code: def run_target_model(
      method,
      input_filename,
      output_dir,
      embedding_test_dir,
      debug=True,
      **kargs,
  ):
      sys.path.append(embedding_test_dir)
      from src.baseline import baseline
  
      with cd(embedding_test_dir):
          baseline(
              method,
              None,
              kargs["emd_size"],
              input_filename,
              output_dir,
              debug=debug,
              **kargs,
          )
  
imports: import random
  import os
  import sys
  import collections
  import itertools
  import pickle
  import scipy.sparse
  import networkx
  import numpy
  from sklearn.cluster import SpectralClustering
  from sklearn import gaussian_process
  from scipy.optimize import minimize
  from bayes_opt import BayesianOptimization
label_desc: Use image node_id 8 for calling a global function with example usage: run_target_model(method, input_filename, output_dir, embedding_test_dir, debug) without return types