code: def test_first_class_background_init_conv():
      conv = nn.Conv2d(256, 19, kernel_size=3, padding=1)
      first_class_background_init(conv, background_prob=0.96)
  
      input = torch.randn(4, 256, 64, 64)
      output = conv(input).softmax(dim=1)
  
      actual_probas = output.mean(dim=(0, 2, 3))
      assert actual_probas[0] > 0.96
      assert (actual_probas[1:] < 0.04).all()
  
imports: import torch
  from torch import nn
  from pytorch_toolbelt.modules.initialization import first_class_background_init
label_desc: Use image node_id 1 for calling a global function with example usage: test_first_class_background_init_conv() without return types