code: def weight_init_normal(m):
      if isinstance(m, nn.Linear):
          torch.nn.init.kaiming_normal(
              m.weight, mode="fan_in", nonlinearity="relu"
          )
  
file_path: baal/experiments/mlp_regression_mcdropout.py
imports: from copy import deepcopy
  from pprint import pprint
  import pandas
  import numpy
  import torch.cuda
  from torch import nn, optim
  from torch.utils.data import Dataset
  from sklearn.preprocessing import StandardScaler
  from sklearn.model_selection import train_test_split
  from baal import ActiveLearningDataset, ModelWrapper
  from baal.active import ActiveLearningLoop
  from baal.active.heuristics import Variance
  from baal.bayesian.dropout import patch_module
label_desc: Use image node_id 1 for calling a global function with example usage: weight_init_normal(m) without return types