When adding constraints, auto_assign_transformers is showing columns that should no longer exist

[npatki]

Environment Details

• SDV version: 1.0.0 (in progress)
• Python version: 3.8
• Operating System: Linux (Colab Notebook)

Error Description

When adding constraints, it's expected that some of the columns will be added/removed/modified as a result.

The transformer assignment should happen after the constraints, so I should be able to see the modified column set when inspecting the transformers. However, I see the original column set instead -- with column names and transformers that should no longer exist.

Steps to reproduce

from sdv.multi_table import HMASynthesizer
from sdv.datasets.demo import download_demo

real_data, metadata = download_demo(
    modality='multi_table',
    dataset_name='fake_hotels'
)

synthesizer = HMASynthesizer(metadata)

fixed_location_combinations = {
    'constraint_class': 'FixedCombinations',
    'table_name': 'hotels',
    'constraint_parameters': {
        'column_names': ['city', 'state']
    } 
}

synthesizer.add_constraints([fixed_location_combinations])
synthesizer.auto_assign_transformers(real_data)
synthesizer.get_transformers(table_name='hotels')

The output is:

{'hotel_id': RegexGenerator(regex_format='HID_[0-9]{3}', enforce_uniqueness=True),
 'city': LabelEncoder(add_noise=True),
 'state': LabelEncoder(add_noise=True),
 'rating': FloatFormatter(learn_rounding_scheme=True, enforce_min_max_values=True),
 'classification': LabelEncoder(add_noise=True)}

It's strange that city and state appear here. These columns names should not exist after the constraint processing is done.

Expected

I expect this to be the output of get_transformers:

{'hotel_id': RegexGenerator(regex_format='HID_[0-9]{3}', enforce_uniqueness=True),
 'rating': FloatFormatter(learn_rounding_scheme=True, enforce_min_max_values=True),
 'classification': LabelEncoder(add_noise=True),
 'city#state': LabelEncoder(add_noise=True)}

We can verify that these are the column names by calling preprocess:

synthesizer.preprocess(real_data)['hotels']

Output: