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Releases: OpenTabular/DeepTab

v1.8.0

24 May 09:18
56763ea

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What's Changed

Full Changelog: v1.7.0...v1.8.0

Release v1.7.0

14 May 11:41
7539961

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What's Changed

Highlights

  • Improved the testing framework with better cross-platform support.
  • Fixed MambularDataset length handling for datasets with only categorical features.
  • Simplified CI/CD and release workflows.
  • Updated release process with improved PyPI publishing flow.
  • Added documentation improvements and additional tests.
  • Completed the final release bump from 1.7.0rc2 to 1.7.0.

Bug Fixes

  • Fixed MambularDataset length for data with only categorical features by @MaxSchambach in #278.
  • Merged 1.7.0 hotfixes back into main by @mkumar73 in #334.

CI/CD and Release Improvements

  • Added conventional commit and semantic release setup by @mkumar73 in #295.
  • Simplified branching, hardened release workflow, and updated PyPI publishing flow by @mkumar73 in #320.
  • Fixed GitHub Actions workflow by simplifying package installation by @ChrisW09 in #286.
  • Synced development branch after semantic release by @mkumar73 in #296.

Documentation, Testing, and Maintenance

  • Enhanced testing framework with cross-platform support by @mhabedank in #266.
  • Added release updates, documentation improvements, and tests by @mkumar73 in #326.
  • Updated project configuration by @ChrisW09 in #274.

Repository Rename and Cleanup

Release Preparation

New Contributors

Full Changelog

v1.5.0...v1.7.0

What's Changed

New Contributors

Full Changelog: v1.5.0...v1.7.0

v1.7.0rc2

08 May 22:22

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v1.7.0rc2 Pre-release
Pre-release

What's Changed

New Contributors

Full Changelog: v1.5.0...v1.7.0rc2

Release v1.5.0

14 Apr 22:09
28b5456

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This release includes significant updates to the mambular package, focusing on integrating the pretab library for preprocessing, updating the version, and removing deprecated preprocessing modules. The most important changes include updating the documentation, modifying imports to use pretab, and removing old preprocessing code.

Documentation Updates:

  • README.md: Updated preprocessing section to mention the use of pretab and provided links for further information.
  • docs/api/preprocessing/Preprocessor.rst: Removed the Preprocessor class documentation.
  • docs/api/preprocessing/index.rst: Removed the preprocessing module documentation.

Codebase Updates:

  • mambular/__version__.py: Updated the version from 1.4.0 to 1.5.0.
  • mambular/models/utils/sklearn_base_lss.py and mambular/models/utils/sklearn_parent.py: Changed imports from mambular.preprocessing to pretab.preprocessor and updated related code. [1] [2]

Removal of Deprecated Code:

  • mambular/preprocessing/basis_expansion.py, mambular/preprocessing/ple_encoding.py, and mambular/preprocessing/__init__.py: Removed old preprocessing classes and methods. [1] [2] [3]

What's Changed

New Contributors

Full Changelog: v1.4.0...v1.5.0

Release 1.4.0

24 Mar 11:01
5db5426

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What's Changed

  • Hotfix/docs by @mkumar73 in #247
  • Modernnca by @AnFreTh in #251
    * Added MonderNCA and complete logic of using labels during training and inference into helper classes.
  • Data check by @AnFreTh in #252
    * Introduced sanity checks in preprocessor module.
  • Develop by @AnFreTh in #253

Full Changelog: v1.3.2...v1.4.0

Release 3.1.2

19 Mar 17:40
0d7be4a

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Fix error for binary classification loss function in sklearninterface

Release v1.3.1

17 Mar 12:48
01a7212

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This release (v1.3.1) introduces the new Tangos model to the Mambular library, along with updates to the documentation, versioning, and configuration files. The most important changes include adding the Tangos model, updating the version number, and modifying the lightning_wrapper.py and pretraining.py files to use the new model.

New Model Addition:

  • mambular/base_models/tangos.py: Added the Tangos model, which is an MLP model with optional GLU activation, batch normalization, layer normalization, and dropout, including a penalty term for specialization and orthogonality.
  • mambular/base_models/__init__.py: Included the Tangos model in the module imports and __all__ list.
  • mambular/configs/tangos_config.py: Added configuration class for the Tangos model with predefined hyperparameters.

Documentation Updates:

  • README.md: Updated to include the new Tangos model in the list of new models and added a description of the model. [1] [2]

Version Update:

  • mambular/__version__.py: Incremented the version number from 1.3.0 to 1.3.1 to reflect the new changes.

Code Refactoring:

  • mambular/base_models/utils/lightning_wrapper.py: Replaced instances of base_model with estimator to accommodate the new Tangos model. [1] [2] [3] [4] [5] [6] [7] [8] [9]
  • mambular/base_models/utils/pretraining.py: Replaced instances of base_model with estimator to reflect the new model structure. [1] [2] [3] [4]

Configuration Updates:

  • mambular/configs/__init__.py: Added DefaultTangosConfig to the module imports and __all__ list.
  • mambular/models/__init__.py: Included TangosClassifier, TangosLSS, and TangosRegressor in the module imports and __all__ list.

v1.3.0

13 Mar 10:36
180f126

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What's Changed in v1.3.0

This Release includes several changes to the mambular package, focusing on refactoring imports and enhancing the functionality of the BaseModel and TaskModel classes. The most important changes include moving BaseModel and TaskModel to a new utils directory, updating import paths accordingly, and adding new methods for pretraining embeddings. Additionally, two new models, Trompt and AutoInt are included in v1.3.0

Refactoring imports:

  • Moved BaseModel and TaskModel to mambular/base_models/utils/ and updated import paths in all relevant files. [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13]

Include new models

  • New model architectures TromptandAutoIntare now included into mambular.

Introduce pretrainingoption:

  • Added pertaining functionality for all models that use encoders.

Include dilation to 1DConv layers in Mambular/TabulaRNN

Enhancements to BaseModel:

  • Added new methods for embedding management, including embedding_parameters, encode_features, get_embedding_state_dict, and load_embedding_state_dict.
  • Modified the encode method to support gradient computation and shuffling embeddings.

Enhancements to TaskModel:

  • Added a new method pretrain_embeddings for pretraining embeddings using contrastive learning.
  • Introduced helper methods get_knn and contrastive_loss to support the new pretraining functionality.

Miscellaneous changes:

  • Added print statements for debugging and logging purposes. [1] [2]
  • Minor formatting changes for code readability.

Release v1.2.0

17 Feb 09:59
25b88a3

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Release v1.2.0

This update enhances the preprocessing and embedding layers in the mambular package, introducing several key improvements:

  • Feature-Specific Preprocessing: The Preprocessor class now includes a feature preprocessing dictionary, enabling different preprocessing strategies for each feature.
  • Support for Unstructured Data: The model can now handle a combination of tabular features and unstructured data, such as images and text.
  • Latent Representation Generation: It is now possible to generate latent representations of the input data, improving downstream modeling and interpretability.

These changes enhance flexibility and extend mambular's capabilities to more diverse data modalities.

Preprocessing improvements:

  • mambular/preprocessing/preprocessor.py: Added feature_preprocessing parameter to allow custom preprocessing techniques for individual columns. Updated the fit method to use this parameter for both numerical and categorical features. [1] [2] [3] [4] [5]

Embedding layer updates:

  • mambular/arch_utils/layer_utils/embedding_layer.py: Modified the forward method to handle different dimensions of categorical embeddings and ensure they are properly processed. [1] [2]

Allow unstructured data as inputs:

  • mambular/arch_utils/layer_utils/embedding_layer.py: Modified the forward method to handle num_features, cat_features and pre-embedded unstructured data. [1] [2]

Get latent representation of tables

  • mambular/base_models/basemodel.py: Updated the encode method to accept a single data parameter instead of separate num_features and cat_features parameters. [1] [2]

Release v1.1.0

03 Jan 18:53
648d029

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What's Changed

🚀 New Models

  • SAINT: Improve neural networks via Row Attention and Contrastive Pre-Training

Continuous improvements and bug fixes

  • Deprecated setup.py for pyproject.toml
  • Formatting and linting
  • Pre-commit hooks
  • Documentation update
  • Bug fixes

Contributors:

Full Changelog: v1.0.0...v1.1.0