add Unload model button; Fixed #2

scripts/stablesr.py

@@ -87,8 +87,13 @@ class StableSR:
 
         def unet_forward(x, timesteps=None, context=None, y=None,**kwargs):
             self.latent_image = self.latent_image.to(x.device)
+            # Ensure the device of all modules layers is the same as the unet
+            # This will fix the issue when user use --medvram or --lowvram
+            self.spade_layers.to(x.device)
+            self.struct_cond_model.to(x.device)
+            timesteps = timesteps.to(x.device)
             self.struct_cond = None # mitigate vram peak
-            self.struct_cond = self.struct_cond_model(self.latent_image, timesteps.to(x.device)[:self.latent_image.shape[0]])
+            self.struct_cond = self.struct_cond_model(self.latent_image, timesteps[:self.latent_image.shape[0]])
             return getattr(unet, FORWARD_CACHE_NAME)(x, timesteps, context, y, **kwargs)
         
         unet.forward = unet_forward
@@ -107,7 +112,7 @@ class StableSR:
             delattr(unet, FORWARD_CACHE_NAME)
 
         # unhook spade layers
-        self.spade_layers.unhook(unet)
+        self.spade_layers.unhook()
 
 
 class Script(scripts.Script):
@@ -151,7 +156,15 @@ class Script(scripts.Script):
             save_original = gr.Checkbox(label='Save Original', value=False, elem_id=f'StableSR-save-original', visible=color_fix.value != 'None')
             color_fix.change(fn=lambda selected: gr.Checkbox.update(visible=selected != 'None'), inputs=color_fix, outputs=save_original, show_progress=False)
             pure_noise = gr.Checkbox(label='Pure Noise', value=True, elem_id=f'StableSR-pure-noise')
-            
+            unload_model= gr.Button(value='Unload Model', variant='tool')
+            def unload_model_fn():
+                if self.stablesr_model is not None:
+                    self.stablesr_model = None
+                    devices.torch_gc()
+                    print('[StableSR] Model unloaded!')
+                else:
+                    print('[StableSR] No model loaded.')
+            unload_model.click(fn=unload_model_fn)
         return [model, scale_factor, pure_noise, color_fix, save_original]
 
     def run(self, p: StableDiffusionProcessingImg2Img, model: str, scale_factor:float, pure_noise: bool, color_fix:str, save_original:bool) -> Processed:
@@ -220,6 +233,9 @@ class Script(scripts.Script):
                 return samples
             finally:
                 self.stablesr_model.unhook(unet)
+                # in --medvram and --lowvram mode, we send the model back to the initial device
+                self.stablesr_model.struct_cond_model.to(device=first_param.device)
+                self.stablesr_model.spade_layers.to(device=first_param.device)
 
                 
         # replace the sample function

srmodule/spade.py

@@ -125,10 +125,12 @@ class SPADELayers(nn.Module):
         self.output_ids = list(range(12))
         self.mid_ids = [0,2]
         self.forward_cache_name = 'org_forward_stablesr'
+        self.unet = None
 
 
     def hook(self, unet: UNetModel, get_struct_cond):
         # hook all resblocks
+        self.unet = unet
         resblock: ResBlock = None
         for i in self.input_ids:
             resblock = unet.input_blocks[i][0]
@@ -154,7 +156,9 @@ class SPADELayers(nn.Module):
                 setattr(resblock, self.forward_cache_name, resblock._forward)
             resblock._forward = lambda x, timesteps, resblock=resblock, spade=self.middle_block[i]: dual_resblock_forward(resblock, x, timesteps, spade, get_struct_cond)
 
-    def unhook(self, unet: UNetModel):
+    def unhook(self):
+        unet = self.unet
+        if unet is None: return
         resblock: ResBlock = None
         for i in self.input_ids:
             resblock = unet.input_blocks[i][0]
@@ -173,6 +177,7 @@ class SPADELayers(nn.Module):
             if hasattr(resblock, self.forward_cache_name):
                 resblock._forward = getattr(resblock, self.forward_cache_name)
                 delattr(resblock, self.forward_cache_name)
+        self.unet = None
 
 
     def load_from_dict(self, state_dict):