code: def get_forward_output_and_loss_func(self):
      def process_batch(batch):
          # noise_map, condition
          prompts, images = batch
          # DB has more dedicated structure for encoding, so we enable autocasting here as well
          with torch.cuda.amp.autocast(
              self.autocast_dtype in (torch.half, torch.bfloat16),
              dtype=self.autocast_dtype,
          ):
              images = images.cuda(non_blocking=True)
  
              cond = self.model.text_encoder([t[0] for t in prompts])
              if self.cfg.with_prior_preservation:
                  cond_prior = self.model.text_encoder(
                      [t[1] for t in prompts]
                  )
                  cond = torch.cat([cond, cond_prior], dim=0)
  
          return images, cond
  
      def fwd_output_and_loss_func(dataloader_iter, model):
          batch = next(dataloader_iter)
          batch = process_batch(batch)
          batch = [x.cuda(non_blocking=True) for x in batch]
          loss = model(batch)
  
          def dummy(output_tensor):
              return loss, {"loss": loss}
  
          return loss, dummy
  
      return fwd_output_and_loss_func
  
imports: from functools import partial
  from typing import Any, Optional
  import torch
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from torch._inductor import config
  from nemo.collections.multimodal.data.dreambooth.dreambooth_dataset import DreamBoothDataset
  from nemo.collections.multimodal.modules.stable_diffusion.distributions.distributions import DiagonalGaussianDistribution
  from nemo.collections.multimodal.parts.utils import randn_like
  from nemo.collections.nlp.data.language_modeling.megatron.data_samplers import MegatronPretrainingRandomSampler
  from nemo.collections.nlp.models.language_modeling.megatron_base_model import MegatronBaseModel
  from nemo.collections.nlp.modules.common.megatron.module import Float16Module
  from nemo.collections.nlp.parts.utils_funcs import get_last_rank
  from nemo.core.classes.common import Serialization
  from nemo.utils import logging
label_desc: Use image node_id 11 for calling the MegatronDreamBooth obj's underlying member method code with example usage: obj.get_forward_output_and_loss_func() and returns: fwd_output_and_loss_func, images,  cond, loss,  dummy, loss,  dict