code: def step(self):
      for _i in range(30):
          loss = (
              self.config["mean"]
              + self.config["sd"] * np.random.randn()
          )
          wandb.log({"loss": loss})
      return {"loss": loss, "done": True}
  
file_path: wandb/tests/functional_tests/t0_main/raytune/t4_trainable.py
imports: import numpy
  import wandb
  from _test_support import get_wandb_api_key_file
  from ray import tune
  from ray.tune import Trainable
  from ray.tune.integration.wandb import WandbTrainableMixin
label_desc: Use image node_id 1 for calling the WandbTrainable obj's underlying member method code with example usage: obj.step() and returns: dict