class_docstr: A simple DNN subnetwork builder.
class_docstr_tok: ["A","simple","DNN","subnetwork","builder","."]
code: def build_subnetwork_report(self):
      return Report(
          hparams={"layer_size": self._layer_size},
          attributes={"complexity": tf.constant(3, dtype=tf.int32)},
          metrics={
              "moo": (
                  tf.constant(3, dtype=tf.int32),
                  tf.constant(3, dtype=tf.int32),
              )
          },
      )
  
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 5 for calling the _DNNBuilder obj's underlying member method code with example usage: obj.build_subnetwork_report() and returns: Report