torchoutil.nn.functional.powerset module

build_powerset_mapping(
num_classes: int,
max_set_size: int,
dtype: dtype | None | Literal['default'] | str | DTypeEnum = None,
device: device | None | Literal['default', 'cuda_if_available'] | str | int = None,
) → Tensor2D[source]

Build powerset mapping matrix of shape (num_powerset_classes, num_classes).

get_num_powerset_classes(
num_classes: int,
max_set_size: int,
) → int[source]
multilabel_to_powerset(
multilabel: Tensor,
*,
num_classes: int,
max_set_size: int,
) → Tensor3D[source]
multilabel_to_powerset(
multilabel: Tensor,
*,
mapping: Tensor,
) → Tensor3D
Args:

multilabel: (batch_size, num_frames, num_classes) Tensor

Returns:

powerset: (batch_size, num_frames, num_powerset_classes) Tensor

powerset_to_multilabel(
powerset: Tensor,
soft: bool = False,
*,
num_classes: int,
max_set_size: int,
) → Tensor3D[source]
powerset_to_multilabel(
powerset: Tensor,
soft: bool = False,
*,
mapping: Tensor,
) → Tensor3D
Args:

powerset: Powerset logits, probabilities or onehot tensor of shape (batch_size, num_frames, num_powerset_classes).

Returns:

multilabel: (batch_size, num_frames, num_classes) Tensor