Don't set `sagemaker_s3_output` via hyperparameter

**Describe the feature you'd like**
I discovered an undocumented feature where we can pass a hyperparameter named `sagemaker_s3_output` with an S3 URI. This will result in being able to store data in `opt/ml/output/intermediate` and that will get uploaded to the S3 URI during the training job.

I would like to take advantage of this, though I have 2 concerns.
1. hyperparameter should be reserved exclusively for actual hyperparameter, and not configuration information
2. Where this becomes a real issue is if we warm start a tuning job with different `sagemaker_s3_output`. `sagemaker_s3_output` would have an impact on the tuning strategy even though it shouldn't.

**How would this feature be used? Please describe.**
The `sagemaker_s3_output` value should be set via the [SageMaker CreateTrainingJob Environment parameter](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html#sagemaker-CreateTrainingJob-request-Environment).

The main issue with this is that [SageMaker CreateHyperParameterTuningJob](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateHyperParameterTuningJob.html) has no Environment parameter (this is another feature request I've submitted to the SageMaker team).

**Describe alternatives you've considered**
We could just pass `sagemaker_s3_output` as a hyperparameter and just try to make sure they don't change between warm starts.