TabARGN¶

class synthyverse.generators.tabargn_generator.TabARGNGenerator(workspace, max_epochs=100, random_state=0, **kwargs)[source]¶

Bases: TabularBaseGenerator

Tabular AutoRegressive Generative Network (TabARGN).

TabARGN uses masked transformers for tabular data generation.

We use the implementation from the MostlyAI engine.

Paper: “TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data” by Tiwald et al. (2025).

Parameters:

workspace (str) – Directory for storing intermediate files.
max_epochs (int) – Maximum number of training epochs. Default: 100.
random_state (int) – Random seed for reproducibility. Default: 0.
**kwargs – Additional arguments passed to TabularBaseGenerator.

Example

>>> import pandas as pd
>>> from synthyverse.generators import TabARGNGenerator
>>>
>>> # Load data
>>> X = pd.read_csv("data.csv")
>>> discrete_features = ["category_col"]
>>>
>>> # Create generator (requires workspace)
>>> generator = TabARGNGenerator(
...     workspace="./tabargn_workspace",
...     max_epochs=100,
...     random_state=42
... )
>>>
>>> # Fit and generate
>>> generator.fit(X, discrete_features)
>>> X_syn = generator.generate(1000)