code: def test_process_data(self, data_to_process):
      data_processor = DataProcessor()
      train_data = data_processor.process_data(
          data_to_process, batch_size=50
      )
  
      if torch.is_tensor(data_to_process):
          assert torch.equal(train_data, data_to_process)
  
      else:
          assert torch.equal(
              train_data,
              torch.tensor(data_to_process).type(torch.float),
          ), train_data.shape
  
      train_dataset = data_processor.to_dataset(train_data)
      assert torch.equal(train_dataset.data, train_data)
  
file_path: benchmark_VAE/tests/test_preprocessing.py
imports: import os
  import numpy
  import pytest
  import torch
  from pythae.data.datasets import BaseDataset
  from pythae.data.preprocessors import DataProcessor
label_desc: Use image node_id 2 for calling the Test_Data_Convert obj's underlying member method code with example usage: obj.test_process_data(data_to_process) without return types