Version History

  • 2.4.1 (4/22/22)

    • Minor usability improvements for LEIP Recipes

    • Recipe configs are now stored in container by default for offline use cases.

  • 2.4.0 (4/8/22)

    • Initial release of LEIP Recipes

    • Support for generation of python and C++ libraries in LEIP Package

    • Improve LEIP Pipeline metrics to allow 'experiments' endpoint in LEIP Enterprise

    • Add support for power op when using a keras batchnorm

  • 2.3.0 (3/18/22)

    • Update LEIP Evaluate with a more robust and modular implementation

    • Add initial detector support for LEIP Evaluate

    • Add support for custom pre/post processors in LEIP Evaluate

    • Update LEIP Pipeline with the ability to only run certain flows

    • Numerous bug fixes for GlacierVM

  • 2.2.1 (2/23/22)

    • Add enhanced metrics for LEIP Evaluate

  • 2.2 (2/15/22)

    • Add support for the LEIP Enterprise server API

    • Add initial support for LEIP Package

    • Add support for Pytorch and per-channel quantization

    • Fix an issue where compression reports were not rendering for all LEIP Pipeline flows.

    • Replace calibration with GlacierVM

  • 2.1 (11/01/21)

    • Add support for LEIP Enterprise event processing

    • Container level performance and stability optimizations

  • 2.0.2 (9/30/21)

    • Fix an accuracy issue that occurred in Yolo models

  • 2.0.1 (8/27/21)

    • Fix an issue in LEIP Optimize where an INT8 target failed for detection and segmentation models in pytorch.

    • Update LEIP preprocessors with a new signature to support image resizing

    • Add support for TF 2.4.x

    • Add support for ONNX models

  • 2.0 (8/1/21)

    • Introduce LEIP Optimize to encapsulate compress + compile

    • Support for INT8 in Cuda optimized environments

    • Introduce LEIP Pipelines, a workflow module designed for experiment tracking, collaboration and automation

    • Numerous improvements in model ingestion and the pre/post-processing components

    • Support for GPU and CPU container variants, each optimized for specific use-cases

  • 1.9.3 (4/6/21)

    • Update LEIP Compile with an additional –optimization category for CUDA

  • 1.9.2 (3/24/21)

    • Update LEIP Compile so you can specify different kinds of optimizations (kernel or graph) using the –optimization parameter

  • 1.9.1 (3/18/21)

    • Include support for the Android SDK

    • Fix a Pytorch issue with compress and compile throwing a ‘device not found’ error with a GPU config

  • 1.9.0 (2/18/21)

    • Include compiler logs/schedules to remove an external dependency

    • LEIP Convert is now rolled into LEIP Compress

  • 1.8.5 (2/03/21)

    • Add support for transpose_conv layer in LEIP Convert

  • 1.8.4 (1/20/21)

    • Update, using LEIP evaluate, if the batch size is > 1 the reported inference speed was artificially slow

    • Update documentation to include more detailed information about using a GPU and docker

    • Refactoring out preprocessors into a new module

    • Updated security patches for TF, Pillow, Open SSL, etc

  • 1.8.3 (12/15/20)

    • If the input shape is None on LEIP Compile, set it to 1 to avoid a segfault.

    • Update the Post Quantizer to resolve an issue where a float32 could be upcast to a float64

  • 1.8.2 (12/11/20)

    • Add batch size support for LEIP evaluate and run

  • 1.8.1 (12/03/20)

    • Add more robust support for TF eager execution

  • 1.8.0 (10/24/20)

    • Add Pytorch support for PTQ, including compressing reports

    • Add Pytorch support for LEIP Compile

  • 1.7.3 (09/29/20)

    • Add channel-wise regularizer to QGT

  • 1.7.2 (09/09/20)

    • Add support for batchnorm folding in an .h5 model

    • Add config validation to LEIP train

    • Update LEIP Train to provide a shortcut way to configure homogenous/uniform quantization

    • Fix a bug where LEIP train does not load pre-trained ckpt properly

    • Fix a bug in LEIP train where modify_scheme() being applied to the model json instead of the attachment scheme json

    • Fix a bug in LEIP train where self.attach_regularizers_step() does not load the models weights back

  • 1.7.1 (08/03/20)

    • Add support for Tensorflow 2.3 in the docker image

  • 1.7.0 (00/01/20)

    • Initial release of LEIP Train and QGT (Quantization Guided Training)

    • Update LRE to address an issue with INT8 performance on certain models

    • Update LEIP Evaluate to support model zoo object detection models

    • Fix a performance issue with LEIP Visualize rendering larger models slowly

  • 1.6.0 (07/15/20)

    • Initial release of the LEIP Visualize compression reports

    • Fix an issue where the base ‘Zoo’ command was not loaded properly in the leip-sdk docker container

    • Add a LEIP ‘install’ command to the base set of commands (the install script is still present)

    • Fix a regression where TF loads on all commands even though it’s not required

  • 1.5.1 (07/07/20)

    • Fix an issue when a model wasn’t being saved if the model_schema.json was not present

  • 1.5.0 (06/26/20)

    • Add Tensor Splitting and Bias Correction optimizations to post training quantization

  • 1.4.2

    • GA Release of the LEIP SDK

Known Issues

The following is a list of know issues and limitations for the LEIP SDK Release version:

Compile

  • Compile for INT8 memory size may not be optimal for all hardware, and Compile may not be able to generate a solution for INT8 for all models that may not be optimal.