class_docstr: Basic test to train module
docstr: Mocks luminoth.datasets.datasets.get_dataset
docstr_tok: ["Mocks","luminoth.datasets.datasets.get_dataset"]
code: def get_dataset(self, dataset_type):
      """
      Mocks luminoth.datasets.datasets.get_dataset
      """
  
      def dataset_class(arg2):
          def build():
              queue_dtypes = [tf.float32, tf.int32, tf.string]
              queue_names = ["image", "bboxes", "filename"]
  
              queue = tf.FIFOQueue(
                  capacity=3,
                  dtypes=queue_dtypes,
                  names=queue_names,
                  name="fifo_queue",
              )
              filename = tf.cast("filename_test", tf.string)
              filename = tf.train.limit_epochs([filename], num_epochs=2)
  
              data = {
                  "image": tf.random_uniform([600, 800, 3], maxval=255),
                  "bboxes": tf.constant([[0, 0, 30, 30, 0]]),
                  "filename": filename,
              }
              enqueue_ops = [queue.enqueue(data)] * 2
              tf.train.add_queue_runner(
                  tf.train.QueueRunner(queue, enqueue_ops)
              )
  
              return queue.dequeue()
  
          return build
  
      return dataset_class
  
imports: import sonnet
  import tempfile
  import tensorflow
  from easydict import EasyDict
  from luminoth.train import run
  from luminoth.models import get_model
  from luminoth.utils.config import get_model_config, load_config_files, get_base_config
label_desc: Use image node_id 2 for calling the TrainTest obj's underlying member method code with example usage: obj.get_dataset(dataset_type) and returns: dataset_class, build, queue