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 _apply_sparse(self, grad, var):
      # TODO(fstahlberg): Implement a sparse version
      tf.logging.warning(
          "MultistepAdamOptimizer does not support sparse updates"
      )
      dense_grad = tf.convert_to_tensor(grad)
      return self._apply_cond(
          super(MultistepAdamOptimizer, self)._apply_dense,
          dense_grad,
          var,
      )
  
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 9 for calling the MultistepAdamOptimizer obj's underlying member method code with example usage: obj._apply_sparse(grad, var) and returns: self