docstr: PTL hook: https://pytorch-lightning.readthedocs.io/en/latest/common/lightning_module.html#transfer-batch-to-device
  When using pipeline parallelism, we need the global batch to remain on the CPU,
  since the memory overhead will be too high when using a large number of microbatches.
  Microbatches are transferred from CPU to GPU inside the pipeline.
code: def transfer_batch_to_device(
      self, batch: Any, device: torch.device, dataloader_idx: int
  ) -> Any:
      """PTL hook: https://pytorch-lightning.readthedocs.io/en/latest/common/lightning_module.html#transfer-batch-to-device
      When using pipeline parallelism, we need the global batch to remain on the CPU,
      since the memory overhead will be too high when using a large number of microbatches.
      Microbatches are transferred from CPU to GPU inside the pipeline.
      """
      return batch
  
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 19 for calling the MegatronControlNet obj's underlying member method code with example usage: obj.transfer_batch_to_device(batch, device, dataloader_idx) and returns: batch