Spaces:
				
			
			
	
			
			
		Runtime error
		
	
	
	
			
			
	
	
	
	
		
		
		Runtime error
		
	Update check_app.py
Browse files- check_app.py +3 -0
    	
        check_app.py
    CHANGED
    
    | @@ -182,6 +182,7 @@ def create_pipeline_logic(prompt_text, model_name, negative_prompt="",  seed=42, | |
| 182 | 
             
                pipe_class = config["pipeline_class"]
         | 
| 183 | 
             
                global pipe
         | 
| 184 | 
             
                if ["pipeline_class"] != pipe_class:
         | 
|  | |
| 185 | 
             
                    pipe["pipeline_class"] = pipe_class
         | 
| 186 | 
             
                    b_pipe = AutoPipelineForText2Image.from_pretrained(
         | 
| 187 | 
             
                        config["repo_id"],
         | 
| @@ -197,6 +198,8 @@ def create_pipeline_logic(prompt_text, model_name, negative_prompt="",  seed=42, | |
| 197 | 
             
                        print("ProgressPipeline specal")
         | 
| 198 | 
             
                    else:
         | 
| 199 | 
             
                        pipe["pipeline"] = b_pipe
         | 
|  | |
|  | |
| 200 |  | 
| 201 | 
             
                gen_seed,image, images = generate_image_with_progress(
         | 
| 202 | 
             
                    model_name,pipe["pipeline"], prompt_text, num_steps=num_inference_steps, guidance_scale=guidance_scale, seed=seed,negative_prompt = negative_prompt,  randomize_seed = randomize_seed, width = width, height = height, progress=progress
         | 
|  | |
| 182 | 
             
                pipe_class = config["pipeline_class"]
         | 
| 183 | 
             
                global pipe
         | 
| 184 | 
             
                if ["pipeline_class"] != pipe_class:
         | 
| 185 | 
            +
                    print(f"NO PIPE. LOADING NEW {model_name}")
         | 
| 186 | 
             
                    pipe["pipeline_class"] = pipe_class
         | 
| 187 | 
             
                    b_pipe = AutoPipelineForText2Image.from_pretrained(
         | 
| 188 | 
             
                        config["repo_id"],
         | 
|  | |
| 198 | 
             
                        print("ProgressPipeline specal")
         | 
| 199 | 
             
                    else:
         | 
| 200 | 
             
                        pipe["pipeline"] = b_pipe
         | 
| 201 | 
            +
                else:
         | 
| 202 | 
            +
                    print(f"HAS PIPE. LOADING EXISTIN  {model_name}")
         | 
| 203 |  | 
| 204 | 
             
                gen_seed,image, images = generate_image_with_progress(
         | 
| 205 | 
             
                    model_name,pipe["pipeline"], prompt_text, num_steps=num_inference_steps, guidance_scale=guidance_scale, seed=seed,negative_prompt = negative_prompt,  randomize_seed = randomize_seed, width = width, height = height, progress=progress
         | 
