code: def weights_init(self, m):
      if isinstance(m, nn.Linear):
          torch.nn.init.xavier_uniform_(m.weight.data)
          if m.bias is not None:
              m.bias.data.fill_(0.0)
  
imports: import copy
  import torch
  import numpy
  import torch.nn
  from tqdm import trange
  from sklearn.model_selection import StratifiedKFold
  from torch_geometric.loader import DataLoader
  from sklearn.svm import SVC
  from sklearn import preprocessing
  from sklearn.metrics import accuracy_score
  from sklearn.model_selection import GridSearchCV
label_desc: Use image node_id 2 for calling the LogReg obj's underlying member method code with example usage: obj.weights_init(m) without return types