code: def _get_metric_kwds(umap_object):
      if hasattr(umap_object, "_metric_kwds"):
          return umap_object._metric_kwds
      else:
          # Assume no keywords exist
          return {}
  
imports: import numpy
  import numba
  from warnings import warn
  import sklearn.decomposition
  import sklearn.cluster
  import sklearn.neighbors
  from matplotlib.patches import Patch
  from umap.utils import submatrix, average_nn_distance
  from bokeh.plotting import show
  from bokeh.plotting import output_file, output_notebook
  from bokeh.layouts import column
  from bokeh.models import CustomJS, TextInput
  from matplotlib.pyplot import show
  from warnings import warn
label_desc: Use image node_id 7 for calling a global function with example usage: _get_metric_kwds(umap_object) and returns: umap_object, dict