private List<String> reduceDimensions() {
        OrderedTensorType inputType = inputs.get(0).type().get();
        int axis = inputType.rank() == 1 ? 0 : 1;  // assumption: first dimension is batch dimension
        if (attributeMap.get("axis").isPresent()) {
            axis = (int)attributeMap.get("axis").get().asDouble();
        }
        if (axis < 0) {
            axis = inputType.rank() + axis;
        }
        List<String> reduceDimensions = new ArrayList<>();
        for (int i = axis; i < inputType.rank(); ++i) {
            reduceDimensions.add(inputType.dimensions().get(i).name());  // Do softmax over all dimensions except batch dimension
        }
        return reduceDimensions;
    }
Convert imported 'softmax' operation to the Vespa softmax ranking function.

@author lesters
model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Softmax.java