code: def init_train_updates(self):
      optimizer = tf.train.AdagradOptimizer(
          learning_rate=self.step,
      )
      self.functions.optimizer = optimizer
      return [optimizer.minimize(self.variables.loss)]
  
imports: import tensorflow
  from .base import GradientDescent
label_desc: Use image node_id 1 for calling the Adagrad obj's underlying member method code with example usage: obj.init_train_updates() and returns: list