class_docstr: Suggests an architecture based on the Harmonica algorithm.
code: def _write_model(self, model_dir, coefficients, my_trial_id):
      filename = os.path.join(model_dir, "harmonica.csv")
      with tf.io.gfile.GFile(filename, mode="w+") as f:
          np.savetxt(f, coefficients, delimiter=",")
  
imports: import cmath
  import os
  from absl import logging
  from model_search import block_builder
  from model_search.architecture import architecture_utils
  from model_search.search import search_algorithm
  import numpy
  from sklearn import linear_model
  from sklearn import preprocessing
  import tensorflow.compat.v2
label_desc: Use image node_id 9 for calling the Harmonica obj's underlying member method code with example usage: obj._write_model(model_dir, coefficients, my_trial_id) without return types