Class Activations

monai/transforms/post/array.py:69–137

Activation operations, typically `Sigmoid` or `Softmax`. Args: sigmoid: whether to execute sigmoid function on model output before transform. Defaults to ``False``. softmax: whether to execute softmax function on model output before transform. Defaul

class Activations(Transform):
    """
    Activation operations, typically `Sigmoid` or `Softmax`.

    Args:
        sigmoid: whether to execute sigmoid function on model output before transform.
            Defaults to ``False``.
        softmax: whether to execute softmax function on model output before transform.
            Defaults to ``False``.
        other: callable function to execute other activation layers, for example:
            `other = lambda x: torch.tanh(x)`. Defaults to ``None``.
        kwargs: additional parameters to `torch.softmax` (used when ``softmax=True``).
            Defaults to ``dim=0``, unrecognized parameters will be ignored.

    Raises:
        TypeError: When ``other`` is not an ``Optional[Callable]``.

    """

    backend = [TransformBackends.TORCH]

    def __init__(self, sigmoid: bool = False, softmax: bool = False, other: Callable | None = None, **kwargs) -> None:
        self.sigmoid = sigmoid
        self.softmax = softmax
        self.kwargs = kwargs
        if other is not None and not callable(other):
            raise TypeError(f"other must be None or callable but is {type(other).__name__}.")
        self.other = other

    def __call__(
        self,
        img: NdarrayOrTensor,
        sigmoid: bool | None = None,
        softmax: bool | None = None,
        other: Callable | None = None,
    ) -> NdarrayOrTensor:
        """
        Args:
            sigmoid: whether to execute sigmoid function on model output before transform.
                Defaults to ``self.sigmoid``.
            softmax: whether to execute softmax function on model output before transform.
                Defaults to ``self.softmax``.
            other: callable function to execute other activation layers, for example:
                `other = torch.tanh`. Defaults to ``self.other``.

        Raises:
            ValueError: When ``sigmoid=True`` and ``softmax=True``. Incompatible values.
            TypeError: When ``other`` is not an ``Optional[Callable]``.
            ValueError: When ``self.other=None`` and ``other=None``. Incompatible values.

        """
        if sigmoid and softmax:
            raise ValueError("Incompatible values: sigmoid=True and softmax=True.")
        if other is not None and not callable(other):
            raise TypeError(f"other must be None or callable but is {type(other).__name__}.")

        # convert to float as activation must operate on float tensor
        img = convert_to_tensor(img, track_meta=get_track_meta())