class_docstr: PL Lightning Module for the FastFlow algorithm.
  
  Args:
      hparams (DictConfig | ListConfig): Model params
class_docstr_tok: ["PL","Lightning","Module","for","the","FastFlow","algorithm",".","Args",":","hparams","(","DictConfig","|","ListConfig",")",":","Model","params"]
docstr: Configures optimizers for each decoder.
  
  Note:
      This method is used for the existing CLI.
      When PL CLI is introduced, configure optimizers method will be
          deprecated, and optimizers will be configured from either
          config.yaml file or from CLI.
  
  Returns:
      Optimizer: Adam optimizer for each decoder
docstr_tok: ["Configures","optimizers","for","each","decoder",".","Note",":","This","method","is","used","for","the","existing","CLI",".","When","PL","CLI","is","introduced",",","configure","optimizers","method","will","be","deprecated",",","and","optimizers","will","be","configured","from","either","config.yaml","file","or","from","CLI",".","Returns",":","Optimizer",":","Adam","optimizer","for","each","decoder"]
code: def configure_optimizers(self) -> torch.optim.Optimizer:
      """Configures optimizers for each decoder.
  
      Note:
          This method is used for the existing CLI.
          When PL CLI is introduced, configure optimizers method will be
              deprecated, and optimizers will be configured from either
              config.yaml file or from CLI.
  
      Returns:
          Optimizer: Adam optimizer for each decoder
      """
      return optim.Adam(
          params=self.model.parameters(),
          lr=self.hparams.model.lr,
          weight_decay=self.hparams.model.weight_decay,
      )
  
file_path: anomalib/src/anomalib/models/fastflow/lightning_model.py
imports: from __future__ import annotations
  import torch
  from omegaconf import DictConfig, ListConfig
  from pytorch_lightning.callbacks import EarlyStopping
  from pytorch_lightning.utilities.types import STEP_OUTPUT
  from torch import Tensor, optim
  from anomalib.models.components import AnomalyModule
  from anomalib.models.fastflow.loss import FastflowLoss
  from anomalib.models.fastflow.torch_model import FastflowModel
label_desc: Use image node_id 3 for calling the FastflowLightning obj's underlying member method code with example usage: obj.configure_optimizers() and returns: optim