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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _from_p(self, mode):
 """Convert the image from P or PA to RGB or RGBA."""

        self._check_modes(("P", "PA"))

        if not self.palette:
            raise RuntimeError("Can't convert palettized image, missing palette.")
        pal = np.array(self.palette)
        pal = da.from_array(pal, chunks=pal.shape)

        if pal.shape[1] == 4:
            # colormap's alpha overrides data alpha
            mode = "RGBA"
            alpha = None
        elif self.mode.endswith("A"):
            # add a new/fake 'bands' dimension to the end
            alpha = self.data.sel(bands="A").data[..., None]
            mode = mode + "A" if not mode.endswith("A") else mode
        else:
            alpha = None

        flat_indexes = self.data.sel(bands='P').data.ravel().astype('int64')
        dim_sizes = ((key, val) for key, val in self.data.sizes.items() if key != 'bands')
        dims, new_shape = zip(*dim_sizes)
        dims = dims + ('bands',)
        new_shape = new_shape + (pal.shape[1],)
        new_data = pal[flat_indexes].reshape(new_shape)
        coords = dict(self.data.coords)
        coords["bands"] = list(mode)

        if alpha is not None:
            new_arr = da.concatenate((new_data, alpha), axis=-1)
            data = xr.DataArray(new_arr, coords=coords, attrs=self.data.attrs, dims=dims)
        else:
            data = xr.DataArray(new_data, coords=coords, attrs=self.data.attrs, dims=dims)

        return data