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NeuroFlex v0.1.2
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@devin-ai-integration devin-ai-integration released this 16 Sep 08:44
· 270 commits to main since this release
v0.1.2
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NeuroFlex v0.1.2 Release Notes

Major Changes and New Features

  1. Integration of UnifiedTransformer

    • Replaced MergedTransformer and UniqueTransformer with a single, more versatile UnifiedTransformer
    • Improved support for multiple backends (PyTorch, JAX, Flax, and Sonnet)
    • Enhanced text processing, generation, and few-shot learning capabilities

  2. Removal of Protein Development LLM

    • Streamlined codebase by removing the protein development-specific language model
    • Refactored related tests and references

  3. CI/CD Workflow Updates

    • Implemented a new GitHub Actions workflow for automated testing and deployment
    • Added steps for creating necessary directories and debugging file-related issues

  4. Core Functionality Improvements

    • Updated NeuroFlex class to incorporate UnifiedTransformer
    • Enhanced setup methods for better component initialization
    • Improved compatibility across multiple scientific domains

  5. Performance Enhancements

    • Resolved optimization issues, including LNSRCH termination problems
    • Improved math solver with custom error handling and fallback methods

Bug Fixes

  • Fixed line search warnings in the optimization algorithm
  • Resolved dimension mismatch issues in transformer tests
  • Addressed various deprecation warnings throughout the codebase

Breaking Changes

  • Removal of protein_development_llm.py and associated functionalities
  • Changes to the transformer API due to the introduction of UnifiedTransformer

Compatibility

  • This version is compatible with Python 3.8 and above
  • Updated dependencies (see requirements.txt for details)

Known Issues

  • Some AlphaFold integration tests are currently skipped and need attention
  • A few Edge AI optimization tests are pending implementation

Future Work

  • Expand test coverage for UnifiedTransformer-specific functionality
  • Address remaining skipped tests in AlphaFold and Edge AI modules
  • Further optimize UnifiedTransformer performance
  • Implement regular test suite runs to monitor progress and catch regressions early

For a complete list of changes, please refer to the commit history.

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