code: def test_zero_activations(self) -> None:
      with tempfile.TemporaryDirectory() as tmpdir:
          num_features = 4
          low, high = 0, 16
          batch_size = high // 2
          mymodel = BasicLinearNet(num_features)
          mydata = RangeDataset(low, high, num_features)
          layers = []
          for name, _module in mymodel.named_modules():
              layers.append(name)
          layers: List[str] = list(filter(None, layers))
          testlayers = layers[1:]
  
          sim1 = SimilarityInfluence(
              mymodel,
              testlayers,
              mydata,
              tmpdir,
              "linear",
              batch_size=batch_size,
          )
          inputs = torch.stack((mydata[1], mydata[8], mydata[14]))
          influences = sim1.influence(inputs, top_k=3)
          self.assertEqual(
              len(influences), len(layers[1:]) + 1
          )  # zero_acts included
          self.assertTrue("zero_acts-fc2" in influences)
  
imports: import tempfile
  from typing import List
  import torch
  import torch.nn
  from captum.influence._core.similarity_influence import cosine_similarity, euclidean_distance, SimilarityInfluence
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from torch.utils.data import Dataset
label_desc: Use image node_id 5 for calling the Test obj's underlying member method code with example usage: obj.test_zero_activations() without return types