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		Runtime error
		
	Commit 
							
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						0fac10f
	
1
								Parent(s):
							
							9bd2ea4
								
Update app.py
Browse files
    	
        app.py
    CHANGED
    
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         @@ -59,12 +59,9 @@ original_pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion- 
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            def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lora_2_scale=0.5, progress=gr.Progress(track_tqdm=True)):
         
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              state_dict_1 = copy.deepcopy(shuffled_items[0]['state_dict'])
         
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              print("state_1", state_dict_1)
         
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              state_dict_2 = copy.deepcopy(shuffled_items[1]['state_dict'])
         
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              print("state_2", state_dict_2)
         
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              pipe = copy.deepcopy(original_pipe)
         
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              pipe.to("cuda") 
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              pipe.load_lora_weights(state_dict_1)
         
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              pipe.fuse_lora(lora_1_scale)
         
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         @@ -75,10 +72,10 @@ def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lor 
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                negative_prompt = None
         
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              image = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=20, width=768, height=768).images[0]
         
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              yield image
         
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              del pipe
         
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              gc.collect()
         
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              torch.cuda.empty_cache()
         
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            def get_description(item):
         
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                  trigger_word = item["trigger_word"]
         
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            def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lora_2_scale=0.5, progress=gr.Progress(track_tqdm=True)):
         
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              state_dict_1 = copy.deepcopy(shuffled_items[0]['state_dict'])
         
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              state_dict_2 = copy.deepcopy(shuffled_items[1]['state_dict'])
         
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              pipe = copy.deepcopy(original_pipe)
         
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              pipe.to("cuda") 
         
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              pipe.load_lora_weights(state_dict_1)
         
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              pipe.fuse_lora(lora_1_scale)
         
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                negative_prompt = None
         
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              image = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=20, width=768, height=768).images[0]
         
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              del pipe
         
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              gc.collect()
         
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              torch.cuda.empty_cache()
         
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              return image
         
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            def get_description(item):
         
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                  trigger_word = item["trigger_word"]
         
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