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(
          self._apply_dense_in_action, dense_grad, var
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow.compat.v1
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.training import training_ops
label_desc: Use image node_id 12 for calling the MultistepAdamOptimizer obj's underlying member method code with example usage: obj._apply_sparse(grad, var) and returns: self