code: def dict2htfa(htfa_dict):
      htfa = HTFA(
          K=htfa_dict["K"],
          n_subj=htfa_dict["n_subj"],
          max_voxel=htfa_dict["max_voxel"],
          max_tr=htfa_dict["max_tr"],
          verbose=False,
      )
      for k in htfa_dict.keys():
          setattr(htfa, k, htfa_dict[k])
      return htfa
  
imports: import numpy
  import pandas
  import nibabel
  import nilearn
  from nilearn.input_data import NiftiMasker
  import nilearn.plotting
  import matplotlib
  import matplotlib.pyplot
  import holoviews
  import timecorr
  import os
  from brainiak.factoranalysis.htfa import HTFA
  import warnings
  import seaborn
label_desc: Use image node_id 4 for calling a global function with example usage: dict2htfa(htfa_dict) and returns: htfa