Update app.py

app.py

@@ -1,3 +1,4 @@
+# app.py
 from diffusers import DDPMPipeline
 import torch
 import numpy as np
@@ -7,33 +8,31 @@ import torchvision.transforms as transforms
 from PIL import Image
 import logging
 
-#–– Set up logging
 logging.basicConfig(level=logging.INFO)
 
-#–– Check for accelerate
+# Optional: warn if 'accelerate' is missing
 try:
     from accelerate import Accelerator
     logging.info("Accelerate library found.")
 except ImportError:
-    logging.warning("Accelerate library not found; for large models, 'accelerate' is recommended.")
+    logging.warning("Accelerate library not found; it's recommended for large models.")
 
-#–– Load the DDPM pipeline
+# Load DDPM pipeline
 MODEL_ID = "ahmetyaylalioglu/textile_diffusion_ddpm"
 logging.info(f"Loading model from {MODEL_ID}...")
 pipeline = DDPMPipeline.from_pretrained(MODEL_ID)
 
-#–– Device setup (ZeroGPU → CPU)
+# ZeroGPU → CPU fallback
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 logging.info(f"Using device: {device}")
 pipeline.to(device)
-pipeline.unet.to(torch.float32)   # ensure CPU‐friendly dtype
+pipeline.unet.to(torch.float32)  # ensure CPU dtype
 pipeline.unet.eval()
 
-#–– Image generation function
 def generate_images(seed, num_images):
     try:
         seed = int(seed)
-        num_images = min(int(num_images), 16)  # cap to 16 to avoid OOM
+        num_images = min(int(num_images), 16)
         logging.info(f"Generating {num_images} images with seed {seed}")
 
         torch.manual_seed(seed)
@@ -43,10 +42,9 @@ def generate_images(seed, num_images):
         grid = make_grid([transforms.ToTensor()(img) for img in imgs], nrow=min(4, num_images))
         return transforms.ToPILImage()(grid)
     except Exception as e:
-        logging.error(f"Error in generate_images: {e}")
+        logging.error(f"generate_images error: {e}")
         return None
 
-#–– Gradio UI
 interface = gr.Interface(
     fn=generate_images,
     inputs=[
@@ -55,8 +53,8 @@ interface = gr.Interface(
     ],
     outputs="image",
     title="Textile Diffusion (DDPM)",
-    description="Generate textile patterns via a DDPM model from Hugging Face."
+    description="Generate textile patterns via a DDPM model."
 )
 
 if __name__ == "__main__":
-    interface.launch(share=True)
+    interface.launch(share=True)