yes

app.py

@@ -1,16 +1,15 @@
-import spaces
-
 import torch
 import gradio as gr
 import numpy as np
 import matplotlib.pyplot as plt
+from PIL import Image
+import spaces
 from transformers import T5Tokenizer, T5EncoderModel
 from diffusers import StableDiffusionXLPipeline, DDIMScheduler, EulerDiscreteScheduler, DPMSolverMultistepScheduler
 from safetensors.torch import load_file
 from huggingface_hub import hf_hub_download
 from two_stream_shunt_adapter import TwoStreamShuntAdapter
 from configs import T5_SHUNT_REPOS
-from PIL import Image
 
 # ─── Device & Model Setup ─────────────────────────────────────
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -69,8 +68,7 @@ def plot_heat(mat, title):
     plt.savefig(buf, format="png", bbox_inches='tight')
     buf.seek(0)
     plt.close(fig)
-    pil_image = Image.open(buf)
-    return pil_image
+    return buf
 
 # ─── SDXL Text Encoding ───────────────────────────────────────
 def encode_sdxl_prompt(prompt, negative_prompt=""):
@@ -136,7 +134,6 @@ def encode_sdxl_prompt(prompt, negative_prompt=""):
     }
 
 # ─── Inference ────────────────────────────────────────────────
-@spaces.GPU
 @torch.no_grad()
 def infer(prompt, negative_prompt, adapter_l_file, adapter_g_file, strength, noise, gate_prob, 
           use_anchor, steps, cfg_scale, scheduler_name, width, height, seed):
@@ -344,15 +341,8 @@ with gr.Blocks(title="SDXL Dual Shunt Adapter", theme=gr.themes.Soft()) as demo:
             prompt, negative_prompt, adapter_l, adapter_g, strength, noise, gate_prob, 
             use_anchor, steps, cfg_scale, scheduler_name, width, height, seed
         ],
-        outputs=[
-            out_img, 
-            delta_l, 
-            gate_l, 
-            delta_g, 
-            gate_g, 
-            stats_l, 
-            stats_g]
+        outputs=[out_img, delta_l, gate_l, delta_g, gate_g, stats_l, stats_g]
     )
 
 if __name__ == "__main__":
-    demo.launch(share=True)
+    demo.launch()

requirements.txt

@@ -1,4 +1,3 @@
-spaces
 sentencepiece
 accelerate
 diffusers
@@ -6,5 +5,4 @@ invisible_watermark
 torch
 transformers
 xformers
-matplotlib
-pillow
+matplotlib