code: def main():
      """
      Run the experiment
      """
      experiment.create(name="ponder_net")
  
      conf = Configs()
      experiment.configs(
          conf,
          {
              "optimizer.optimizer": "Adam",
              "optimizer.learning_rate": 0.0003,
          },
      )
  
      with experiment.start():
          conf.run()
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/adaptive_computation/ponder_net/experiment.py
imports: from typing import Any
  import torch
  from torch import nn
  from torch.utils.data import DataLoader
  from labml import tracker, experiment
  from labml_helpers.metrics.accuracy import AccuracyDirect
  from labml_helpers.train_valid import SimpleTrainValidConfigs, BatchIndex
  from labml_nn.adaptive_computation.parity import ParityDataset
  from labml_nn.adaptive_computation.ponder_net import ParityPonderGRU, ReconstructionLoss, RegularizationLoss
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types