Ebonite

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* 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

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* Fixed critical bug with wrapper_meta

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* 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

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* 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

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* Multi-model interface bug fixes

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* Minor bug fixes