code: def __init__(self, acti, acti_kw):
      super().__init__()
      self.conv1 = torch.nn.Conv2d(1, 20, 5, 1)
      self.conv2 = torch.nn.Conv2d(20, 50, 5, 1)
      self.fc1 = torch.nn.Linear(4 * 4 * 50, 500)
      self.fc2 = torch.nn.Linear(500, 10)
      self.relu1 = torch.nn.ReLU6()
      self.relu2 = torch.nn.ReLU6()
      self.acti = acti
      self.acti_kw = acti_kw
      self.max_pool1 = torch.nn.MaxPool2d(2, 2)
      self.max_pool2 = torch.nn.MaxPool2d(2, 2)
  
file_path: nni/test/algo/compression/pruning/test_speedup_softmax.py
imports: import unittest
  import torch
  import torch.nn.functional
  from nni.compression.utils.counter import count_flops_params
  from nni.compression.speedup import ModelSpeedup
  from nni.compression.pruning import L1NormPruner
label_desc: Use image node_id 1 to create a new NaiveModel object from inherited base classes: torch.nn with example: obj = NaiveModel(acti, acti_kw)