code: def test_multi_stage_trainer(self):
      input_dim = 5
      stage1 = DummyTrainer(
          "stage1",
          input_dim,
          expected_epochs=[0, 1, 2],
          validation_keys=["a", "b", "c"],
          test_keys=["d", "e"],
      )
      stage2 = DummyTrainer(
          "stage2",
          input_dim,
          expected_epochs=[3, 4, 5],
          validation_keys=["x", "y", "z"],
          test_keys=["u", "v"],
      )
      multi_stage_trainer = MultiStageTrainer(
          [stage1, stage2],
          epochs=[3, 3],
      )
  
      reporters = [
          DummyReporter("stage1", expected_epochs=[0, 1, 2]),
          DummyReporter("stage2", expected_epochs=[3, 4, 5]),
      ]
      compound_reporter = CompoundReporter(reporters, _merge_report)
      multi_stage_trainer.set_reporter(compound_reporter)
  
      training_size = 100
      validation_size = 20
      train_dataloader = DataLoader(
          make_dataset(input_dim, training_size), batch_size=5
      )
      validation_dataloader = DataLoader(
          make_dataset(input_dim, validation_size),
          batch_size=5,
      )
  
      trainer = pl.Trainer(max_epochs=6, min_epochs=6)
      trainer.fit(
          multi_stage_trainer, train_dataloader, validation_dataloader
      )
  
      test_size = 20
      test_dataloader = DataLoader(
          make_dataset(input_dim, test_size),
          batch_size=5,
      )
      trainer.test(dataloaders=test_dataloader)
      print(f"stage1 {stage1._call_count}")
      print(f"stage2 {stage2._call_count}")
      self.assertEqual(stage1._call_count["train"], 60)
      # It seems that lightning call validation 2 times at the beginning
      self.assertEqual(stage1._call_count["validation"], 14)
      self.assertEqual(stage1._call_count["test"], 4)
      self.assertEqual(stage2._call_count["train"], 60)
      self.assertEqual(stage2._call_count["validation"], 12)
      self.assertEqual(stage2._call_count["test"], 4)
  
      for reporter, t in zip(reporters, [stage1, stage2]):
          print(
              f"{reporter.name} {reporter._log_count} {reporter._flush_count}"
          )
          self.assertEqual(reporter._log_count, t._call_count["train"])
          # flush got called in train & validation 3 times each.
          # In stage1, there is an additional call to validation at the beginning
          self.assertEqual(
              reporter._flush_count, 8 if t == stage1 else 7
          )
  
imports: import unittest
  from typing import List
  import pytorch_lightning
  import torch
  import torch.nn
  import torch.optim
  from reagent.reporting import CompoundReporter, ReporterBase
  from reagent.training import MultiStageTrainer, ReAgentLightningModule
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 1 for calling the TestMultiStageTrainer obj's underlying member method code with example usage: obj.test_multi_stage_trainer() without return types