rmsprop_applier.py 文件源码

def apply_gradients(self, var_list, accum_grad_list, name=None):

    update_ops = []

    with tf.device(self._device):
      with tf.control_dependencies(None):
        self._create_slots(var_list)

      with tf.name_scope(name, self._name, []) as name:
        self._prepare()
        for var, accum_grad in zip(var_list, accum_grad_list):
          with tf.name_scope("update_" + var.op.name), tf.device(var.device):
            clipped_accum_grad = tf.clip_by_norm(accum_grad, self._clip_norm)
            update_ops.append(self._apply_dense(clipped_accum_grad, var))
        return update_ops;
        #return tf.group(*update_ops, name=name)