code: def __init__(
      self, model_name, num_classes, learning_rate, n_train_steps
  ):
      super().__init__()
  
      self.learning_rate = learning_rate
      self.n_train_steps = n_train_steps
      self.model = timm.create_model(
          model_name,
          pretrained=True,
          in_chans=3,
          num_classes=num_classes,
      )
  
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 1 to create a new SorghumModel object from inherited base classes: nn with example: obj = SorghumModel(model_name, num_classes, learning_rate, n_train_steps)