debugging..

app.py

@@ -18,21 +18,21 @@ def get_file_size_in_mb(file_path):
 
 
 # Load the models using torch.hub
-# hubert = torch.hub.load("bshall/hubert:main", "hubert_soft", trust_repo=True)
-# acoustic = torch.hub.load("bshall/acoustic-model:main", "hubert_soft", trust_repo=True, pretrained=False)
-# hifigan = torch.hub.load("bshall/hifigan:main", "hifigan_hubert_soft", trust_repo=True, pretrained=False)
+hubert = torch.hub.load("bshall/hubert:main", "hubert_soft", trust_repo=True)
+acoustic = torch.hub.load("bshall/acoustic-model:main", "hubert_soft", trust_repo=True, pretrained=False)
+hifigan = torch.hub.load("bshall/hifigan:main", "hifigan_hubert_soft", trust_repo=True, pretrained=False)
 
 
 # Load the state dictionaries from the CPU-saved files
-hubert = torch.load("hubert_cpu.pt", map_location=torch.device('cpu'))
-acoustic = torch.load("acoustic_cpu.pt", map_location=torch.device('cpu'))
-hifigan = torch.load("hifigan_cpu.pt", map_location=torch.device('cpu'))
+hubert_state_dict = torch.load("hubert_cpu.pt", map_location=torch.device('cpu'))
+acoustic_state_dict = torch.load("acoustic_cpu.pt", map_location=torch.device('cpu'))
+hifigan_state_dict = torch.load("hifigan_cpu.pt", map_location=torch.device('cpu'))
 
 
 # Set the state dictionaries to the models
-# hubert.load_state_dict(hubert_state_dict,  strict=False)
-# acoustic.load_state_dict(acoustic_state_dict,  strict=False)
-# hifigan.load_state_dict(hifigan_state_dict,  strict=False)
+hubert.load_state_dict(hubert_state_dict.state_dict(),  strict=False)
+acoustic.load_state_dict(acoustic_state_dict.state_dict(),  strict=False)
+hifigan.load_state_dict(hifigan_state_dict.state_dict(),  strict=False)
 
 # Move models to CPU (if not already on CPU)
 hubert = hubert.to('cpu')