in src/diarizers/utils.py [0:0]
def __call__(self, features):
"""_summary_
Args:
features (_type_): _description_
Returns:
_type_: _description_
"""
batch = {}
speakers = [f["nb_speakers"] for f in features]
labels = [f["labels"] for f in features]
batch["labels"] = self.pad_targets(labels, speakers)
batch["waveforms"] = torch.stack([f["waveforms"] for f in features])
return batch