code: def optimizer_scheduler(self):
      opt = torch.optim.SGD(
          self.parameters(),
          lr=self.learning_rate,
          momentum=0.9,
          weight_decay=0.0005,
      )
      # define scheduler here if needed
      return opt, None
  
imports: import argparse
  import ast
  import os
  import albumentations
  import numpy
  import pandas
  import timm
  import torch
  import torch.nn
  import torchvision
  from effdet import DetBenchTrain, EfficientDet, get_efficientdet_config
  from effdet.config.model_config import efficientdet_model_param_dict
  from effdet.efficientdet import HeadNet
  from PIL import Image, ImageFile
  from sklearn.model_selection import train_test_split
  from torchvision.models.detection.faster_rcnn import FastRCNNPredictor
  from tez import Tez, TezConfig
label_desc: Use image node_id 2 for calling the WheatModel obj's underlying member method code with example usage: obj.optimizer_scheduler() and returns: opt,  None