code: def test_trainer_fit(ray_start_4_cpus):
      def training_loop(self):
          train.report(dict(my_metric=1))
  
      trainer = DummyTrainer(train_loop=training_loop)
      result = trainer.fit()
      assert result.metrics["my_metric"] == 1
  
imports: import logging
  import tempfile
  import pytest
  import ray
  from ray import train, tune
  from ray.air.constants import MAX_REPR_LENGTH
  from ray.data.context import DataContext
  from ray.train import Checkpoint, ScalingConfig
  from ray.train.gbdt_trainer import GBDTTrainer
  from ray.train.trainer import BaseTrainer
  from ray.util.placement_group import get_current_placement_group
label_desc: Use image node_id 1 for calling a global function with example usage: test_trainer_fit(ray_start_4_cpus) without return types