def decide_slices(self, data_shapes):
        """Decide the slices for each context according to the workload.

        Parameters
        ----------
        data_shapes : list
            list of (name, shape) specifying the shapes for the input data or label.
        """
        assert len(data_shapes) > 0
        major_axis = [DataDesc.get_batch_axis(x.layout) for x in data_shapes]

        for (name, shape), axis in zip(data_shapes, major_axis):
            if axis == -1:
                continue

            batch_size = shape[axis]
            if self.batch_size is not None:
                assert batch_size == self.batch_size, ("all data must have the same batch size: "
                                                       + ("batch_size = %d, but " % self.batch_size)
                                                       + ("%s has shape %s" % (name, shape)))
            else:
                self.batch_size = batch_size
                self.slices = _split_input_slice(self.batch_size, self.workload)

        return major_axis
Decide the slices for each context according to the workload.

        Parameters
        ----------
        data_shapes : list
            list of (name, shape) specifying the shapes for the input data or label.
        
rfcn/core/DataParallelExecutorGroup.py