class_docstr: Initializing data loader for NNCF to be used with unsupervised training algorithms.
docstr: Get input to model.
  
  Returns:
      (dataloader_output,), {}: tuple[tuple, dict]: The current model call to be made during
      the initialization process
docstr_tok: ["Get","input","to","model",".","Returns",":","(","dataloader_output",",",")",",","{","}",":","tuple","[","tuple",",","dict","]",":","The","current","model","call","to","be","made","during","the","initialization","process"]
code: def get_inputs(self, dataloader_output) -> tuple[tuple, dict]:
      """Get input to model.
  
      Returns:
          (dataloader_output,), {}: tuple[tuple, dict]: The current model call to be made during
          the initialization process
      """
      return (dataloader_output,), {}
  
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 4 for calling the InitLoader obj's underlying member method code with example usage: obj.get_inputs(dataloader_output) and returns: dataloader_output,  dict