Upload dc.py

dc.py

@@ -679,7 +679,7 @@ class GuiSD:
         #progress(1, desc="Inference preparation completed. Starting inference...")
 
         info_state = "" # for yield version
-        return self.infer_short(self.model, pipe_params), info_state
+        return self.infer_short(self.model, pipe_params, progress), info_state
 ## END MOD
 
 def dynamic_gpu_duration(func, duration, *args):
@@ -804,8 +804,8 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
 
     prompt, negative_prompt = insert_model_recom_prompt(prompt, negative_prompt, model_name)
     progress(0.5, desc="Preparing...")
-    lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt = \
-        set_prompt_loras(prompt, model_name, lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt)
+    #lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt = \
+    #    set_prompt_loras(prompt, model_name, lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt)
     lora1 = get_valid_lora_path(lora1)
     lora2 = get_valid_lora_path(lora2)
     lora3 = get_valid_lora_path(lora3)
@@ -814,7 +814,7 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     progress(1, desc="Preparation completed. Starting inference...")
 
     progress(0, desc="Loading model...")
-    sd_gen.load_new_model(model_name, vae, TASK_MODEL_LIST[0])
+    sd_gen.load_new_model(model_name, vae, TASK_MODEL_LIST[0], progress)
     progress(1, desc="Model loaded.")
     progress(0, desc="Starting Inference...")
     images, info = sd_gen_generate_pipeline(prompt, negative_prompt, 1, num_inference_steps,