class_docstr: The subnet with the architecture of PFLD. 
code: def init_params(self):
      for m in self.modules():
          if isinstance(m, nn.Conv2d):
              init.kaiming_normal_(m.weight, mode="fan_out")
              if m.bias is not None:
                  init.constant_(m.bias, 0)
          elif isinstance(m, nn.BatchNorm2d):
              init.constant_(m.weight, 1)
              init.constant_(m.bias, 0)
          elif isinstance(m, nn.Linear):
              init.normal_(m.weight, std=0.001)
              if m.bias is not None:
                  init.constant_(m.bias, 0)
  
file_path: nni/examples/nas/legacy/oneshot/pfld/lib/subnet.py
imports: from __future__ import absolute_import, division, print_function
  import torch
  import torch.nn
  from lib.ops import MBBlock, SeparableConv, SingleOperation, StemBlock, conv_bn
  from torch.nn import init
label_desc: Use image node_id 2 for calling the PFLDInference obj's underlying member method code with example usage: obj.init_params() without return types