code: def plot_latent_inducing(self,
                          which_indices=None,
                          legend=False,
                          plot_limits=None,
                          marker=None,
                          projection='2d',
                          **kwargs):
      
      canvas, projection, kwargs, sig_dims = _new_canvas(self, projection, kwargs, which_indices)
  
      if legend: label = 'inducing'
      else: label = None
      if marker is not None:
          kwargs['marker'] = marker
      update_not_existing_kwargs(kwargs, pl().defaults.inducing_2d)  # @UndefinedVariable
      from .data_plots import _plot_inducing
      scatters = _plot_inducing(self, canvas, sig_dims[:2], projection, label, **kwargs)
      return pl().add_to_canvas(canvas, dict(scatter=scatters), legend=legend)
docs: Plot a scatter plot of the inducing inputs.
  
      :param [int] which_indices: which input dimensions to plot against each other
      :param bool legend: whether to plot the legend on the figure
      :param plot_limits: the plot limits for the plot
      :type plot_limits: (xmin, xmax, ymin, ymax) or ((xmin, xmax), (ymin, ymax))
      :param str marker: marker to use [default is custom arrow like]
      :param kwargs: the kwargs for the scatter plots
      :param str projection: for now 2d or 3d projection (other projections can be implemented, see developer documentation)