Onnxmltools

LightGBM

* Improves lightgbm conversion speed 491
* Fix discovering classifier objective 480
* Fix missing type in lgbm regressor 488
* Support gamma objective in LGBMRegressor 484
* Allow to add custom post transform functions that are not supported by the ONNX spec yet 463
* Enable option zipmap for LGBM converter 452

XGBoost

* Use all tree when best_ntree_limit is not specified 459
* Fix discrepencies when xgboost trees are empty 447

Keras

* Switch to tf2onnx for tensorflow>=2.0 instead of keras2onnx 492

New features

* New converters for CatBoost 392
* Integration with Hummingbird 404, 418, 427
* Support for opset 13 437

XGBoost

* Support float type for feature_id 423
* Support unsigned integer as class type 426
* Fix the converter when the parameter best_ntree_limit is used 429
* Support multi:softmax objective 442

CoreML

* Extend CoreML: ReshapeStatic/LoadConstantND 430
* Fix PReLU conversion from CoreML 425

2. Work with the new xgboost version
3. Remove Python 2.x support

Details:
Add the flake8 to be the default code formatter (401)
Fixes 396, xgboost converter for xgboost >= 1.0.2 (397)
Support onnx 1.7 in CI build (398)
fixed the xgboost version (395)
fix ceiling-mode defaults for pool operators (AvgPool, MaxPool) (388)
Update documentation, add examples (385)
Remove support of python 2.7 (383)
upgrade to 1.7 (384)
Fix for onnx 1.7 release (381)
Ping h2o version==3.28.0.3 (377)
Fix xgboost converter (373)
xgboost not supporting 1.0 version. (372)

Known issues:
onnxmltools tf2onnx wrapper can only work with tf2onnx <= 1.5.6.

The major update for this release

The major updates of this release.
1. Add a new converter for H2O GBM MOJO
2. add tf2onnx wrapper with a onnxmltools converter style API.
3. Some bug fixing for the existing converters.

Support opset 11