Set HyperTransformer config manually, based on Metadata if given

[npatki]

Environment Details

• SDV version: 0.17.0.dev1

Error Description

1. The entire RDT HyperTransformer config is being printed out during modeling. This is unnecessarily verbose because I don't have any way of changing it right now. (Especially the case for HMA1.)
2. The HyperTransformer config does not properly correspond to the metadata that I provide. For example, if I specify that a column is type categorical, it is being detected and modeled as numerical.

Steps to reproduce

metadata, data = load_tabular_demo('student_placements', metadata=True)
model = GaussianCopula(
    table_metadata=metadata
)
model.fit(data)
synthetic_data = model.sample(num_rows=100)

Observe that the config is printed out. Also observe that the column duration is listed as categorical but is being read in as numerical. It's also being modeled as numerical, as the synthetic data includes values that are not previously see in the real data.

Expected Fix

If we use HyperTransformer set_config, we can solve both issues.

• The config is printed out during detect_initial_config, which we don't need to do
• The config we set should be based on the metadata that the user provides (if applicable). If not provided, it should be based on the pandas dtypes of the passed in data.