v0.13.0

VGSLify v0.13.0 Release Notes

Release Date: October 2024

New Features and Improvements:

1. PyTorch Backend Support:

   • VGSLify now supports the PyTorch backend, alongside TensorFlow. This required updates to the LayerFactory base class to handle parsing the VGSL specification and configuring layers for PyTorch.
   • The TensorFlowLayerFactory and TorchLayerFactory classes are now responsible for implementing their respective layer types.

2. Refactor of VGSL Parsing and Layer Handling:

   • A base class has been introduced for parsing models back to the VGSL specification, with backend-specific subclasses handling the necessary package-specific logic.
   • The overall codebase has been simplified by merging redundant functions. For example, LSTM, GRU, and bidirectional RNNs now share more common code, as do pooling layers like AvgPool and MaxPool.

3. New model_name Parameter:

   • The VGSLModelGenerator.generate_model function now accepts a model_name parameter, allowing users to specify a custom model name instead of the default "VGSL_Model".

4. Reduced Code Duplication:

   • Significant reduction of duplicate code, particularly in the handling of RNNs (LSTM, GRU, bidirectional RNNs) and pooling layers (AvgPool, MaxPool).

5. Updated Documentation:

   • The documentation, README, and examples have been updated to reflect all changes, including PyTorch support, the model_name parameter, and refactoring of VGSL parsing and layer handling.
   • Tutorials and examples are available to guide users through the new features.

Documentation is available at: VGSLify Documentation.