code: def _get_embedding(umap_object):
      if hasattr(umap_object, "embedding_"):
          return umap_object.embedding_
      elif hasattr(umap_object, "embedding"):
          return umap_object.embedding
      else:
          raise ValueError(
              "Could not find embedding attribute of umap_object"
          )
  
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 5 for calling a global function with example usage: _get_embedding(umap_object) and returns: umap_object, umap_object