code: def _test_logger(self, logp):
      evalp = EvaluationPlugin(
          loss_metrics(
              minibatch=True, epoch=True, experience=True, stream=True
          ),
          loggers=[logp],
      )
      strat = Naive(
          self.model, self.optimizer, evaluator=evalp, train_mb_size=32
      )
      for e in self.benchmark.train_stream:
          strat.train(e)
      strat.eval(self.benchmark.train_stream)
  
file_path: avalanche/tests/test_loggers.py
imports: import unittest
  from torch.optim import SGD
  from avalanche.evaluation.metrics import loss_metrics
  from avalanche.models import SimpleMLP
  from avalanche.training import Naive
  from avalanche.training.plugins import EvaluationPlugin
  from tests.unit_tests_utils import get_fast_benchmark
  from avalanche.logging import TextLogger, TensorboardLogger, InteractiveLogger
  from avalanche.logging.csv_logger import CSVLogger
  import tempfile
label_desc: Use image node_id 7 for calling the TestLoggers obj's underlying member method code with example usage: obj._test_logger(logp) without return types