Remove upscaler

README.md

@@ -14,7 +14,6 @@ pinned: true
 header: mini
 license: apache-2.0
 models:
-- fal/AuraSR-v2
 - fluently/Fluently-v4
 - Linaqruf/anything-v3-1
 - Lykon/dreamshaper-8
@@ -22,9 +21,6 @@ models:
 - runwayml/stable-diffusion-v1-5
 - SG161222/Realistic_Vision_V5.1_noVAE
 preload_from_hub:
-- >-
-  fal/AuraSR-v2
-  config.json,model.safetensors
 - >-
   fluently/Fluently-v4
   text_encoder/model.fp16.safetensors,unet/diffusion_pytorch_model.fp16.safetensors,vae/diffusion_pytorch_model.fp16.safetensors
@@ -52,7 +48,6 @@ Gradio app for Stable Diffusion 1.5 including:
 * multiple samplers with Karras schedule
 * Compel prompting
 * 100+ styles from sdxl_prompt_styler
-* AuraSR GAN
 * DeepCache and ToMe
 * optional TAESD
 

app.py

@@ -169,13 +169,6 @@ with gr.Blocks(
                             value=True,
                             scale=1,
                         )
-                        upscale_4x = gr.Checkbox(
-                            interactive=cfg.NUM_IMAGES == 1,
-                            elem_classes=["checkbox"],
-                            label="Upscale 4x",
-                            value=False,
-                            scale=3,
-                        )
 
             with gr.TabItem("🛠️ Advanced"):
                 with gr.Group():
@@ -270,12 +263,6 @@ with gr.Blocks(
         js=seed_js,
     )
 
-    num_images.change(
-        lambda n, upscale: gr.Checkbox(interactive=n == 1, value=upscale if n == 1 else False),
-        inputs=[num_images, upscale_4x],
-        outputs=[upscale_4x],
-    )
-
     file_format.change(
         lambda f: gr.Gallery(format=f),
         inputs=[file_format],
@@ -307,7 +294,6 @@ with gr.Blocks(
             increment_seed,
             deepcache_interval,
             tome_ratio,
-            upscale_4x,
         ],
     )
 

cli.py

@@ -33,7 +33,6 @@ def main():
     parser.add_argument("--clip-skip", action="store_true")
     parser.add_argument("--truncate", action="store_true")
     parser.add_argument("--karras", action="store_true")
-    parser.add_argument("--upscale", action="store_true")
     parser.add_argument("--no-increment", action="store_false")
     # fmt: on
 
@@ -57,7 +56,6 @@ def main():
         args.no_increment,
         args.deepcache,
         args.tome,
-        args.upscale,
     )
     save_images(images, args.filename)
 

generate.py

@@ -10,7 +10,6 @@ from typing import Callable
 import spaces
 import tomesd
 import torch
-from aura_sr import AuraSR
 from compel import Compel, DiffusersTextualInversionManager, ReturnedEmbeddingsType
 from compel.prompt_parser import PromptParser
 from DeepCache import DeepCacheSDHelper
@@ -56,7 +55,6 @@ class Loader:
     def __new__(cls):
         if cls._instance is None:
             cls._instance = super(Loader, cls).__new__(cls)
-            cls._instance.gan = None
             cls._instance.pipe = None
         return cls._instance
 
@@ -102,7 +100,7 @@ class Loader:
                 model=model,
             )
 
-    def load(self, model, scheduler, karras, taesd, deepcache_interval, upscale, dtype, device):
+    def load(self, model, scheduler, karras, taesd, deepcache_interval, dtype, device):
         model_lower = model.lower()
 
         schedulers = {
@@ -156,10 +154,6 @@ class Loader:
                 or self.pipe.scheduler.config.use_karras_sigmas == karras
             )
 
-            if upscale and not self.gan:
-                print("Loading fal/AuraSR-v2...")
-                self.gan = AuraSR.from_pretrained("fal/AuraSR-v2")
-
             if same_model:
                 if not same_scheduler:
                     print(f"Switching to {scheduler}...")
@@ -169,7 +163,7 @@ class Loader:
                     self.pipe.scheduler = schedulers[scheduler](**scheduler_kwargs)
                 self._load_vae(model_lower, taesd, variant)
                 self._load_deepcache(interval=deepcache_interval)
-                return self.pipe, self.gan
+                return self.pipe
             else:
                 print(f"Unloading {model_name.lower()}...")
                 self.pipe = None
@@ -186,16 +180,8 @@ class Loader:
         self._load_vae(model_lower, taesd, variant)
         self._load_deepcache(interval=deepcache_interval)
 
-        if upscale and self.gan is None:
-            print("Loading fal/AuraSR-v2...")
-            self.gan = AuraSR.from_pretrained("fal/AuraSR-v2")
-
-        if not upscale and self.gan is not None:
-            print("Unloading fal/AuraSR-v2...")
-            self.gan = None
-
         torch.cuda.empty_cache()
-        return self.pipe, self.gan
+        return self.pipe
 
 
 # applies tome to the pipeline
@@ -261,7 +247,6 @@ def generate(
     increment_seed=True,
     deepcache_interval=1,
     tome_ratio=0,
-    upscale=False,
     log: Callable[[str], None] = None,
     Error=Exception,
 ):
@@ -289,13 +274,12 @@ def generate(
     with torch.inference_mode():
         start = time.perf_counter()
         loader = Loader()
-        pipe, gan = loader.load(
+        pipe = loader.load(
             model,
             scheduler,
             karras,
             taesd,
             deepcache_interval,
-            upscale,
             DTYPE,
             DEVICE,
         )
@@ -347,10 +331,6 @@ def generate(
                         height=height,
                         width=width,
                     ).images[0]
-                    if upscale:
-                        print("Upscaling image...")
-                        batch_size = 12 if ZERO_GPU else 4  # smaller batch to fit in 8GB
-                        image = gan.upscale_4x_overlapped(image, max_batch_size=batch_size)
                     images.append((image, str(current_seed)))
                 finally:
                     if not ZERO_GPU:
@@ -362,7 +342,6 @@ def generate(
         if ZERO_GPU:
             # spaces always start fresh
             loader.pipe = None
-            loader.gan = None
 
         diff = time.perf_counter() - start
         if log:

requirements.txt

@@ -1,5 +1,4 @@
 accelerate
-aura-sr==0.0.4
 compel
 deepcache==0.1.1
 diffusers

usage.md

@@ -55,10 +55,6 @@ Optionally, the [Karras](https://arxiv.org/abs/2206.00364) noise schedule can be
 * [LMS](https://huggingface.co/docs/diffusers/api/schedulers/lms_discrete)
 * [PNDM](https://huggingface.co/docs/diffusers/api/schedulers/pndm)
 
-#### Upscaler
-
-[AuraSR](https://huggingface.co/fal/AuraSR-v2) from [fal.ai](https://fal.ai) can be enabled to upscale your image 4x. It's disabled if `Images` is greater than **1**, so use it once you've finalized your parameters and found a seed.
-
 ### Advanced
 
 #### DeepCache