code: def test_batch_segmentation_spleen(self):
      if not torch.cuda.is_available():
          return
  
      model = "segmentation_spleen"
      params = {
          "device": "cuda",
          "multi_gpu": True,
          "gpus": "all",
          "logging": "WARNING",
          "save_label": True,
          "label_tag": "original",
          "max_workers": 0,
          "max_batch_size": 3,
      }
  
      response = requests.post(
          f"{SERVER_URI}/batch/infer/{model}?images=all&run_sync=true",
          json=params,
      )
      assert response.status_code == 200
  
imports: import unittest
  import requests
  import torch
  from tests.integration import SERVER_URI
label_desc: Use image node_id 1 for calling the EndPointBatchInfer obj's underlying member method code with example usage: obj.test_batch_segmentation_spleen() without return types