Update app.py

app.py

@@ -5,11 +5,11 @@ import torch
 import spaces
 
 from PIL import Image
-from diffusers import FlowMatchEulerDiscreteScheduler
-from optimization import optimize_pipeline_
-from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
-from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
-from qwenimage.qwen_fa3_processor import QwenDoubleStreamAttnProcessorFA3
+from diffusers import FlowMatchEulerDiscreteScheduler, QwenImageEditPlusPipeline
+# from optimization import optimize_pipeline_
+# from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
+# from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
+# from qwenimage.qwen_fa3_processor import QwenDoubleStreamAttnProcessorFA3
 
 from huggingface_hub import InferenceClient
 import math
@@ -243,12 +243,12 @@ pipe.load_lora_weights(
     )
 pipe.fuse_lora()
 
-# Apply the same optimizations from the first version
-pipe.transformer.__class__ = QwenImageTransformer2DModel
-pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
+# # Apply the same optimizations from the first version
+# pipe.transformer.__class__ = QwenImageTransformer2DModel
+# pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
 
-# --- Ahead-of-time compilation ---
-optimize_pipeline_(pipe, image=[Image.new("RGB", (1024, 1024)), Image.new("RGB", (1024, 1024))], prompt="prompt")
+# # --- Ahead-of-time compilation ---
+# optimize_pipeline_(pipe, image=[Image.new("RGB", (1024, 1024)), Image.new("RGB", (1024, 1024))], prompt="prompt")
 
 # --- UI Constants and Helpers ---
 MAX_SEED = np.iinfo(np.int32).max