code: def test_tiny_yolov3_training(transfer_learning):
      json_dir = os.path.join(detection_dataset, "json")
      json_file = os.path.join(
          json_dir, "number-plate_tiny-yolov3_detection_config.json"
      )
      models_dir = os.path.join(detection_dataset, "models")
  
      delete_cache([json_dir, models_dir])
  
      trainer = DetectionModelTrainer()
      trainer.setModelTypeAsTinyYOLOv3()
      trainer.setDataDirectory(data_directory=detection_dataset)
      trainer.setTrainConfig(
          object_names_array=["number-plate"],
          batch_size=2,
          num_experiments=2,
          train_from_pretrained_model=transfer_learning,
      )
      trainer.trainModel()
  
      assert os.path.isfile(json_file)
      assert (
          len(
              [
                  file
                  for file in os.listdir(models_dir)
                  if file.endswith(".pt")
              ]
          )
          > 0
      )
  
      delete_cache([json_dir, models_dir])
  
file_path: ImageAI/test/test_custom_detection_training.py
imports: import os, sys
  import shutil
  import pytest
  from os.path import dirname
  from imageai.Detection.Custom import DetectionModelTrainer
label_desc: Use image node_id 3 for calling a global function with example usage: test_tiny_yolov3_training(transfer_learning) without return types