Method __call__

monai/transforms/transform.py:442–466

``data`` often comes from an iteration over an iterable, such as :py:class:`torch.utils.data.Dataset`. To simplify the input validations, this method assumes: - ``data`` is a Python dictionary, - ``data[key]`` is a Numpy ndarray, PyTorch Tensor or string, w

(self, data)

    @abstractmethod
    def __call__(self, data):
        """
        ``data`` often comes from an iteration over an iterable,
        such as :py:class:`torch.utils.data.Dataset`.

        To simplify the input validations, this method assumes:

        - ``data`` is a Python dictionary,
        - ``data[key]`` is a Numpy ndarray, PyTorch Tensor or string, where ``key`` is an element
          of ``self.keys``, the data shape can be:

          #. string data without shape, `LoadImaged` transform expects file paths,
          #. most of the pre-/post-processing transforms expect: ``(num_channels, spatial_dim_1[, spatial_dim_2, ...])``,
             except for example: `AddChanneld` expects (spatial_dim_1[, spatial_dim_2, ...])

        - the channel dimension is often not omitted even if number of channels is one.

        Raises:
            NotImplementedError: When the subclass does not override this method.

        returns:
            An updated dictionary version of ``data`` by applying the transform.

        """
        raise NotImplementedError(f"Subclass {self.__class__.__name__} must implement this method.")

    def key_iterator(self, data: Mapping[Hashable, Any], *extra_iterables: Iterable | None) -> Generator:
        """