class_docstr: Module to L2-normalize the input. Typically used in last layer to
  normalize the embedding.
class_docstr_tok: ["Module","to","L2-normalize","the","input",".","Typically","used","in","last","layer","to","normalize","the","embedding","."]
code: def __init__(self):
      super().__init__()
  
imports: from typing import Dict
  import torch
  from torch import Tensor
  from torch.nn.functional import normalize
  from torch.nn.modules import Module
  from avalanche.training.utils import get_last_fc_layer, swap_last_fc_layer
  from avalanche.training.plugins.strategy_plugin import SupervisedPlugin
  from avalanche.training.storage_policy import ClassBalancedBuffer
  from avalanche.benchmarks.utils.data_loader import ReplayDataLoader
label_desc: Use image node_id 1 to create a new L2Normalization object from inherited base classes: Module with example: obj = L2Normalization()