code: def _build_vocabulary(partition, params):
      model = sklearn.feature_extraction.text.CountVectorizer(**params)
      model.fit(partition)
      return set(model.vocabulary_)
  
imports: import itertools
  import dask
  import dask.array
  import dask.bag
  import dask.dataframe
  import distributed
  import numpy
  import scipy.sparse
  import sklearn.base
  import sklearn.feature_extraction.text
  from dask.delayed import Delayed
  from distributed import get_client, wait
  from sklearn.utils.validation import check_is_fitted
label_desc: Use image node_id 4 for calling a global function with example usage: _build_vocabulary(partition, params) and returns: set