code: def __init__(self, num_classes=10, input_size=6, hidden_size=50):
      super().__init__()
      self.classifier = MultiHeadClassifier(
          self._hidden_size, num_classes
      )
  
imports: import unittest
  import random
  import torch
  import numpy
  from torch import nn
  from torch.optim import SGD
  from torch.nn import CrossEntropyLoss
  from avalanche.models import MultiHeadClassifier, PNN
  from avalanche.models.dynamic_modules import MultiTaskModule
  from avalanche.training.plugins import EvaluationPlugin
  from avalanche.training.supervised.cumulative import Cumulative
  from avalanche.evaluation.metrics import StreamAccuracy, ExperienceAccuracy
  from avalanche.training.supervised.strategy_wrappers import PNNStrategy
  from tests.unit_tests_utils import get_fast_benchmark, get_device, set_deterministic_run
label_desc: Use image node_id 1 to create a new MHTestMLP object from inherited base classes: TestMLP, MultiTaskModule with example: obj = MHTestMLP(num_classes, input_size, hidden_size)