code: def test_umap_update_bad_params(nn_data):
      dmat = pairwise_distances(nn_data[:100])
      u = UMAP(metric="precomputed", n_epochs=11)
      u.fit(dmat)
      with pytest.raises(ValueError):
          u.update(dmat)
  
      u = UMAP(n_epochs=11)
      u.fit(nn_data[:100], y=np.repeat(np.arange(5), 20))
      with pytest.raises(ValueError):
          u.update(nn_data[100:200])
  
imports: import warnings
  import numpy
  from sklearn.metrics import pairwise_distances
  import pytest
  import numba
  from umap import UMAP
  import umap.validation
label_desc: Use image node_id 33 for calling a global function with example usage: test_umap_update_bad_params(nn_data) without return types