code: def __init__(self, sizes):
      super(MLP, self).__init__()
      layers = []
      for i in range(0, len(sizes) - 1):
          layers.append(nn.Linear(sizes[i], sizes[i + 1]))
          if i < (len(sizes) - 2):
              layers.append(nn.ReLU())
      self.net = nn.Sequential(*layers)
  
imports: import torch.nn
  from torch.nn.functional import relu, avg_pool2d
  from avalanche.models import MultiHeadClassifier, MultiTaskModule, DynamicModule
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: nn with example: obj = MLP(sizes)