class_docstr: Wraps a pair of ``SummaryWriter`` instances but is a no-op if they're ``None``.
  Allows Tensorboard logging without always checking for Nones first.
code: def add_validation_scalar(self, name, value, global_step):
      if self._validation_log is not None:
          self._validation_log.add_scalar(
              name, self._item(value), global_step
          )
  
imports: from __future__ import with_statement
  from __future__ import division
  from __future__ import absolute_import
  import logging
  import os
  import shutil
  import time
  import re
  import datetime
  import traceback
  import torch
  import torch.optim.lr_scheduler
  from torch.nn.parallel import replicate, parallel_apply
  from torch.nn.parallel.scatter_gather import scatter_kwargs, gather
  from allennlp.common import Params
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.util import peak_memory_mb, gpu_memory_mb
  from allennlp.common.tqdm import Tqdm
  from allennlp.data.instance import Instance
  from allennlp.data.iterators.data_iterator import DataIterator
  from allennlp.models.model import Model
  from allennlp.nn import util
  from allennlp.training.learning_rate_schedulers import LearningRateScheduler
  from allennlp.training.optimizers import Optimizer
label_desc: Use image node_id 5 for calling the TensorboardWriter obj's underlying member method code with example usage: obj.add_validation_scalar(name, value, global_step) without return types