code: def create_strategy_and_benchmark(self):
      model = SimpleMLP(input_size=6)
      old_layer = model.classifier
      model.classifier = nn.Identity()
      model = TrainEvalModel(
          model,
          train_classifier=old_layer,
          eval_classifier=FeCAMClassifier(),
      )
      optimizer = torch.optim.SGD(model.parameters(), lr=0.1)
      strategy = Naive(model, optimizer)
      benchmark = load_benchmark()
      return strategy, benchmark
  
imports: import unittest
  import torch
  import torch.nn
  from avalanche.models import FeCAMClassifier, NCMClassifier, SimpleMLP, TrainEvalModel
  from avalanche.training.plugins import CurrentDataFeCAMUpdate, CurrentDataNCMUpdate, FeCAMOracle, MemoryFeCAMUpdate, MemoryNCMUpdate, NCMOracle
  from avalanche.training.supervised import Naive
  from tests.unit_tests_utils import load_benchmark
label_desc: Use image node_id 1 for calling the UpdateFeCAMTest obj's underlying member method code with example usage: obj.create_strategy_and_benchmark() and returns: strategy,  benchmark