code: def forward(self, x, eps=1e-6):
      norm = x.norm(dim=1, keepdim=True).clamp(min=eps)
      return x / norm
  
imports: import copy
  import random
  from functools import wraps, partial
  import torch
  from torch import nn
  import torch.nn.functional
  from torchvision import transforms
label_desc: Use image node_id 1 for calling the L2Norm obj's underlying member method code with example usage: obj.forward(x, eps) and returns: unknown