Upload dc.py

dc.py

@@ -552,7 +552,7 @@ def dynamic_gpu_duration(func, duration, *args):
     @torch.inference_mode()
     @spaces.GPU(duration=duration)
     def wrapped_func():
-        return func(*args)
+        yield from func(*args)
 
     return wrapped_func()
 
@@ -578,8 +578,8 @@ def sd_gen_generate_pipeline(*args):
     if load_lora_cpu:
         msg_load_lora = "Updating LoRAs in CPU (Slow but saves GPU usage)..."
 
-    #if lora_list != sd_gen.model.lora_memory and lora_list != [None] * 5:
-    #    yield msg_load_lora, gr.update(), gr.update()
+    if lora_list != sd_gen.model.lora_memory and lora_list != [None] * 5:
+        yield msg_load_lora, gr.update(), gr.update()
 
     # Load lora in CPU
     if load_lora_cpu:
@@ -609,7 +609,7 @@ def sd_gen_generate_pipeline(*args):
     if verbose_arg:
         gr.Info(msg_request)
         print(msg_request)
-    #yield msg_request.replace("\n", "<br>"), gr.update(), gr.update()
+    yield msg_request.replace("\n", "<br>"), gr.update(), gr.update()
 
     start_time = time.time()
 
@@ -686,7 +686,6 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     gpu_duration = 59
 
     images: list[tuple[PIL.Image.Image, str | None]] = []
-    info_state = info_images = ""
     progress(0, desc="Preparing...")
 
     if randomize_seed:
@@ -710,8 +709,8 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     progress(1, desc="Preparation completed. Starting inference...")
 
     progress(0, desc="Loading model...")
-    for _ in sd_gen.load_new_model(model_name, vae, TASK_MODEL_LIST[0]):
-        pass
+    for m in sd_gen.load_new_model(model_name, vae, TASK_MODEL_LIST[0]):
+        progress(0.5, desc=m)
     progress(1, desc="Model loaded.")
     progress(0, desc="Starting Inference...")
     images = None
@@ -727,6 +726,7 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
         True, None, None, "plus_face", "original", 0.7, None, None, "base", "style", 0.7, 0.0,
         load_lora_cpu, verbose_info, gpu_duration
     ):
+        progress(0.5, desc=info_state)
         images = stream_images
     progress(1, desc="Inference completed.")
     output_image = images[0][0] if images else None