code: def __init__(self, num_features) -> None:
      super().__init__()
      self.fc1 = nn.Linear(num_features, 5, bias=False)
      self.fc1.weight.data.fill_(0.02)
      self.relu1 = nn.ReLU()
      self.fc2 = nn.Linear(5, 1, bias=False)
      self.fc2.weight.data.fill_(0.02)
  
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 1 to create a new BasicLinearNet object from inherited base classes: nn with example: obj = BasicLinearNet(num_features)