code: def init_weights(self):
      if self.init:
          nn.init.normal_(self.conv1.weight, std=1e-3)
          nn.init.normal_(self.conv2.weight, std=1e-3)
  
          self.conv1.weight[:, 0, :] += (
              1.0 / self.kernel_size
          )  # new initialization scheme
          self.conv2.weight += (
              1.0 / self.kernel_size
          )  # new initialization scheme
  
          nn.init.normal_(self.conv1.bias, std=1e-6)
          nn.init.normal_(self.conv2.bias, std=1e-6)
      else:
          nn.init.xavier_uniform_(self.conv1.weight)
          nn.init.xavier_uniform_(self.conv2.weight)
  
      if self.downsample is not None:
          self.downsample.weight.data.normal_(0, 0.1)
  
imports: import pickle
  import numpy
  import torch
  import torch.nn
  import torch.optim
  from torch.autograd import Variable
  from torch.nn.utils import weight_norm
  from bigdl.chronos.model.tcmf.data_loader import TCMFDataLoader
  from bigdl.chronos.model.tcmf.time import TimeCovariates
  import logging
label_desc: Use image node_id 2 for calling the TemporalBlock obj's underlying member method code with example usage: obj.init_weights() without return types