code: def __init__(self, learning_rate):
      super().__init__()
      self.learning_rate = learning_rate
      self.base_model = create_model(
          num_classes=1,
          image_size=1024,
          architecture="tf_efficientdet_d1",
      )
  
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 1 to create a new WheatModel object from inherited base classes: nn with example: obj = WheatModel(learning_rate)