code: def forward(self, x, task_labels):
      x = self.layers(x)
      x = self.classifier(x, task_labels)
      return x
  
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 2 for calling the MHTestMLP obj's underlying member method code with example usage: obj.forward(x, task_labels) and returns: x