code: def weight_init(m):
      if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d):
          nn.init.xavier_uniform_(
              m.weight, gain=nn.init.calculate_gain("relu")
          )
          nn.init.zeros_(m.bias)
  
file_path: baal/tests/ensemble_test.py
imports: import pytest
  import torch
  from torch import nn
  from torch import optim
  from torch.utils.data import Dataset
  from baal.ensemble import EnsembleModelWrapper, ensemble_prediction
label_desc: Use image node_id 1 for calling a global function with example usage: weight_init(m) without return types