code: def train_step_gen(self, training_batch, batch_idx: int):
      print(f"train_step_gen {self.name}")
      assert (
          self.current_epoch in self.expected_epochs
      ), f"{self.current_epoch} {self.expected_epochs}"
      self._call_count["train"] += 1
      x, label = training_batch
  
      self.reporter.log()
  
      y = self.linear1(x)
      yield self.loss_fn(y, label)
      y = self.linear2(x)
      yield self.loss_fn(y, label)
  
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 5 for calling the DummyTrainer obj's underlying member method code with example usage: obj.train_step_gen(training_batch, batch_idx) without return types