class_docstr: Post-Processing Configuration Callback.
  
  Args:
      normalization_method(NormalizationMethod): Normalization method. <none, min_max, cdf>
      threshold_method (ThresholdMethod): Flag indicating whether threshold should be manual or adaptive.
      manual_image_threshold (float | None): Default manual image threshold value.
      manual_pixel_threshold (float | None): Default manual pixel threshold value.
docstr: Setup post-processing configuration within Anomalib Model.
  
  Args:
      trainer (Trainer): PyTorch Lightning Trainer
      pl_module (LightningModule): Anomalib Model that inherits pl LightningModule.
      stage (str | None, optional): fit, validate, test or predict. Defaults to None.
code: def setup(
      self,
      trainer: Trainer,
      pl_module: LightningModule,
      stage: str | None = None,
  ) -> None:
      """Setup post-processing configuration within Anomalib Model.
  
      Args:
          trainer (Trainer): PyTorch Lightning Trainer
          pl_module (LightningModule): Anomalib Model that inherits pl LightningModule.
          stage (str | None, optional): fit, validate, test or predict. Defaults to None.
      """
      del trainer, stage  # These variables are not used.
  
      if isinstance(pl_module, AnomalyModule):
          pl_module.threshold_method = self.threshold_method
          if pl_module.threshold_method == ThresholdMethod.MANUAL:
              pl_module.image_threshold.value = torch.tensor(
                  self.manual_image_threshold
              ).cpu()
              pl_module.pixel_threshold.value = torch.tensor(
                  self.manual_pixel_threshold
              ).cpu()
  
file_path: anomalib/src/anomalib/utils/callbacks/post_processing_configuration.py
imports: from __future__ import annotations
  import logging
  import torch
  from pytorch_lightning import Callback, LightningModule, Trainer
  from anomalib.models.components.base.anomaly_module import AnomalyModule
  from anomalib.post_processing import NormalizationMethod, ThresholdMethod
label_desc: Use image node_id 2 for calling the PostProcessingConfigurationCallback obj's underlying member method code with example usage: obj.setup(trainer, pl_module, stage) without return types