class_docstr: Hierarchical Attention Network (RNN baseline model)
code: def __init__(self, hparams) -> None:
      super().__init__()
      self.hparams.update(hparams)
  
      # 2. HAN ENCODER
      self.init_encoder()
      # 3. LOSS
      self.init_loss()
  
      # 5. METRICS
      self.init_metrics()
  
      self.train_step_targets = []
      self.train_step_predictions = []
      self.last_update = 0
      self.last_global_step = 0
  
imports: from turtle import hideturtle
  import pytorch_lightning
  import torch
  import torch.nn.functional
  import torch.nn
  from pytorch_lightning import seed_everything
  from pathlib import Path
  from src.transformer.transformer_utils import *
  from src.transformer.metrics import CorrectedBAcc, CorrectedF1, CorrectedMCC, AUL
  import torchmetrics
label_desc: Use image node_id 1 to create a new FFN object from inherited base classes: pl with example: obj = FFN(hparams)