class_docstr: Callback for NNCF compression.
  
  Assumes that the pl module contains a 'model' attribute, which is
  the PyTorch module that must be compressed.
  
  Args:
      config (dict): NNCF Configuration
      export_dir (Str): Path where the export `onnx` and the OpenVINO `xml` and `bin` IR are saved.
                        If None model will not be exported.
class_docstr_tok: ["Callback","for","NNCF","compression",".","Assumes","that","the","pl","module","contains","a","'model","'","attribute",",","which","is","the","PyTorch","module","that","must","be","compressed",".","Args",":","config","(","dict",")",":","NNCF","Configuration","export_dir","(","Str",")",":","Path","where","the","export","`","onnx","`","and","the","OpenVINO","`","xml","`","and","`","bin","`","IR","are","saved",".","If","None","model","will","not","be","exported","."]
docstr: Call when the train batch begins.
  
  Prepare compression method to continue training the model in the next step.
docstr_tok: ["Call","when","the","train","batch","begins",".","Prepare","compression","method","to","continue","training","the","model","in","the","next","step","."]
code: def on_train_batch_start(
      self,
      trainer: pl.Trainer,
      pl_module: pl.LightningModule,
      batch: Any,
      batch_idx: int,
      unused: int = 0,
  ) -> None:
      """Call when the train batch begins.
  
      Prepare compression method to continue training the model in the next step.
      """
      del (
          trainer,
          pl_module,
          batch,
          batch_idx,
          unused,
      )  # These variables are not used.
  
      if self.nncf_ctrl:
          self.nncf_ctrl.scheduler.step()
  
file_path: anomalib/src/anomalib/utils/callbacks/nncf/callback.py
imports: from __future__ import annotations
  import os
  from pathlib import Path
  from typing import Any
  import pytorch_lightning
  from nncf import NNCFConfig
  from nncf.api.compression import CompressionAlgorithmController
  from nncf.torch import register_default_init_args
  from pytorch_lightning import Callback
  from anomalib.utils.callbacks.nncf.utils import InitLoader, wrap_nncf_model
label_desc: Use image node_id 3 for calling the NNCFCallback obj's underlying member method code with example usage: obj.on_train_batch_start(trainer, pl_module, batch, batch_idx, unused) without return types