Update app.py

app.py

@@ -1,7 +1,4 @@
 #!/usr/bin/env python
-#patch 0.04
-#Func() Dalle Collage Moved Midjourney Space 
-#Pruned DalleCollage Space 
 import os
 import random
 import uuid
@@ -178,20 +175,14 @@ def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str
 
     
 
-DESCRIPTION = """## MidJourney
-
-Drop your best results in the community: [rb.gy/klkbs7](http://rb.gy/klkbs7), Have you tried the stable hamster space? [rb.gy/hfrm2f](http://rb.gy/hfrm2f)
+DESCRIPTION = """## CloneJourney
 """
 
-
-if not torch.cuda.is_available():
-    DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
-
 MAX_SEED = np.iinfo(np.int32).max
-CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1"
+CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "lazy")
 MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048"))
-USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
-ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
+USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "1") == "1"
+ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "1") == "1"
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
@@ -208,11 +199,9 @@ if torch.cuda.is_available():
         pipe.enable_model_cpu_offload()
     else:
         pipe.to(device)
-        print("Loaded on Device!")
 
     if USE_TORCH_COMPILE:
-        pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
-        print("Model Compiled!")
+        pipe.unet = torch.compile(pipe.unet, mode="max-autotune", fullgraph=True)
 
 def save_image(img, path):
     img.save(path)
@@ -232,8 +221,8 @@ def generate(
     filter_name: str = DEFAULT_FILTER_NAME,
     grid_size: str = "2x2",
     seed: int = 0,
-    width: int = 1024,
-    height: int = 1024,
+    width: int = 896,
+    height: int = 1152,
     guidance_scale: float = 3,
     randomize_seed: bool = False,
     use_resolution_binning: bool = True,