def _check_type()

in ignite/metrics/accuracy.py [0:0]

• 30 lines of code
• 8 McCabe index (conditional complexity)

    def _check_type(self, output: Sequence[torch.Tensor]) -> None:
        y_pred, y = output

        if y.ndimension() + 1 == y_pred.ndimension():
            num_classes = y_pred.shape[1]
            if num_classes == 1:
                update_type = "binary"
                self._check_binary_multilabel_cases((y_pred, y))
            else:
                update_type = "multiclass"
        elif y.ndimension() == y_pred.ndimension():
            self._check_binary_multilabel_cases((y_pred, y))

            if self._is_multilabel:
                update_type = "multilabel"
                num_classes = y_pred.shape[1]
            else:
                update_type = "binary"
                num_classes = 1
        else:
            raise RuntimeError(
                f"Invalid shapes of y (shape={y.shape}) and y_pred (shape={y_pred.shape}), check documentation."
                " for expected shapes of y and y_pred."
            )
        if self._type is None:
            self._type = update_type
            self._num_classes = num_classes
        else:
            if self._type != update_type:
                raise RuntimeError(f"Input data type has changed from {self._type} to {update_type}.")
            if self._num_classes != num_classes:
                raise ValueError(f"Input data number of classes has changed from {self._num_classes} to {num_classes}")