code: def _job_chunks(lambda_seq, n_jobs):
      n_chunks = n_jobs
      if n_jobs < 0:
          # so, have n chunks if we are using all n cores/cpus
          n_chunks = cpu_count() + 1 - n_jobs
  
      return _chunks(lambda_seq, n_chunks)
  
imports: import json
  import logging
  import numpy
  import pandas
  from collections import namedtuple
  from joblib import Parallel, delayed, cpu_count
  from scipy.stats import entropy
  from scipy.spatial.distance import pdist, squareform
  from sklearn.manifold import MDS, TSNE
  from pyLDAvis.utils import NumPyEncoder
label_desc: Use image node_id 13 for calling a global function with example usage: _job_chunks(lambda_seq, n_jobs) and returns: _chunks