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CHANGELOG.rst

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Changelog

Current release candidate

0.6.2 (2020-06-18)

  • Minor bugfixes

0.6.1 (2020-06-15)

  • Deleted accidental debug 'print' call :/

0.6.0 (2020-06-12)

  • Prebuilt flask server images for faster image build
  • More and better methods in Ebonite client
  • Pipelines - chain Models methods into one Model-like objects
  • Refactioring of image and instance API
  • Rework of pandas DatasetType: now with column types, even non-primitive (e.g. datetimes)
  • Helper functions for stanalone docker build/run
  • Minor bugfixes and features

0.5.2 (2020-05-16)

  • Fixed dependency inspection to include wrapper dependencies
  • Fixed s3 repo to fail with subdirectories
  • More flexible way to add parameters for instance running (e.g. docker run arguments)
  • Added new type of Requirement to represent unix packages - for example, libgomp for xgboost
  • Minor tweaks

0.5.1 (2020-04-16)

  • Minor fixes and examples update

0.5.0 (2020-04-10)

  • Built Docker images and running Docker containers along with their metadata are now persisted in metadata repository
  • Added possibility to track running status of Docker container via Ebonite client
  • Implemented support for pushing built images to remote Docker registry
  • Improved testing of metadata repositories and Ebonite client and fixed discovered bugs in them
  • Fixed bug with failed transactions not being rolled back
  • Fixed bug with serialization of complex models some component of which could not be pickled
  • Decomposed model IO from model wrappers
  • bytes are now used for binary datasets instead of file-like objects
  • Eliminated build_model_flask_docker in favor of Server-driven abstraction
  • Sped up PickleModelIO by avoiding ModelAnalyzer calls for non-model objects
  • Sped up Model.create by calling model methods with given input data just once
  • Dataset types and model wrappers expose their runtime requirements

0.4.0 (2020-02-17)

  • Implemented asyncio-based server via aiohttp library
  • Implemented support for Tensorflow 2.x models
  • Changed default type of base python docker image to "slim"
  • Added 'description' and 'params' fields to Model. 'description' is a text field and 'params' is a dict with arbitrary keys
  • Fixed bug with building docker image with different python version that the Model was created with

0.3.5 (2020-01-31)

  • Fixed critical bug with wrapper_meta

0.3.4 (2020-01-31)

  • Fixed bug with deleting models from tasks
  • Support working with model meta without requiring installation of all model dependencies
  • Added region argument for s3 repository
  • Support for delete_model in Ebonite client
  • Support for force flag in delete_model which deletes model even if artifacts could not be deleted

0.3.3 (2020-01-10)

  • Eliminated tensorflow warnings. Added more tests for providers/loaders. Fixed bugs in multi-model provider/builder.
  • Improved documentation
  • Eliminate useless "which docker" check which fails on Windows hosts
  • Perform redirect from / to Swagger API docs in Flask server
  • Support for predict_proba method in ML model
  • Do not fix first dimension size for numpy arrays and torch tensors
  • Support for Pytorch JIT (TorchScript) models
  • Bump tensorflow from 1.14.0 to 1.15.0
  • Added more tests

0.3.2 (2019-12-04)

  • Multi-model interface bug fixes

0.3.1 (2019-12-04)

  • Minor bug fixes

0.3.0 (2019-11-27)

  • Added support for LightGBM models
  • Added support for XGBoost models
  • Added support for PyTorch models
  • Added support for CatBoost models
  • Added uwsgi server for flask containers

0.2.1 (2019-11-19)

  • Minor bug fixes

0.2.0 (2019-11-14)

  • First release on PyPI.