class_docstr: A simple subnetwork builder that takes feature_columns.
code: def build_subnetwork_train_op(
      self,
      subnetwork,
      loss,
      var_list,
      labels,
      iteration_step,
      summary,
      previous_ensemble,
  ):
      optimizer = tf_compat.v1.train.GradientDescentOptimizer(
          learning_rate=0.001
      )
      return optimizer.minimize(loss, var_list=var_list)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import logging
  from adanet import tf_compat
  from adanet.core import testing_utils
  from adanet.core.estimator import Estimator
  from adanet.core.report_materializer import ReportMaterializer
  from adanet.subnetwork import Builder
  from adanet.subnetwork import SimpleGenerator
  from adanet.subnetwork import Subnetwork
  import tensorflow.compat.v2
  from tensorflow_estimator.python.estimator.head import regression_head
label_desc: Use image node_id 4 for calling the _SimpleBuilder obj's underlying member method code with example usage: obj.build_subnetwork_train_op(subnetwork, loss, var_list, labels, iteration_step, summary, previous_ensemble) and returns: optimizer