code: def log_validation_results(trainer):
      train_evaluator.run(train_loader)
      val_evaluator.run(val_loader)
  
file_path: aim/examples/pytorch_ignite_track.py
imports: import ignite
  import torch
  import torch.nn.functional
  from aim.pytorch_ignite import AimLogger
  from ignite.contrib.handlers import ProgressBar
  from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer
  from ignite.handlers import EarlyStopping, global_step_from_engine
  from ignite.metrics import Accuracy, ConfusionMatrix, Loss, RunningAverage
  from torch import nn, optim
  from torch.utils.data import DataLoader
  from torchvision import datasets, transforms
label_desc: Use image node_id 2 for calling a global function with example usage: log_validation_results(trainer) without return types