Integrate GaussianCopula model into the Synthesizer.

[jalr4ever]

Description

I have made GaussianCopula extended with SynthesizerModel.

Motivation and Context

We could see that the Core Data Pre-Post Process Pipeline was triggered in Synthesizer, which meant data would not be processed if just instance a Model to sythetic data, you have to assign a model to Synthesizer.

Now we support model=GaussianCopulaSynthesizerModel(), we could write code just like this:

from sdgx.data_connectors.csv_connector import CsvConnector
from sdgx.models.ml.single_table.ctgan import CTGANSynthesizerModel
from sdgx.synthesizer import Synthesizer
from sdgx.utils import download_demo_data

# This will download demo data to ./dataset
dataset_csv = download_demo_data()

# Create data connector for csv file
data_connector = CsvConnector(path=dataset_csv)

# Initialize synthesizer, use GaussianCopula model
synthesizer = Synthesizer(
    model=GaussianCopulaSynthesizerModel(),  # For quick demo
    data_connector=data_connector,
)

# Fit the model
synthesizer.fit()

# Sample
sampled_data = synthesizer.sample(1000)
print(sampled_data)

How has this been tested?

Types of changes

• Maintenance (no change in code, maintain the project's CI, docs, etc.)
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist:

• My code follows the code style of this project.
• My change requires a change to the documentation.
• I have updated the documentation accordingly.

[Wh1isper]

LGTM