Integrate GaussianCopula model into the Synthesizer.

sdgx/models/statistics/single_table/base.py

@@ -2,24 +2,28 @@
 # Which is Lincensed by MIT License
 
 import os
-from copy import deepcopy
-from typing import List, Optional
 
 import numpy as np
 import torch
 
+from sdgx.data_loader import DataLoader
+from sdgx.data_models.metadata import Metadata
+from sdgx.models.base import SynthesizerModel
 
-class StatisticSynthesizerModel:
+
+class StatisticSynthesizerModel(SynthesizerModel):
     random_states = None
 
-    def __init__(self, transformer=None, sampler=None) -> None:
+    def __init__(self, transformer=None, sampler=None, *args, **kwargs) -> None:
+        super().__init__(*args, **kwargs)
+        self._generator = None
         self.model = None
         self.status = "UNFINED"
         self.model_type = "MODEL_TYPE_UNDEFINED"
         # self.epochs = epochs
         self._device = "CPU"
 
-    def fit(self, input_df, discrete_cols: Optional[List] = None):
+    def fit(self, metadata: Metadata, dataloader: DataLoader, *args, **kwargs):
         raise NotImplementedError
 
     def set_device(self, device):

sdgx/models/statistics/single_table/copula.py

@@ -9,16 +9,13 @@
 import sdgx.models.components.sdv_copulas as copulas
 from sdgx.data_loader import DataLoader
 from sdgx.data_models.metadata import Metadata
-from sdgx.exceptions import NonParametricError, SynthesizerInitError
+from sdgx.exceptions import NonParametricError
 from sdgx.models.components.optimize.sdv_copulas.data_transformer import (
     StatisticDataTransformer,
 )
 from sdgx.models.components.sdv_copulas import multivariate
-from sdgx.models.components.sdv_ctgan.data_transformer import DataTransformer
-from sdgx.models.components.sdv_rdt.transformers import OneHotEncoder
 from sdgx.models.components.utils import (
     flatten_dict,
-    log_numerical_distributions_error,
     unflatten_dict,
     validate_numerical_distributions,
 )
@@ -27,7 +24,7 @@
 LOGGER = logging.getLogger(__name__)
 
 
-class GaussianCopulaSynthesizer(StatisticSynthesizerModel):
+class GaussianCopulaSynthesizerModel(StatisticSynthesizerModel):
     """Model wrapping ``copulas.multivariate.GaussianMultivariate`` copula.
 
     Args:

tests/models/test_copula.py

@@ -1,10 +1,7 @@
-from pathlib import Path
-
 import pandas as pd
 import pytest
 
-from sdgx.models.statistics.single_table.copula import GaussianCopulaSynthesizer
-from sdgx.utils import get_demo_single_table
+from sdgx.models.statistics.single_table.copula import GaussianCopulaSynthesizerModel
 
 
 @pytest.fixture
@@ -13,7 +10,7 @@ def dummy_data(dummy_single_table_path):
 
 
 def test_gaussian_copula(dummy_single_table_metadata, dummy_single_table_data_loader):
-    model = GaussianCopulaSynthesizer()
+    model = GaussianCopulaSynthesizerModel()
     model.fit(dummy_single_table_metadata, dummy_single_table_data_loader)
 
     sampled_data = model.sample(10)