class_docstr: A subnetwork builder always produces a NaN loss.
class_docstr_tok: ["A","subnetwork","builder","always","produces","a","NaN","loss","."]
code: def build_subnetwork_train_op(
      self,
      subnetwork,
      loss,
      var_list,
      labels,
      iteration_step,
      summary,
      previous_ensemble,
  ):
      return tf.no_op()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  import json
  import os
  from absl.testing import parameterized
  from adanet import tf_compat
  from adanet.core import testing_utils
  from adanet.core.tpu_estimator import TPUEstimator
  from adanet.subnetwork import Builder
  from adanet.subnetwork import Report
  from adanet.subnetwork import SimpleGenerator
  from adanet.subnetwork import Subnetwork
  import numpy
  import tensorflow.compat.v2
  from tensorflow_estimator.python.estimator.head import regression_head
label_desc: Use image node_id 3 for calling the _NanLossBuilder 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: tf