tcd

app.py

@@ -9,7 +9,7 @@ from diffusers import AutoPipelineForImage2Image
 from diffusers.utils import load_image
 import math
 from DeepCache import DeepCacheSDHelper
-from scheduling_tcd import TCDScheduler
+
 
 adapter_id = "latent-consistency/lcm-lora-sdv1-5"
 
@@ -31,10 +31,10 @@ def resize(value,img):
 def infer(model_id,source_img, prompt, steps, seed, Strength):
     pipe = OVStableDiffusionImg2ImgPipeline.from_pretrained(model_id, torch_dtype=torch.float16, export=True) if torch.cuda.is_available() else AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo")
     pipe = pipe.to(device)
-    pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)
-    tcd_lora_id = "h1t/TCD-SDXL-LoRA"
-    pipe.load_lora_weights(tcd_lora_id)
-    pipe.fuse_lora()
+    # pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)
+    # tcd_lora_id = "h1t/TCD-SDXL-LoRA"
+    # pipe.load_lora_weights(tcd_lora_id)
+    # pipe.fuse_lora()
     start_time = time.time()
     generator = torch.Generator(device).manual_seed(seed)  
     if int(steps * Strength) < 1: