code: def validation_step(self, batch, batch_idx):
      tensor_shape = None  # Placeholder
      fwd_bwd_function = get_forward_backward_func()
  
      losses_reduced_per_micro_batch = fwd_bwd_function(
          forward_step_func=self.get_forward_output_and_loss_func(),
          data_iterator=dataloader_iter,
          model=[self.model],
          num_microbatches=get_num_microbatches(),
          forward_only=True,
          tensor_shape=None,  # required by pipeline parallelism
          dtype=self.autocast_dtype,
          sequence_parallel=self.cfg.get("sequence_parallel", False),
          enable_autocast=True,
      )
      # only the last stages of the pipeline return losses
      val_loss_dict = {}
      if losses_reduced_per_micro_batch:
          # average loss across micro batches
          for key in losses_reduced_per_micro_batch[0]:
              loss_tensors_list = [
                  loss_reduced[key]
                  for loss_reduced in losses_reduced_per_micro_batch
              ]
              loss_tensor = torch.stack(loss_tensors_list)
              val_loss_dict[key] = loss_tensor.mean()
  
      self.log_dict(
          val_loss_dict,
          prog_bar=False,
          logger=True,
          on_step=False,
          on_epoch=True,
      )
  
imports: from typing import Any
  import einops
  import torch
  import torch.nn
  from einops import rearrange, repeat
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from pytorch_lightning.utilities.rank_zero import rank_zero_only
  from torch._inductor import config
  from nemo.collections.multimodal.data.controlnet.controlnet_dataset import build_train_valid_datasets
  from nemo.collections.multimodal.models.text_to_image.stable_diffusion.ldm.ddpm import LatentDiffusion
  from nemo.collections.multimodal.models.text_to_image.stable_diffusion.samplers.ddim import DDIMSampler
  from nemo.collections.multimodal.modules.stable_diffusion.attention import SpatialTransformer
  from nemo.collections.multimodal.modules.stable_diffusion.diffusionmodules.openaimodel import AttentionBlock, Downsample, ResBlock, TimestepEmbedSequential, UNetModel
  from nemo.collections.multimodal.modules.stable_diffusion.diffusionmodules.util import conv_nd, linear, timestep_embedding, zero_module
  from nemo.collections.multimodal.parts.stable_diffusion.utils import exists, log_txt_as_img
  from nemo.collections.nlp.models.language_modeling.megatron_base_model import MegatronBaseModel
  from nemo.collections.nlp.modules.common.megatron.module import Float16Module
  from nemo.utils import logging
label_desc: Use image node_id 13 for calling the MegatronControlNet obj's underlying member method code with example usage: obj.validation_step(batch, batch_idx) without return types