Update app.py

app.py

@@ -161,6 +161,7 @@ def randomize_loras(selected_indices):
 
 @spaces.GPU(duration=70)
 def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, progress):
+    print("Entrou aqui!")
     pipe.to("cuda")
     generator = torch.Generator(device="cuda").manual_seed(seed)
     with calculateDuration("Generating image"):
@@ -180,8 +181,8 @@ def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, progress)
 
 @spaces.GPU(duration=70)
 def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps, cfg_scale, width, height, seed):
-    generator = torch.Generator(device="cuda").manual_seed(seed)
     pipe_i2i.to("cuda")
+    generator = torch.Generator(device="cuda").manual_seed(seed)
     image_input = load_image(image_input_path)
     final_image = pipe_i2i(
         prompt=prompt_mash,
@@ -238,6 +239,7 @@ def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_ind
                     pipe.load_lora_weights(lora_path, weight_name=lora["weights"], low_cpu_mem_usage=True, adapter_name=lora_name)
                 else:
                     pipe.load_lora_weights(lora_path, low_cpu_mem_usage=True, adapter_name=lora_name)
+        print(lora_names)
         if image_input is not None:
             pipe_i2i.set_adapters(lora_names, adapter_weights=[lora_scale_1, lora_scale_2])
         else: