily append weights to a place accessible during loss calc

         sd_model._custom_loss_weight = w

-        

+

         #Replace 'get_loss' with a weight-aware one. Otherwise we need to reimplement 'forward' completely

         #Keep 'get_loss', but don't overwrite the previous old_get_loss if it's already set

         if not hasattr(sd_model, '_old_get_loss'):

@@ -120,7 +120,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs):
             del sd_model._custom_loss_weight

         except AttributeError:

             pass

-            

+

         #If we have an old loss function, reset the loss function to the original one

         if hasattr(sd_model, '_old_get_loss'):

             sd_model.get_loss = sd_model._old_get_loss

@@ -184,7 +184,7 @@ class StableDiffusionModelHijack:
 

     def undo_hijack(self, m):

         if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation:

-            m.cond_stage_model = m.cond_stage_model.wrapped 

+            m.cond_stage_model = m.cond_stage_model.wrapped

 

         elif type(m.cond_stage_model) == sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords:

             m.cond_stage_model = m.cond_stage_model.wrapped