How to use the hvplot.util.is_dask function in hvplot

if kind is None:
                geom_types = set([gt[5:] if 'Multi' in gt else gt for gt in data.geom_type])
                if len(geom_types) > 1:
                    raise ValueError('The GeopandasInterface can only read dataframes which '
                                     'share a common geometry type')
                geom_type = list(geom_types)[0]
                if geom_type == 'Point':
                    kind = 'points'
                elif geom_type == 'Polygon':
                    kind = 'polygons'
                elif geom_type in ('LineString', 'LineRing'):
                    kind = 'paths'
        elif isinstance(data, pd.DataFrame):
            datatype = 'pandas'
            self.data = data
        elif is_dask(data):
            datatype = 'dask'
            self.data = data.persist() if persist else data
        elif is_streamz(data):
            datatype = 'streamz'
            self.data = data.example
            self.stream_type = data._stream_type
            streaming = True
            self.cb = data
            if data._stream_type == 'updating':
                self.stream = Pipe(data=self.data)
            else:
                self.stream = Buffer(data=self.data, length=backlog, index=False)
            data.stream.gather().sink(self.stream.send)
        elif is_xarray(data):
            import xarray as xr
            z = kwds.get('z')

'NdOverlay': dict(plot=self._overlay_opts)}
        hist_opts = {'bin_range': self.kwds.get('bin_range', None),
                     'normed': self.kwds.get('normed', False),
                     'cumulative': self.kwds.get('cumulative', False)}
        if 'bins' in self.kwds:
            bins = self.kwds['bins']
            if isinstance(bins, int):
                hist_opts['num_bins'] = bins
            else:
                hist_opts['bins'] = bins

        if not isinstance(y, (list, tuple)):
            if not 'bin_range' in self.kwds:
                ys = data[y]
                ymin, ymax = (ys.min(), ys.max())
                if is_dask(ys):
                    ymin, ymax = ymin.compute(), ymax.compute()
                hist_opts['bin_range'] = ymin, ymax

            ds = Dataset(data, self.by)
            if self.by:
                hist = hists = histogram(
                    ds.groupby(self.by), dimension=y, **hist_opts
                )
                hist = hists.last
                hists = hists.layout() if self.subplots else hists.overlay()
            else:
                hists = histogram(ds, dimension=y, **hist_opts)

            return hists.opts(opts).redim(**self._redim)

        ranges = []