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")
 
  #####################