code: def train_tensorflow_mnist(
      num_workers: int = 2,
      use_gpu: bool = False,
      epochs: int = 4,
      storage_path: str = None,
  ) -> Result:
      config = {"lr": 1e-3, "batch_size": 64, "epochs": epochs}
      trainer = TensorflowTrainer(
          train_loop_per_worker=train_func,
          train_loop_config=config,
          scaling_config=ScalingConfig(
              num_workers=num_workers, use_gpu=use_gpu
          ),
          run_config=RunConfig(storage_path=storage_path),
      )
      results = trainer.fit()
      return results
  
file_path: ray/python/ray/train/examples/tf/tensorflow_mnist_example.py
imports: import argparse
  import json
  import os
  import numpy
  import tensorflow
  from filelock import FileLock
  from ray.air.integrations.keras import ReportCheckpointCallback
  from ray.train import Result, RunConfig, ScalingConfig
  from ray.train.tensorflow import TensorflowTrainer
label_desc: Use image node_id 4 for calling a global function with example usage: train_tensorflow_mnist(num_workers, use_gpu, epochs, storage_path) and returns: results