class_docstr: Builds a NASNet subnetwork for AdaNet.
docstr: See `adanet.subnetwork.Builder`.
docstr_tok: ["See","`","adanet.subnetwork.Builder","`","."]
code: def build_mixture_weights_train_op(
      self, loss, var_list, logits, labels, iteration_step, summary
  ):
      """See `adanet.subnetwork.Builder`."""
  
      if not self._learn_mixture_weights:
          return tf.no_op("mixture_weights_train_op")
  
      # The AdaNet Estimator is responsible for incrementing the global step.
      optimizer, learning_rate = self._optimizer_fn(
          learning_rate=self._initial_learning_rate
      )
      summary.scalar(
          "learning_rate/adanet/mixture_weights", learning_rate
      )
      return optimizer.minimize(loss=loss, var_list=var_list)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import adanet
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling the Builder obj's underlying member method code with example usage: obj.build_mixture_weights_train_op(loss, var_list, logits, labels, iteration_step, summary) and returns: optimizer, tf