Update app.py

app.py

@@ -33,9 +33,9 @@ import datetime
 import cyper
 from PIL import Image
 
-from accelerate import Accelerator
+#from accelerate import Accelerator
 
-accelerator = Accelerator(mixed_precision="bf16")
+#accelerator = Accelerator(mixed_precision="bf16")
 
 hftoken = os.getenv("HF_AUTH_TOKEN") 
 
@@ -95,8 +95,8 @@ ll_transformer=SD3Transformer2DModel.from_pretrained("ford442/stable-diffusion-3
 pipe.transformer=ll_transformer.eval()
 pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/UltraReal.safetensors")
 
-pipe.to(accelerator.device)
-#pipe.to(device=device, dtype=torch.bfloat16)
+#pipe.to(accelerator.device)
+pipe.to(device=device, dtype=torch.bfloat16)
 
 upscaler_2 = UpscaleWithModel.from_pretrained("Kim2091/ClearRealityV1").to(torch.device('cpu'))
 
@@ -124,8 +124,7 @@ def infer_60(
     seed = random.randint(0, MAX_SEED)
     generator = torch.Generator(device='cuda').manual_seed(seed)
     print('-- generating image --')
-    with accelerator.autocast():
-      sd_image = pipe(
+    sd_image = pipe(
             prompt=prompt,
             prompt_2=prompt,
             prompt_3=prompt,
@@ -138,7 +137,7 @@ def infer_60(
             height=height,
             generator=generator,
             max_sequence_length=512
-      ).images[0]
+    ).images[0]
     print('-- got image --')
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
     sd35_path = f"sd35ll_{timestamp}.png"
@@ -179,8 +178,7 @@ def infer_90(
     seed = random.randint(0, MAX_SEED)
     generator = torch.Generator(device='cuda').manual_seed(seed)
     print('-- generating image --')
-    with accelerator.autocast():
-      sd_image = pipe(
+    sd_image = pipe(
             prompt=prompt,
             prompt_2=prompt,
             prompt_3=prompt,
@@ -193,7 +191,7 @@ def infer_90(
             height=height,
             generator=generator,
             max_sequence_length=512
-      ).images[0]
+    ).images[0]
     print('-- got image --')
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
     sd35_path = f"sd35ll_{timestamp}.png"
@@ -234,8 +232,7 @@ def infer_110(
     seed = random.randint(0, MAX_SEED)
     generator = torch.Generator(device='cuda').manual_seed(seed)
     print('-- generating image --')
-    with accelerator.autocast():
-      sd_image = pipe(
+    sd_image = pipe(
             prompt=prompt,
             prompt_2=prompt,
             prompt_3=prompt,
@@ -248,7 +245,7 @@ def infer_110(
             height=height,
             generator=generator,
             max_sequence_length=512
-      ).images[0]
+    ).images[0]
     print('-- got image --')
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
     sd35_path = f"sd35ll_{timestamp}.png"