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Intel® End-to-End AI Optimization Kit release v1.0
Highlights
This release introduces a new component: multi-model, hardware-aware training free neural architecture search module DE-NAS to extend model optimization to more domains. DE-NAS supports CNN, ViT, NLP and ASR models, and leverage training-free score to construct compact models directly on CPU clusters.
This release provides following major features:
- Multi-model, hardware aware training free NAS framework
- Pluggable search strategy
- Training-free scoring for candidate evaluation
- CNN, ViT, NLP, ASR DE-NAS recipes
Improvements
- New docker file supports PyTorch 1.12
- New CI/CD workflows support
- Updated data processing with RecDP for DLRM
- Automated packaging and delivery
Versions and Components
- TensorFlow 2.10
- PyTorch 1.5, 1.10, 1.12
- Intel® Extension for TensorFlow 2.10.x
- Intel® Extension for Pytorch 0.2, 1.10.x, 1.12.x
- Horovod 0.26
- Spark 3.1
- Python 3.x
Links
- https://github.com/intel/e2eAIOK
- https://pypi.org/project/e2eAIOK
- https://hub.docker.com/repository/docker/e2eaiok/e2eaiok-tensorflow
- https://hub.docker.com/repository/docker/e2eaiok/e2eaiok-pytorch
Full Changelog: https://github.com/intel/e2eAIOK/commits/v1.0