code: def testEmptyModelName(self):
      # With empty model name the algorithm should skip the configuration without errors.
      self.assertConfigureSuccess(TensorflowPredict(), {})
      self.assertConfigureSuccess(
          TensorflowPredict(), {"graphFilename": ""}
      )
      self.assertConfigureSuccess(
          TensorflowPredict(), {"graphFilename": "", "inputs": [""]}
      )
      self.assertConfigureSuccess(
          TensorflowPredict(),
          {"graphFilename": "", "inputs": ["wrong_input"]},
      )
      self.assertConfigureSuccess(
          TensorflowPredict(), {"savedModel": ""}
      )
      self.assertConfigureSuccess(
          TensorflowPredict(), {"savedModel": "", "inputs": [""]}
      )
      self.assertConfigureSuccess(
          TensorflowPredict(),
          {"savedModel": "", "inputs": ["wrong_input"]},
      )
      self.assertConfigureSuccess(
          TensorflowPredict(), {"graphFilename": "", "savedModel": ""}
      )
      self.assertConfigureSuccess(
          TensorflowPredict(),
          {"graphFilename": "", "savedModel": "", "inputs": [""]},
      )
      self.assertConfigureSuccess(
          TensorflowPredict(),
          {
              "graphFilename": "",
              "savedModel": "",
              "inputs": ["wrong_input"],
          },
      )
  
file_path: essentia/test/src/unittests/machinelearning/test_tensorflowpredict.py
imports: from essentia_test import *
  import sys
  import os
label_desc: Use image node_id 5 for calling the TestTensorFlowPredict obj's underlying member method code with example usage: obj.testEmptyModelName() without return types