class_docstr: Initializing data loader for NNCF to be used with unsupervised training algorithms.
docstr: Return structure for ground truth in loss criterion based on dataloader output.
  
  This implementation does not do anything and is a placeholder.
  
  Returns:
      None
docstr_tok: ["Return","structure","for","ground","truth","in","loss","criterion","based","on","dataloader","output",".","This","implementation","does","not","do","anything","and","is","a","placeholder",".","Returns",":","None"]
code: def get_target(self, _):
      """Return structure for ground truth in loss criterion based on dataloader output.
  
      This implementation does not do anything and is a placeholder.
  
      Returns:
          None
      """
      return None
  
imports: from __future__ import annotations
  import logging
  from copy import copy
  from typing import Any, Iterator
  from nncf import NNCFConfig
  from nncf.api.compression import CompressionAlgorithmController
  from nncf.torch import create_compressed_model, load_state, register_default_init_args
  from nncf.torch.initialization import PTInitializingDataLoader
  from nncf.torch.nncf_network import NNCFNetwork
  from torch import nn
  from torch.utils.data.dataloader import DataLoader
label_desc: Use image node_id 5 for calling the InitLoader obj's underlying member method code with example usage: obj.get_target(_) and returns: None