code: def optimizer_scheduler(self):
      opt = torch.optim.SGD(
          self.parameters(),
          lr=self.learning_rate,
          momentum=0.9,
      )
      sch = torch.optim.lr_scheduler.ReduceLROnPlateau(
          opt,
          factor=0.5,
          patience=2,
          verbose=True,
          mode="max",
          threshold=1e-4,
      )
      return opt, sch
  
imports: import argparse
  import os
  import albumentations
  import numpy
  import pandas
  import timm
  import torch
  import torch.nn
  from cv2 import dft
  from sklearn import metrics, model_selection
  from tqdm.auto import tqdm
  from tez import Tez, TezConfig
  from tez.callbacks import EarlyStopping
  from tez.datasets import ImageDataset
  from tez.utils import seed_everything
label_desc: Use image node_id 3 for calling the SorghumModel obj's underlying member method code with example usage: obj.optimizer_scheduler() and returns: opt,  sch