Update app.py

app.py

@@ -12,6 +12,7 @@ import spaces
 import torch
 from diffusers import AutoPipelineForText2Image, DPMSolverMultistepScheduler
 from huggingface_hub import hf_hub_download
+from diffusers.models.attention_processor import AttnProcessor2_0
 
 DESCRIPTION = """
 # Res-Adapter :Domain Consistent Resolution Adapter for Diffusion Models
@@ -28,7 +29,7 @@ USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE") == "1"
 ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD") == "1"
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
-pipe = AutoPipelineForText2Image.from_pretrained('Lykon/dreamshaper-xl-1-0',use_safetensors=True)# torch_dtype=torch.float16, variant="safetensors")
+pipe = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0',use_safetensors=True)# torch_dtype=torch.float16, variant="safetensors")
 pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True, algorithm_type="sde-dpmsolver++")
 
 
@@ -75,8 +76,7 @@ def generate(
         prompt_2 = None  # type: ignore
     if not use_negative_prompt_2:
         negative_prompt_2 = None  # type: ignore
-
-    base_image = pipe(
+    res_adapt=pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
         prompt_2=prompt_2,
@@ -86,11 +86,11 @@ def generate(
         guidance_scale=guidance_scale_base,
         num_inference_steps=num_inference_steps_base,
         generator=generator,
-        output_type="pil").images[0]
+        output_type="pil",
+    ).images[0]
 
-    
-    
-    res_adapt=pipe(
+    pipe.unet.set_attn_processor(AttnProcessor2_0())
+    base_image = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
         prompt_2=prompt_2,
@@ -100,9 +100,12 @@ def generate(
         guidance_scale=guidance_scale_base,
         num_inference_steps=num_inference_steps_base,
         generator=generator,
-        output_type="pil",
-    ).images[0]
-    return [base_image,res_adapt]
+        output_type="pil").images[0]
+
+    
+    
+    
+    return [res_adapt,base_image]
 
 
 examples = [
@@ -129,7 +132,7 @@ with gr.Blocks(css="footer{display:none !important}", theme=theme) as demo:
             placeholder="Enter your prompt",
         )
         run_button = gr.Button("Generate")
-    # result = gr.Gallery(label="Left is Base and Right is Lora"),
+    # result = gr.Gallery(label="Right is Res-Adapt-LORA and Left is Base"),
     with gr.Accordion("Advanced options", open=False):
         with gr.Row():
             use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=False)
@@ -250,7 +253,7 @@ with gr.Blocks(css="footer{display:none !important}", theme=theme) as demo:
             guidance_scale_base,
             num_inference_steps_base,
         ],
-        outputs=gr.Gallery(label="Left is Base and Right is Lora"),
+        outputs=gr.Gallery(label="Right is Res-Adapt-LORA and Left is Base"),
         api_name="run",
     )