class_docstr: Adam with SGD updates every n steps with accumulated gradients.
class_docstr_tok: ["Adam","with","SGD","updates","every","n","steps","with","accumulated","gradients","."]
code: def _prepare(self):
      super(MultistepAdamOptimizer, self)._prepare()
      self._n_t = tf.convert_to_tensor(self._n, name="n")
  
file_path: tensor2tensor/tensor2tensor/utils/multistep_optimizer.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling the MultistepAdamOptimizer obj's underlying member method code with example usage: obj._prepare() without return types