Update filepath

pipeline/morph_pipeline_successed_ver1.py

@@ -1108,6 +1108,7 @@ class AudioLDM2MorphPipeline(DiffusionPipeline,TextualInversionLoaderMixin):
         morphing_with_lora=False,
         use_morph_prompt=False,
     ):  
+        device = "cuda" if torch.cuda.is_available() else "cpu"
         # 0. Load the pre-trained AP-adapter model
         layer_num = 0
         cross = [None, None, 768, 768, 1024, 1024, None, None]
@@ -1140,7 +1141,7 @@ class AudioLDM2MorphPipeline(DiffusionPipeline,TextualInversionLoaderMixin):
                 else:
                     attn_procs[name] = AttnProcessor2_0()
 
-        state_dict = torch.load(adapter_weight, map_location="cuda")
+        state_dict = torch.load(adapter_weight, map_location=device)
         for name, processor in attn_procs.items():
             if hasattr(processor, 'to_v_ip') or hasattr(processor, 'to_k_ip'):
                 weight_name_v = name + ".to_v_ip.weight"
@@ -1164,7 +1165,6 @@ class AudioLDM2MorphPipeline(DiffusionPipeline,TextualInversionLoaderMixin):
         # print(f"height: {height}, original_waveform_length: {original_waveform_length}") # height: 1000, original_waveform_length: 160000
 
         # # 2. Define call parameters
-        device = "cuda" if torch.cuda.is_available() else "cpu"
         do_classifier_free_guidance = guidance_scale > 1.0
         self.use_lora = use_lora
         self.use_adain = use_adain