code: def test_torch_image_classification_custom_net():
      from gluoncv.auto.tasks import ImageClassification
      from timm import create_model
      import torch.nn as nn
  
      net = create_model("resnet18")
      net.fc = nn.Linear(512, 4)
      task = ImageClassification(
          {
              "num_trials": 1,
              "epochs": 1,
              "custom_net": net,
              "batch_size": 8,
          }
      )
      classifier = task.fit(IMAGE_CLASS_DATASET)
      assert task.fit_summary().get("valid_acc", 0) > 0
      test_result = classifier.predict(IMAGE_CLASS_TEST)
  
imports: from gluoncv.auto.tasks import ImageClassification
  import autogluon.core
  from nose.tools import nottest
label_desc: Use image node_id 2 for calling a global function with example usage: test_torch_image_classification_custom_net() without return types