Changelog

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.

[0.1.10] - 2025-04-13

Added

  • Enhanced benchmarking capabilities with CPU performance analysis

  • New optimization improvements for data loading

Changed

  • Updated benchmarking infrastructure for better performance analysis

  • Improved README documentation

[0.1.2] - 2025-03-30

Changed

  • Updated package name to match PyPI repository

  • Fixed GitHub Actions workflow for automated releases

[0.1.1] - 2025-03-30

Added

  • 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)

Changed

  • 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

Fixed

  • Memory leaks in cleanup operations

  • Batch size calculation for device distribution

  • Progress tracking accuracy

  • Test reliability and coverage

  • Multi-GPU batch distribution issues

Documentation

  • Added comprehensive examples

  • Updated README with installation and usage instructions

  • Added API documentation

  • Included example requirements and setup guide

  • Added detailed feature documentation

Examples

  • Added data loading demo with multiple formats

  • Included sample data generation scripts

  • Added configuration examples

  • Demonstrated key features with real-world scenarios

[0.1.0] - 2025-03-19

Added

  • 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

Changed

  • Improved memory management with allocation stack

  • Enhanced batch size calculation for multi-GPU scenarios

  • Better error handling and recovery

  • Updated documentation with examples

Fixed

  • Memory leaks in cleanup operations

  • Batch size calculation for device distribution

  • Progress tracking accuracy

  • Test reliability and coverage

Documentation

  • Added comprehensive examples

  • Updated README with installation and usage instructions

  • Added API documentation

  • Included example requirements and setup guide

Examples

  • Added data loading demo with multiple formats

  • Included sample data generation scripts

  • Added configuration examples

  • Demonstrated key features with real-world scenarios