code: def push_validation_data(self, batch, validation_data):
      render = vutils.make_grid(
          validation_data["render"],
          nrow=2,
          normalize=True,
          scale_each=True,
      )
      tb_datapack = tensorboard_helper.TensorboardDatapack()
      tb_datapack.set_training(False)
      tb_datapack.set_iteration(self.iteration)
      for key in validation_data.keys():
          if "loss" in key:
              tb_datapack.add_scalar(
                  {f"val_loss/{key}": validation_data[key]}
              )
      tb_datapack.add_image({"render/val": render})
      self.tb_pusher.push_to_tensorboard(tb_datapack)
  
imports: import os
  import time
  from utils.render_utils import render_vanilla
  import tqdm
  import torch
  import torch.nn.functional
  import torchvision.utils
  import numpy
  from utils import utils, render_utils, ray_utils
  from trainers import base_trainer, tensorboard_helper
  from models.vanilla import weight_reset
label_desc: Use image node_id 6 for calling the NeRFTrainer obj's underlying member method code with example usage: obj.push_validation_data(batch, validation_data) without return types