bugfixes

app.py

@@ -105,6 +105,7 @@ def _vamp(
         codes, mask,
         batch_size=1 if api else 1,
         feedback_steps=1,
+        _sampling_steps=12 if sig.duration <6.0 else 24,
         time_stretch_factor=stretch_factor,
         return_mask=True,
         temperature=sampletemp,

vampnet/__init__.py

@@ -55,8 +55,9 @@ def download_finetuned(name):
     filenames = ["coarse.pth", "c2f.pth"]
     paths = []
     for filename in filenames:
-        path = f"{MODELS_DIR}/{name}/loras/{filename}"
+        path = f"{MODELS_DIR}/loras/{name}/{filename}"
         if not Path(path).exists():
+            print(f"{path} does not exist, downloading")
             path = hf_hub_download(
                 repo_id=repo_id,
                 filename=filename,

vampnet/interface.py

@@ -537,7 +537,7 @@ class Interface(torch.nn.Module):
             zv, 
             mask=mask,
             typical_filtering=True,
-            _sampling_steps=[2],
+            _sampling_steps=2,
             return_mask=True
         )
         mask_z = torch.cat(

vampnet/modules/transformer.py

@@ -595,13 +595,13 @@ class VampNet(at.ml.BaseModel):
         self, 
         codec,
         time_steps: int = 300,
-        _sampling_steps: List[int] = [12],
+        _sampling_steps: int = 12,
         start_tokens: Optional[torch.Tensor] = None,
         temperature: float = 1.0,
         mask: Optional[torch.Tensor] = None,
         mask_temperature: float = 10.5,
         typical_filtering=True,
-        typical_mass=0.2,
+        typical_mass=0.15,
         typical_min_tokens=64,
         top_p=None,
         seed: int = None,
@@ -613,7 +613,7 @@ class VampNet(at.ml.BaseModel):
     ):
         if seed is not None:
             at.util.seed(seed)
-        sampling_steps = sum(_sampling_steps)
+        sampling_steps = _sampling_steps
         logging.debug(f"beginning generation with {sampling_steps} steps")
 
         #####################