Update app.py

app.py

@@ -33,7 +33,6 @@ torch.backends.cudnn.deterministic = False
 #torch.backends.cudnn.benchmark = False
 torch.backends.cuda.preferred_blas_library="cublas"
 #torch.backends.cuda.preferred_linalg_library="cusolver"
-torch.set_float32_matmul_precision("highest")
 
 hftoken = os.getenv("HF_AUTH_TOKEN") 
 
@@ -133,6 +132,7 @@ def infer(
     latent_file,  # Add latents file input
     progress=gr.Progress(track_tqdm=True),
 ):
+    torch.set_float32_matmul_precision("highest")
     seed = random.randint(0, MAX_SEED)
     generator = torch.Generator(device='cuda').manual_seed(seed)
     if expanded:
@@ -267,7 +267,7 @@ def infer(
     refine.save(refine_path,optimize=False,compress_level=0)
     upload_to_ftp(refine_path)
     with torch.no_grad():
-        upscale2 = upscaler_2(downscale, tiling=True, tile_width=1024, tile_height=1024)
+        upscale2 = upscaler_2(refine, tiling=True, tile_width=1024, tile_height=1024)
     print('-- got upscaled image --')
     downscale2 = upscale2.resize((upscale2.width // 4, upscale2.height // 4),Image.LANCZOS)
     upscale_path = f"sd35_upscale_{seed}.png"