Update app.py

app.py

@@ -1,7 +1,6 @@
 import os
 import gradio as gr
 import numpy as np
-import spaces
 import torch
 import random
 from PIL import Image
@@ -9,6 +8,14 @@ from typing import Iterable
 from gradio.themes import Soft
 from gradio.themes.utils import colors, fonts, sizes
 
+
+class MockSpaces:
+    def GPU(self, duration=0):
+        def decorator(func):
+            return func
+        return decorator
+spaces = MockSpaces()
+
 colors.steel_blue = colors.Color(
     name="steel_blue",
     c50="#EBF3F8",
@@ -74,21 +81,10 @@ class SteelBlueTheme(Soft):
             color_accent_soft="*primary_100",
             block_label_background_fill="*primary_200",
         )
-
 steel_blue_theme = SteelBlueTheme()
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-print("CUDA_VISIBLE_DEVICES=", os.environ.get("CUDA_VISIBLE_DEVICES"))
-print("torch.__version__ =", torch.__version__)
-print("torch.version.cuda =", torch.version.cuda)
-print("cuda available:", torch.cuda.is_available())
-print("cuda device count:", torch.cuda.device_count())
-if torch.cuda.is_available():
-    print("current device:", torch.cuda.current_device())
-    print("device name:", torch.cuda.get_device_name(torch.cuda.current_device()))
-
-print("Using device:", device)
+print("CUDA_VISIBLE_DEVICES:", os.environ.get("CUDA_VISIBLE_DEVICES"))
+print("GPU Count:", torch.cuda.device_count())
 
 from diffusers import FlowMatchEulerDiscreteScheduler
 from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
@@ -96,54 +92,45 @@ from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
 from qwenimage.qwen_fa3_processor import QwenDoubleStreamAttnProcessorFA3
 
 dtype = torch.bfloat16
-device = "cuda" if torch.cuda.is_available() else "cpu"
+
+print("Loading Transformer with split config...")
+transformer_model = QwenImageTransformer2DModel.from_pretrained(
+    "linoyts/Qwen-Image-Edit-Rapid-AIO", 
+    subfolder='transformer',
+    torch_dtype=dtype,
+    device_map="auto"
+)
+
+print("Loading Pipeline...")
 
 pipe = QwenImageEditPlusPipeline.from_pretrained(
     "Qwen/Qwen-Image-Edit-2509",
-    transformer=QwenImageTransformer2DModel.from_pretrained(
-        "linoyts/Qwen-Image-Edit-Rapid-AIO", # [transformer weights extracted from: Phr00t/Qwen-Image-Edit-Rapid-AIO]
-        subfolder='transformer',
-        torch_dtype=dtype,
-        device_map='cuda'
-    ),
-    torch_dtype=dtype
-).to(device)
+    transformer=transformer_model,
+    torch_dtype=dtype,
+    device_map="auto" 
+)
 
-pipe.load_lora_weights("autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime",
-                       weight_name="Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors",
-                       adapter_name="anime")
-pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multiple-angles",
-                       weight_name="镜头转换.safetensors",
-                       adapter_name="multiple-angles")
-pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Light_restoration",
-                       weight_name="移除光影.safetensors",
-                       adapter_name="light-restoration")
-pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Relight",
-                       weight_name="Qwen-Edit-Relight.safetensors",
-                       adapter_name="relight")
-pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multi-Angle-Lighting",
-                       weight_name="多角度灯光-251116.safetensors",
-                       adapter_name="multi-angle-lighting")
-pipe.load_lora_weights("tlennon-ie/qwen-edit-skin",
-                       weight_name="qwen-edit-skin_1.1_000002750.safetensors",
-                       adapter_name="edit-skin")
-pipe.load_lora_weights("lovis93/next-scene-qwen-image-lora-2509",
-                       weight_name="next-scene_lora-v2-3000.safetensors",
-                       adapter_name="next-scene")
-pipe.load_lora_weights("vafipas663/Qwen-Edit-2509-Upscale-LoRA",
-                       weight_name="qwen-edit-enhance_64-v3_000001000.safetensors",
-                       adapter_name="upscale-image")
 
+pipe.load_lora_weights("autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime", weight_name="Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors", adapter_name="anime")
+pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multiple-angles", weight_name="镜头转换.safetensors", adapter_name="multiple-angles")
+pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Light_restoration", weight_name="移除光影.safetensors", adapter_name="light-restoration")
+pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Relight", weight_name="Qwen-Edit-Relight.safetensors", adapter_name="relight")
+pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multi-Angle-Lighting", weight_name="多角度灯光-251116.safetensors", adapter_name="multi-angle-lighting")
+pipe.load_lora_weights("tlennon-ie/qwen-edit-skin", weight_name="qwen-edit-skin_1.1_000002750.safetensors", adapter_name="edit-skin")
+pipe.load_lora_weights("lovis93/next-scene-qwen-image-lora-2509", weight_name="next-scene_lora-v2-3000.safetensors", adapter_name="next-scene")
+pipe.load_lora_weights("vafipas663/Qwen-Edit-2509-Upscale-LoRA", weight_name="qwen-edit-enhance_64-v3_000001000.safetensors", adapter_name="upscale-image")
+
+try:
+    pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
+except Exception as e:
+    print(f"Warning: FA3 set skipped: {e}")
 
-pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
 MAX_SEED = np.iinfo(np.int32).max
 
 def update_dimensions_on_upload(image):
     if image is None:
         return 1024, 1024
-    
     original_width, original_height = image.size
-    
     if original_width > original_height:
         new_width = 1024
         aspect_ratio = original_height / original_width
@@ -152,55 +139,38 @@ def update_dimensions_on_upload(image):
         new_height = 1024
         aspect_ratio = original_width / original_height
         new_width = int(new_height * aspect_ratio)
-        
-    # Ensure dimensions are multiples of 8
     new_width = (new_width // 8) * 8
     new_height = (new_height // 8) * 8
-    
     return new_width, new_height
 
 @spaces.GPU(duration=30)
-def infer(
-    input_image,
-    prompt,
-    lora_adapter,
-    seed,
-    randomize_seed,
-    guidance_scale,
-    steps,
-    progress=gr.Progress(track_tqdm=True)
-):
+def infer(input_image, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps, progress=gr.Progress(track_tqdm=True)):
     if input_image is None:
         raise gr.Error("Please upload an image to edit.")
-
-    if lora_adapter == "Photo-to-Anime":
-        pipe.set_adapters(["anime"], adapter_weights=[1.0])
-    elif lora_adapter == "Multiple-Angles":
-        pipe.set_adapters(["multiple-angles"], adapter_weights=[1.0])
-    elif lora_adapter == "Light-Restoration":
-        pipe.set_adapters(["light-restoration"], adapter_weights=[1.0])
-    elif lora_adapter == "Relight":
-        pipe.set_adapters(["relight"], adapter_weights=[1.0])
-    elif lora_adapter == "Multi-Angle-Lighting":
-        pipe.set_adapters(["multi-angle-lighting"], adapter_weights=[1.0])
-    elif lora_adapter == "Edit-Skin":
-        pipe.set_adapters(["edit-skin"], adapter_weights=[1.0])
-    elif lora_adapter == "Next-Scene":
-        pipe.set_adapters(["next-scene"], adapter_weights=[1.0])
-    elif lora_adapter == "Upscale-Image":
-        pipe.set_adapters(["upscale-image"], adapter_weights=[1.0])
-        
+    
+    adapters_map = {
+        "Photo-to-Anime": "anime",
+        "Multiple-Angles": "multiple-angles",
+        "Light-Restoration": "light-restoration",
+        "Relight": "relight",
+        "Multi-Angle-Lighting": "multi-angle-lighting",
+        "Edit-Skin": "edit-skin",
+        "Next-Scene": "next-scene",
+        "Upscale-Image": "upscale-image"
+    }
+    
+    if lora_adapter in adapters_map:
+        pipe.set_adapters([adapters_map[lora_adapter]], adapter_weights=[1.0])
+            
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
-
-    generator = torch.Generator(device=device).manual_seed(seed)
+    
+    generator = torch.Generator(device=pipe.device).manual_seed(seed)
+    
     negative_prompt = "worst quality, low quality, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, blurry"
-
     original_image = input_image.convert("RGB")
-    
-    # Use the new function to update dimensions
     width, height = update_dimensions_on_upload(original_image)
-
+    
     result = pipe(
         image=original_image,
         prompt=prompt,
@@ -211,88 +181,46 @@ def infer(
         generator=generator,
         true_cfg_scale=guidance_scale,
     ).images[0]
-
     return result, seed
 
 @spaces.GPU(duration=30)
 def infer_example(input_image, prompt, lora_adapter):
     input_pil = input_image.convert("RGB")
-    guidance_scale = 1.0
-    steps = 4
-    result, seed = infer(input_pil, prompt, lora_adapter, 0, True, guidance_scale, steps)
+    result, seed = infer(input_pil, prompt, lora_adapter, 0, True, 1.0, 4)
     return result, seed
 
-
 css="""
-#col-container {
-    margin: 0 auto;
-    max-width: 960px;
-}
-#main-title h1 {font-size: 2.1em !important;}
+#col-container { margin: 0 auto; max-width: 960px; }
+#main-title h1 { font-size: 2.1em !important; }
 """
 
 with gr.Blocks(css=css, theme=steel_blue_theme) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown("# **Qwen-Image-Edit-2509-LoRAs-Fast**", elem_id="main-title")
-        gr.Markdown("Perform diverse image edits using specialized [LoRA](https://huggingface.co/models?other=base_model:adapter:Qwen/Qwen-Image-Edit-2509) adapters for the [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit-2509) model.")
-
+        gr.Markdown("# **Qwen-Image-Edit-2509-LoRAs-Fast (2xA40 Fixed)**", elem_id="main-title")
+        gr.Markdown("Forked & Optimized for RunPod 2xGPU Split.")
+        
         with gr.Row(equal_height=True):
             with gr.Column():
                 input_image = gr.Image(label="Upload Image", type="pil", height=290)
-                
-                prompt = gr.Text(
-                    label="Edit Prompt",
-                    show_label=True,
-                    placeholder="e.g., transform into anime..",
-                )
-
+                prompt = gr.Text(label="Edit Prompt", show_label=True, placeholder="e.g., transform into anime..")
                 run_button = gr.Button("Edit Image", variant="primary")
-
             with gr.Column():
                 output_image = gr.Image(label="Output Image", interactive=False, format="png", height=350)
-                
-                with gr.Row():
-                    lora_adapter = gr.Dropdown(
-                        label="Choose Editing Style",
-                        choices=["Photo-to-Anime", "Multiple-Angles", "Light-Restoration", "Multi-Angle-Lighting", "Upscale-Image", "Relight", "Next-Scene", "Edit-Skin"],
-                        value="Photo-to-Anime"
-                    )
-                with gr.Accordion("Advanced Settings", open=False, visible=False):
-                    seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
-                    randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
-                    guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=1.0)
-                    steps = gr.Slider(label="Inference Steps", minimum=1, maximum=50, step=1, value=4)
         
-        gr.Examples(
-            examples=[
-                ["examples/1.jpg", "Transform into anime.", "Photo-to-Anime"],
-                ["examples/5.jpg", "Remove shadows and relight the image using soft lighting.", "Light-Restoration"],
-                ["examples/4.jpg", "Use a subtle golden-hour filter with smooth light diffusion.", "Relight"],
-                ["examples/2.jpeg", "Rotate the camera 45 degrees to the left.", "Multiple-Angles"],
-                ["examples/7.jpg", "Light source from the Right Rear", "Multi-Angle-Lighting"],
-                ["examples/10.jpeg", "Upscale the image.", "Upscale-Image"],
-                ["examples/7.jpg", "Light source from the Below", "Multi-Angle-Lighting"],
-                ["examples/2.jpeg", "Switch the camera to a top-down right corner view.", "Multiple-Angles"],
-                ["examples/9.jpg", "The camera moves slightly forward as sunlight breaks through the clouds, casting a soft glow around the character's silhouette in the mist. Realistic cinematic style, atmospheric depth.", "Next-Scene"],
-                ["examples/8.jpg", "Make the subjects skin details more prominent and natural.", "Edit-Skin"],
-                ["examples/6.jpg", "Switch the camera to a bottom-up view.", "Multiple-Angles"],
-                ["examples/6.jpg", "Rotate the camera 180 degrees upside down.", "Multiple-Angles"],
-                ["examples/4.jpg", "Rotate the camera 45 degrees to the right.", "Multiple-Angles"],
-                ["examples/4.jpg", "Switch the camera to a top-down view.", "Multiple-Angles"],
-                ["examples/4.jpg", "Switch the camera to a wide-angle lens.", "Multiple-Angles"],
-            ],
-            inputs=[input_image, prompt, lora_adapter],
-            outputs=[output_image, seed],
-            fn=infer_example,
-            cache_examples=False,
-            label="Examples"
-        )
-
-    run_button.click(
-        fn=infer,
-        inputs=[input_image, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps],
-        outputs=[output_image, seed]
-    )
+        with gr.Row():
+            lora_adapter = gr.Dropdown(
+                label="Choose Editing Style",
+                choices=["Photo-to-Anime", "Multiple-Angles", "Light-Restoration", "Multi-Angle-Lighting", "Upscale-Image", "Relight", "Next-Scene", "Edit-Skin"],
+                value="Photo-to-Anime"
+            )
+        
+        with gr.Accordion("Advanced Settings", open=False, visible=False):
+            seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
+            randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
+            guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=1.0)
+            steps = gr.Slider(label="Inference Steps", minimum=1, maximum=50, step=1, value=4)
+            
+        run_button.click(fn=infer, inputs=[input_image, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps], outputs=[output_image, seed])
 
 if __name__ == "__main__":
-    demo.queue(max_size=30).launch(mcp_server=True, ssr_mode=False, show_error=True)
+    demo.queue(max_size=30).launch(server_name="0.0.0.0", server_port=7860, ssr_mode=False)