All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- Enhanced benchmarking capabilities with CPU performance analysis
- New optimization improvements for data loading
- Updated benchmarking infrastructure for better performance analysis
- Improved README documentation
- Updated package name to match PyPI repository
- Fixed GitHub Actions workflow for automated releases
- Comprehensive examples demonstrating key features
- Memory management with allocation stack
- Enhanced batch size calculation for multi-GPU scenarios
- Improved error handling and recovery
- Progress tracking with detailed statistics
- Data caching with automatic cleanup
- Support for various data formats (CSV, JSON, Images)
- Improved memory management with better allocation tracking
- Enhanced batch size calculation for multi-GPU scenarios
- Better error handling and recovery mechanisms
- Updated documentation with examples and tutorials
- Optimized data loading performance
- Memory leaks in cleanup operations
- Batch size calculation for device distribution
- Progress tracking accuracy
- Test reliability and coverage
- Multi-GPU batch distribution issues
- Added comprehensive examples
- Updated README with installation and usage instructions
- Added API documentation
- Included example requirements and setup guide
- Added detailed feature documentation
- Added data loading demo with multiple formats
- Included sample data generation scripts
- Added configuration examples
- Demonstrated key features with real-world scenarios
- Added multi-GPU usage examples
- Initial release of JAX DataLoader
- Support for multiple data formats (CSV, JSON, Images)
- Multi-GPU support with automatic batch distribution
- Memory management with automatic batch size tuning
- Progress tracking and statistics
- Data caching and prefetching
- Type hints and documentation
- Improved memory management with allocation stack
- Enhanced batch size calculation for multi-GPU scenarios
- Better error handling and recovery
- Updated documentation with examples
- Memory leaks in cleanup operations
- Batch size calculation for device distribution
- Progress tracking accuracy
- Test reliability and coverage
- Added comprehensive examples
- Updated README with installation and usage instructions
- Added API documentation
- Included example requirements and setup guide
- Added data loading demo with multiple formats
- Included sample data generation scripts
- Added configuration examples
- Demonstrated key features with real-world scenarios