code: def eval_step(self, batch, batch_idx, prefix: str):
      images: Tensor
      output: HyperpriorOutput
  
      images = batch
  
      output = self.model(images)
  
      distortion_loss = self.distortion_loss(output.image, images)
      rate_output = self.rate_loss(
          original=images,
          latent_likelihoods=output.latent_likelihoods,
          quantized_latent_likelihoods=output.quantized_latent_likelihoods,
          hyper_latent_likelihoods=output.hyper_latent_likelihoods,
          quantized_hyper_latent_likelihoods=output.quantized_hyper_latent_likelihoods,
      )
      eval_loss = (
          self.distortion_lam * distortion_loss + rate_output.rate_loss
      )
  
      self.log_quality_metrics(output, images, prefix=prefix)
      self.log_dict(
          {
              f"{prefix}/total_loss": eval_loss,
              f"{prefix}/distortion_loss": distortion_loss,
              f"{prefix}/rate_loss": rate_output.rate_loss,
              f"{prefix}/total_bpp": rate_output.total_bpp,
              f"{prefix}/quantized_total_bpp": rate_output.quantized_total_bpp,
              f"{prefix}/hyper_bpp": rate_output.hyper_bpp,
              f"{prefix}/quantized_hyper_bpp": rate_output.quantized_hyper_bpp,
              f"{prefix}/latent_bpp": rate_output.latent_bpp,
              f"{prefix}/quantized_latent_bpp": rate_output.quantized_latent_bpp,
              f"{prefix}/target": rate_output.target,
              f"{prefix}/lam2": rate_output.lam2,
          },
          sync_dist=True,
      )
  
imports: import math
  from typing import List, NamedTuple, Optional
  import hydra
  import torch
  from image_module import ImageModule
  from omegaconf import DictConfig
  from torch import Tensor
  from torch.utils.data import Dataset
  from neuralcompression import HyperpriorOutput
  from neuralcompression.loss_fn import DistortionLoss, MSELoss, TargetRateConfig
  from neuralcompression.metrics import pickle_size_of
  from neuralcompression.models import HyperpriorAutoencoderBase
label_desc: Use image node_id 9 for calling the TargetRateCompressionModule obj's underlying member method code with example usage: obj.eval_step(batch, batch_idx, prefix) without return types