CTGAN

This release removes a warning that was cluttering the console.

Maintenance

• Cleanup automated PR workflows - Issue #370 by @R-Palazzo
• Only run unit and integration tests on oldest and latest python versions for macos - Issue #375 by @R-Palazzo

Internal

• Remove FutureWarning: Setting an item of incompatible dtype is deprecated - Issue #373 by @fealho

This release adds support for Python 3.12!

Maintenance

• Support Python 3.12 - Issue #324 by @fealho
• Remove scikit-learn dependency - Issue #346 by @R-Palazzo
• Add bandit workflow - Issue #353 by @R-Palazzo

Internal

• Replace integration test that uses the iris demo data - Issue #352 by @R-Palazzo

Bugs Fixed

• Fix minimum version workflow when pointing to github branch - Issue #355 by @R-Palazzo

This release changes the loss_values attribute of a CTGAN model to contain floats instead of torch.Tensors.

New Features

• Return loss values as float values not PyTorch objects - Issue #332 by @fealho

Maintenance

• Transition from using setup.py to pyproject.toml to specify project metadata - Issue #333 by @R-Palazzo
• Remove bumpversion and use bump-my-version - Issue #334 by @R-Palazzo
• Add dependency checker - Issue #336 by @amontanez24

This release makes CTGAN sampling more efficient by saving the frequency of each categorical value.

New Features

• Improve DataSampler efficiency - Issue #327 by @fealho

This release adds a progress bar that will show when setting the verbose parameter to True when initializing TVAE.

New Features

• Add verbosity TVAE (progress bar + save the loss values) - Issue [#300]((https://github.com/sdv-dev/CTGAN/issues/300) by @frances-h

This release adds a progress bar that will show when setting the verbose parameter to True when initializing CTGAN. It also removes a warning that was showing.

Maintenance

• Remove model_missing_values from ClusterBasedNormalizer call - PR #310 by @fealho
• Switch default branch from master to main - Issue #311 by @amontanez24
• Remove or implement CTGAN tests - Issue #312 by @fealho

New Features

• Add progress bar for CTGAN fitting (+ save the loss values) - Issue #298 by @frances-h

This release adds support for Python 3.11 and drops support for Python 3.7.

Maintenance

• Why is there an upper bound in the packaging requirement? (packaging<22) - Issue #276 by @fealho
• Add support for Python 3.11 - Issue #296 by @fealho
• Drop support for Python 3.7 - Issue #302 by @fealho

This release adds support for Torch 2.0!

Bugs Fixed

• Torch 2.0 fails with cuda=False - Issue #288 by @amontanez24

Maintenance

• Upgrade to torch 2.0 - Issue #280 by @frances-h

This release adds support for Pandas 2.0! It also fixes a bug in the load_demo function.

Bugs Fixed

• load_demo raises urllib.error.HTTPError: HTTP Error 403: Forbidden - Issue #284 by @amontanez24

Maintenance

• Remove upper bound for pandas - Issue #282 by @frances-h

This release fixes a bug that prevented the CTGAN model from being saved after sampling.

Bugs Fixed

• Cannot save CTGANSynthesizer after sampling (TypeError) - Issue #270 by @pvk-developer

This release adds support for python 3.10 and drops support for python 3.6. It also fixes a couple of the most common warnings that were surfacing.

New Features

• Support Python 3.10 and 3.11 - Issue #259 by @pvk-developer

Bugs Fixed

• Fix SettingWithCopyWarning (may be leading to a numerical calculation bug) - Issue #215 by @amontanez24
• FutureWarning in data_transformer with pandas 1.5.0 - Issue #246 by @amontanez24

Maintenance

• CTGAN Package Maintenance Updates - Issue #257 by @amontanez24

This release renames the models in CTGAN. CTGANSynthesizer is now called CTGAN and TVAESynthesizer is now called TVAE.

New Features

• Rename synthesizers - Issue #243 by @amontanez24

This release updates CTGAN to use the latest version of RDT. It also includes performance and robustness updates to the data transformer.

Issues closed

• Bump rdt version - Issue #242 by @katxiao
• Single thread data transform is slow for huge table - Issue #151 by @mfhbree
• Fix RDT api - Issue #232 by @pvk-developer
• Update macos to use latest version. - Issue #237 by @pvk-developer
• Update the RDT version to 1.0 - Issue #224 by @pvk-developer
• Update slack invite link. - Issue #222 by @pvk-developer
• robustness fix, when data have less rows than the default number of cl… - Issue #211 by @Deathn0t

Issues closed

• Update self.decoder with correct variable name - Issue #203 by @tejuafonja
• Add random state - Issue #204 by @katxiao

This release adds support for Python 3.9 and updates dependencies to ensure compatibility with the rest of the SDV ecosystem, and upgrades to the latests RDT release.

Issues closed

• Add support for Python 3.9 - Issue #177 by @pvk-developer
• Add pip check to CI workflows - Issue #174 by @pvk-developer
• Typo in CTGAN code - Issue #158 by @ori-katz100 and @fealho

Dependency upgrades to ensure compatibility with the rest of the SDV ecosystem.

In this release, the way in which the loss function of the TVAE model was computed has been fixed. In addition, the default value of the discriminator_decay has been changed to a more optimal value. Also some improvements to the tests were added.

Issues closed

• TVAE: loss function - Issue #143 by @fealho and @DingfanChen
• Set discriminator_decay to 1e-6 - Pull request #145 by @fealho
• Adds unit tests - Pull requests #140 by @fealho

This release exposes all the hyperparameters which the user may find useful for both CTGAN and TVAE. Also TVAE can now be fitted on datasets that are shorter than the batch size and drops the last batch only if the data size is not divisible by the batch size.

Issues closed

• TVAE: Adapt batch_size to data size - Issue #135 by @fealho and @csala
• ValueError from validate_discre_columns with uniqueCombinationConstraint - Issue 133 by @fealho and @MLjungg

Maintenance relese to upgrade dependencies to ensure compatibility with the rest
of the SDV libraries.

Also add a validation on the CTGAN condition_column and condition_value inputs.

Improvements

• Validate condition_column and condition_value - Issue #124 by @fealho

Improvements

• Check discrete_columns valid before fitting - Issue #35 by @fealho

Bugs fixed

• ValueError: max() arg is an empty sequence - Issue #115 by @fealho