[train] fix tensorflow example by using ScalingConfig

[mjovanovic9999]

Why are these changes needed?

I was trying to run the basic example https://github.com/ray-project/ray/blob/master/python/ray/train/examples/tf/tune_tensorflow_autoencoder_example.py

Gave me this error:

ValueError: scaling_config should be an instance of ScalingConfig, found <class 'dict'> with value {'num_workers': 2, 'use_gpu': False}.

This chage soloved the issue:

scaling_config = dict(num_workers=num_workers, use_gpu=use_gpu)

to:

from ray.train import ScalingConfig
...
scaling_config = ScalingConfig(num_workers=num_workers, use_gpu=use_gpu)

Related issue number

Closes #46505

Checks

• I've signed off every commit(by using the -s flag, i.e., git commit -s) in this PR.
• I've run scripts/format.sh to lint the changes in this PR.
• I've included any doc changes needed for https://docs.ray.io/en/master/.
  • I've added any new APIs to the API Reference. For example, if I added a
    method in Tune, I've added it in doc/source/tune/api/ under the
    corresponding .rst file.
• I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/
• Testing Strategy
  • Unit tests
  • Release tests
  • This PR is not tested :(

[mjovanovic9999]

@anyscalesam Please review

[matthewdeng]

Nice find!

[matthewdeng]

Could you run the formatting step?

[mjovanovic9999]

@matthewdeng done

[matthewdeng]

thanks!