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_dense(self, grad, var):
      return self._apply_cond(self._apply_dense_in_action, 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 7 for calling the MultistepAdamOptimizer obj's underlying member method code with example usage: obj._apply_dense(grad, var) and returns: self