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Merge pull request #5749 from Param-29/redblack-v1
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packages/syft/examples/experimental/redblack/param/scripts/package_support.json
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| { | ||
| "class": [ | ||
| "xgboost.plotting.XGBModel", | ||
| "xgboost.sklearn.DMatrix", | ||
| "xgboost.libpath.XGBoostLibraryNotFound", | ||
| "xgboost.compat.LazyLoader", | ||
| "xgboost.dask.DaskXGBRanker", | ||
| "xgboost.dask.DeviceQuantileDMatrix", | ||
| "xgboost.tracker.ExSocket", | ||
| "xgboost.training._PackedBooster", | ||
| "xgboost.dask.LazyLoader", | ||
| "xgboost.callback.TrainingCallback", | ||
| "xgboost.core.DataIter", | ||
| "xgboost.dask.TrainReturnT", | ||
| "xgboost.sklearn.XGBoostError", | ||
| "xgboost.training.Booster", | ||
| "xgboost.core.Booster", | ||
| "xgboost.callback.XGBoostError", | ||
| "xgboost.training.XGBoostError", | ||
| "xgboost.dask.DaskDMatrix", | ||
| "xgboost.dask.XGBRanker", | ||
| "xgboost.dask.DMatrix", | ||
| "xgboost.data._ProxyDMatrix", | ||
| "xgboost.dask.DaskXGBRFRegressor", | ||
| "xgboost.plotting.Booster", | ||
| "xgboost.core.XGBoostError", | ||
| "xgboost.callback.LegacyCallbacks", | ||
| "xgboost.callback.EarlyStopping", | ||
| "xgboost.core.DeviceQuantileDMatrix", | ||
| "xgboost.callback.LearningRateScheduler", | ||
| "xgboost.sklearn.XGBRFRegressor", | ||
| "xgboost.core.EarlyStopException", | ||
| "xgboost.training.CVPack", | ||
| "xgboost.data.DMatrix", | ||
| "xgboost.core._ProxyDMatrix", | ||
| "xgboost.dask.DataIter", | ||
| "xgboost.dask.DaskDeviceQuantileDMatrix", | ||
| "xgboost.sklearn.XGBRankerMixIn", | ||
| "xgboost.core.CallbackEnv", | ||
| "xgboost.sklearn.XGBRanker", | ||
| "xgboost.callback.CallbackEnv", | ||
| "xgboost.dask.DaskXGBClassifier", | ||
| "xgboost.dask.XGBRankerMixIn", | ||
| "xgboost.dask.XGBModel", | ||
| "xgboost.data.SingleBatchInternalIter", | ||
| "xgboost.dask.Booster", | ||
| "xgboost.sklearn.XGBRFClassifier", | ||
| "xgboost.dask.DaskXGBRegressor", | ||
| "xgboost.callback.TrainingCheckPoint", | ||
| "xgboost.callback.Booster", | ||
| "xgboost.dask.DaskXGBRFClassifier", | ||
| "xgboost.sklearn.XGBoostLabelEncoder", | ||
| "xgboost.callback.EvaluationMonitor", | ||
| "xgboost.dask.TrainingCallback", | ||
| "xgboost.sklearn.Booster", | ||
| "xgboost.sklearn.XGBModel", | ||
| "xgboost.sklearn.XGBRegressor", | ||
| "xgboost.callback.CallbackContainer", | ||
| "xgboost.tracker.RabitTracker", | ||
| "xgboost.tracker.SlaveEntry", | ||
| "xgboost.core.DMatrix", | ||
| "xgboost.dask.DaskPartitionIter", | ||
| "xgboost.dask.DaskScikitLearnBase", | ||
| "xgboost.dask.RabitTracker", | ||
| "xgboost.data.DataIter", | ||
| "xgboost.callback.EarlyStopException", | ||
| "xgboost.dask.RabitContext", | ||
| "xgboost.dask.XGBClassifier", | ||
| "xgboost.compat.XGBoostLabelEncoder", | ||
| "xgboost.sklearn.XGBClassifier", | ||
| "xgboost.rabit.Op" | ||
| ], | ||
| "modules": [ | ||
| "xgboost.callback", | ||
| "xgboost.compat", | ||
| "xgboost.config", | ||
| "xgboost.core", | ||
| "xgboost.dask", | ||
| "xgboost.data", | ||
| "xgboost.libpath", | ||
| "xgboost.plotting", | ||
| "xgboost.rabit", | ||
| "xgboost.sklearn", | ||
| "xgboost.tracker", | ||
| "xgboost.training" | ||
| ], | ||
| "methods": { | ||
| "xgboost.callback.CallbackContainer.before_iteration": "bool", | ||
| "xgboost.dask.DaskScikitLearnBase._set_evaluation_result": "NoneType", | ||
| "xgboost.dask.XGBModel._can_use_inplace_predict": "bool", | ||
| "xgboost.sklearn.XGBRFClassifier._configure_fit": "tuple", | ||
| "xgboost.dask.DaskDMatrix.__init__": "NoneType", | ||
| "xgboost.dask.XGBRanker._set_evaluation_result": "NoneType", | ||
| "xgboost.dask.DaskXGBRegressor._set_evaluation_result": "NoneType", | ||
| "xgboost.sklearn.XGBRanker._set_evaluation_result": "NoneType", | ||
| "xgboost.training.Booster.predict": "numpy.ndarray", | ||
| "xgboost.dask.XGBRanker._get_type": "str", | ||
| "xgboost.sklearn.XGBRFRegressor.apply": "numpy.ndarray", | ||
| "xgboost.sklearn.XGBModel.apply": "numpy.ndarray", | ||
| "xgboost.dask.DaskXGBRanker._get_type": "str", | ||
| "xgboost.sklearn.XGBRanker.apply": "numpy.ndarray", | ||
| "xgboost.dask.DaskXGBRFRegressor._set_evaluation_result": "NoneType", | ||
| "xgboost.dask.DaskDMatrix._map_local_data": "xgboost.dask.DaskDMatrix", | ||
| "xgboost.sklearn.Booster.num_boosted_rounds": "int", | ||
| "xgboost.training.Booster.num_features": "int", | ||
| "xgboost.sklearn.XGBRFClassifier.apply": "numpy.ndarray", | ||
| "xgboost.callback.TrainingCheckPoint.after_iteration": "bool", | ||
| "xgboost.sklearn.XGBModel._can_use_inplace_predict": "bool", | ||
| "xgboost.callback.EarlyStopping.before_iteration": "bool", | ||
| "xgboost.sklearn.XGBRFClassifier._get_type": "str", | ||
| "xgboost.callback.LearningRateScheduler.after_iteration": "bool", | ||
| "xgboost.dask.DaskDMatrix.__await__": "Generator", | ||
| "xgboost.dask.DaskXGBClassifier._fit_async": "xgboost.dask.DaskXGBClassifier", | ||
| "xgboost.dask.DaskXGBRFRegressor.__getstate__": "dict", | ||
| "xgboost.dask.XGBModel._configure_fit": "tuple", | ||
| "xgboost.core.DMatrix.__init__": "NoneType", | ||
| "xgboost.dask.DaskPartitionIter.__init__": "NoneType", | ||
| "xgboost.dask.DaskXGBRanker._fit_async": "xgboost.dask.DaskXGBRanker", | ||
| "xgboost.sklearn.XGBRFClassifier._get_iteration_range": "tuple", | ||
| "xgboost.dask.DaskXGBClassifier._get_type": "str", | ||
| "xgboost.dask.DaskXGBRanker._get_iteration_range": "tuple", | ||
| "xgboost.dask.DaskXGBRegressor._configure_fit": "tuple", | ||
| "xgboost.sklearn.XGBRanker.fit": "xgboost.sklearn.XGBRanker", | ||
| "xgboost.plotting.XGBModel.apply": "numpy.ndarray", | ||
| "xgboost.dask.XGBClassifier._configure_fit": "tuple", | ||
| "xgboost.dask.DaskXGBClassifier.__getstate__": "dict", | ||
| "xgboost.dask.DaskXGBRFRegressor._configure_fit": "tuple", | ||
| "xgboost.dask.DaskXGBRanker._configure_fit": "tuple", | ||
| "xgboost.plotting.XGBModel._can_use_inplace_predict": "bool", | ||
| "xgboost.dask.DaskDeviceQuantileDMatrix._map_local_data": "xgboost.dask.DaskDMatrix", | ||
| "xgboost.core.Booster.predict": "numpy.ndarray", | ||
| "xgboost.core._ProxyDMatrix.set_info": "NoneType", | ||
| "xgboost.sklearn.XGBRegressor.apply": "numpy.ndarray", | ||
| "xgboost.dask.DaskXGBRFClassifier.get_num_boosting_rounds": "int", | ||
| "xgboost.training._PackedBooster.__init__": "NoneType", | ||
| "xgboost.core.Booster._set_feature_info": "NoneType", | ||
| "xgboost.dask.XGBRanker.fit": "xgboost.sklearn.XGBRanker", | ||
| "xgboost.dask.XGBRanker._can_use_inplace_predict": "bool", | ||
| "xgboost.callback.LearningRateScheduler.__init__": "NoneType", | ||
| "xgboost.dask.Booster.num_boosted_rounds": "int", | ||
| "xgboost.dask.XGBRanker.apply": "numpy.ndarray", | ||
| "xgboost.dask.DaskXGBRanker.__await__": "Awaitable", | ||
| "xgboost.sklearn.XGBRFRegressor._get_iteration_range": "tuple", | ||
| "xgboost.dask.DaskXGBRFRegressor.get_xgb_params": "dict", | ||
| "xgboost.training.Booster._set_feature_info": "NoneType", | ||
| "xgboost.sklearn.XGBRFRegressor._set_evaluation_result": "NoneType", | ||
| "xgboost.core.DMatrix.slice": "xgboost.core.DMatrix", | ||
| "xgboost.core.DeviceQuantileDMatrix.set_info": "NoneType", | ||
| "xgboost.dask.DaskXGBRegressor.__getstate__": "dict", | ||
| "xgboost.dask.DeviceQuantileDMatrix.set_info": "NoneType", | ||
| "xgboost.dask.RabitContext.__init__": "NoneType", | ||
| "xgboost.dask.DaskDMatrix._create_fn_args": "dict", | ||
| "xgboost.dask.DaskDeviceQuantileDMatrix.__await__": "Generator", | ||
| "xgboost.dask.DeviceQuantileDMatrix.slice": "xgboost.core.DMatrix", | ||
| "xgboost.dask.XGBClassifier.apply": "numpy.ndarray", | ||
| "xgboost.sklearn.DMatrix.slice": "xgboost.core.DMatrix", | ||
| "xgboost.sklearn.XGBRanker._can_use_inplace_predict": "bool", | ||
| "xgboost.sklearn.Booster.predict": "numpy.ndarray", | ||
| "xgboost.sklearn.XGBClassifier._get_iteration_range": "tuple", | ||
| "xgboost.dask.DaskScikitLearnBase._get_type": "str", | ||
| "xgboost.callback.Booster.predict": "numpy.ndarray", | ||
| "xgboost.dask.DMatrix.slice": "xgboost.core.DMatrix", | ||
| "xgboost.dask.DaskDMatrix.num_col": "int", | ||
| "xgboost.sklearn.XGBRegressor._get_iteration_range": "tuple", | ||
| "xgboost.sklearn.XGBClassifier._set_evaluation_result": "NoneType", | ||
| "xgboost.dask.DaskXGBRFRegressor._get_iteration_range": "tuple", | ||
| "xgboost.dask.Booster.num_features": "int", | ||
| "xgboost.dask.XGBModel._get_type": "str", | ||
| "xgboost.dask.DaskXGBRegressor._get_iteration_range": "tuple", | ||
| "xgboost.core.DeviceQuantileDMatrix.slice": "xgboost.core.DMatrix", | ||
| "xgboost.callback.TrainingCallback.after_iteration": "bool", | ||
| "xgboost.callback.EvaluationMonitor.before_iteration": "bool", | ||
| "xgboost.sklearn.XGBRFClassifier.predict_proba": "numpy.ndarray", | ||
| "xgboost.sklearn.XGBRFRegressor._get_type": "str", | ||
| "xgboost.callback.TrainingCheckPoint.before_iteration": "bool", | ||
| "xgboost.training.Booster.num_boosted_rounds": "int", | ||
| "xgboost.sklearn.XGBRFClassifier._set_evaluation_result": "NoneType", | ||
| "xgboost.dask.DaskXGBRegressor._get_type": "str", | ||
| "xgboost.dask.XGBClassifier._get_type": "str", | ||
| "xgboost.dask.DaskXGBRFClassifier.fit": "xgboost.dask.DaskXGBClassifier", | ||
| "xgboost.callback.Booster._set_feature_info": "NoneType", | ||
| "xgboost.sklearn.XGBModel._get_iteration_range": "tuple", | ||
| "xgboost.callback.EarlyStopping._update_rounds": "bool", | ||
| "xgboost.core.DMatrix.set_info": "NoneType", | ||
| "xgboost.dask.DaskXGBRegressor.fit": "xgboost.dask.DaskXGBRegressor", | ||
| "xgboost.sklearn.XGBRegressor._can_use_inplace_predict": "bool", | ||
| "xgboost.dask.DaskXGBRFClassifier._get_type": "str", | ||
| "xgboost.callback.LearningRateScheduler.before_iteration": "bool", | ||
| "xgboost.sklearn.XGBModel._set_evaluation_result": "NoneType", | ||
| "xgboost.callback.EvaluationMonitor.__init__": "NoneType", | ||
| "xgboost.dask.XGBRanker._configure_fit": "tuple", | ||
| "xgboost.dask.RabitContext.__exit__": "NoneType", | ||
| "xgboost.dask.DaskXGBClassifier._can_use_inplace_predict": "bool", | ||
| "xgboost.callback.EarlyStopping.after_iteration": "bool", | ||
| "xgboost.dask.DaskXGBRFClassifier._get_iteration_range": "tuple", | ||
| "xgboost.dask.DaskScikitLearnBase.__await__": "Awaitable", | ||
| "xgboost.dask.DaskXGBRFRegressor.__await__": "Awaitable", | ||
| "xgboost.dask.DaskXGBRanker.fit": "xgboost.dask.DaskXGBRanker", | ||
| "xgboost.plotting.Booster.predict": "numpy.ndarray", | ||
| "xgboost.dask.DaskXGBRFRegressor._can_use_inplace_predict": "bool", | ||
| "xgboost.callback.EvaluationMonitor.after_iteration": "bool", | ||
| "xgboost.dask.DaskXGBRFRegressor.get_num_boosting_rounds": "int", | ||
| "xgboost.dask.DMatrix.__init__": "NoneType", | ||
| "xgboost.core._ProxyDMatrix.slice": "xgboost.core.DMatrix", | ||
| "xgboost.dask.DaskXGBRFClassifier.__await__": "Awaitable", | ||
| "xgboost.dask.XGBModel._get_iteration_range": "tuple", | ||
| "xgboost.callback.Booster.num_boosted_rounds": "int", | ||
| "xgboost.sklearn.Booster.num_features": "int", | ||
| "xgboost.sklearn.XGBClassifier.predict_proba": "numpy.ndarray", | ||
| "xgboost.plotting.Booster.num_boosted_rounds": "int", | ||
| "xgboost.dask.XGBClassifier.predict_proba": "numpy.ndarray", | ||
| "xgboost.dask.DaskXGBRFClassifier.get_xgb_params": "dict", | ||
| "xgboost.callback.EarlyStopping.__init__": "NoneType", | ||
| "xgboost.dask.DaskScikitLearnBase.__getstate__": "dict", | ||
| "xgboost.dask.DaskXGBRegressor._can_use_inplace_predict": "bool", | ||
| "xgboost.dask.TrainingCallback.after_iteration": "bool", | ||
| "xgboost.dask.DaskXGBRFClassifier._can_use_inplace_predict": "bool", | ||
| "xgboost.plotting.XGBModel._get_iteration_range": "tuple", | ||
| "xgboost.data.DMatrix.set_info": "NoneType", | ||
| "xgboost.dask.DaskXGBClassifier._get_iteration_range": "tuple", | ||
| "xgboost.dask.DaskXGBRFRegressor.fit": "xgboost.dask.DaskXGBRegressor", | ||
| "xgboost.dask.DaskXGBRFClassifier.__getstate__": "dict", | ||
| "xgboost.dask.DaskXGBClassifier.fit": "xgboost.dask.DaskXGBClassifier", | ||
| "xgboost.dask.RabitContext.__enter__": "NoneType", | ||
| "xgboost.dask.TrainingCallback.before_iteration": "bool", | ||
| "xgboost.dask.DaskXGBRFClassifier._configure_fit": "tuple", | ||
| "xgboost.sklearn.XGBClassifier._configure_fit": "tuple", | ||
| "xgboost.data._ProxyDMatrix.set_info": "NoneType", | ||
| "xgboost.dask.DaskXGBClassifier._configure_fit": "tuple", | ||
| "xgboost.dask.DaskScikitLearnBase._configure_fit": "tuple", | ||
| "xgboost.sklearn.XGBModel._configure_fit": "tuple", | ||
| "xgboost.dask.DaskXGBRanker._can_use_inplace_predict": "bool", | ||
| "xgboost.core.Booster.num_boosted_rounds": "int", | ||
| "xgboost.core.Booster.num_features": "int", | ||
| "xgboost.sklearn.XGBRegressor._set_evaluation_result": "NoneType", | ||
| "xgboost.sklearn.DMatrix.__init__": "NoneType", | ||
| "xgboost.sklearn.XGBRFClassifier._can_use_inplace_predict": "bool", | ||
| "xgboost.plotting.XGBModel._set_evaluation_result": "NoneType", | ||
| "xgboost.dask.DaskPartitionIter.reset": "NoneType", | ||
| "xgboost.sklearn.XGBRFRegressor._can_use_inplace_predict": "bool", | ||
| "xgboost.dask.DaskXGBRFRegressor.__init__": "NoneType", | ||
| "xgboost.dask.DaskXGBRFRegressor._get_type": "str", | ||
| "xgboost.plotting.XGBModel._get_type": "str", | ||
| "xgboost.dask.XGBClassifier._get_iteration_range": "tuple", | ||
| "xgboost.data._ProxyDMatrix.slice": "xgboost.core.DMatrix", | ||
| "xgboost.dask.Booster.predict": "numpy.ndarray", | ||
| "xgboost.dask.DaskDeviceQuantileDMatrix._create_fn_args": "dict", | ||
| "xgboost.dask.DaskXGBRanker.__getstate__": "dict", | ||
| "xgboost.dask.DaskScikitLearnBase._get_iteration_range": "tuple", | ||
| "xgboost.dask.XGBClassifier._can_use_inplace_predict": "bool", | ||
| "xgboost.sklearn.Booster._set_feature_info": "NoneType", | ||
| "xgboost.sklearn.XGBClassifier._get_type": "str", | ||
| "xgboost.dask.DaskXGBClassifier._set_evaluation_result": "NoneType", | ||
| "xgboost.dask.XGBModel.apply": "numpy.ndarray", | ||
| "xgboost.sklearn.DMatrix.set_info": "NoneType", | ||
| "xgboost.data.DMatrix.__init__": "NoneType", | ||
| "xgboost.callback.TrainingCallback.before_iteration": "bool", | ||
| "xgboost.callback.Booster.num_features": "int", | ||
| "xgboost.dask.DaskXGBRFClassifier._set_evaluation_result": "NoneType", | ||
| "xgboost.callback.EvaluationMonitor._fmt_metric": "str", | ||
| "xgboost.dask.DaskScikitLearnBase._can_use_inplace_predict": "bool", | ||
| "xgboost.dask.DaskXGBClassifier.__await__": "Awaitable", | ||
| "xgboost.sklearn.XGBRegressor._get_type": "str", | ||
| "xgboost.plotting.XGBModel._configure_fit": "tuple", | ||
| "xgboost.dask.DaskXGBRanker._set_evaluation_result": "NoneType", | ||
| "xgboost.callback.CallbackContainer.after_iteration": "bool", | ||
| "xgboost.dask.DaskXGBRFClassifier._fit_async": "xgboost.dask.DaskXGBClassifier", | ||
| "xgboost.dask.XGBClassifier._set_evaluation_result": "NoneType", | ||
| "xgboost.sklearn.XGBRegressor._configure_fit": "tuple", | ||
| "xgboost.dask.DaskXGBRegressor.__await__": "Awaitable", | ||
| "xgboost.dask.XGBModel._set_evaluation_result": "NoneType", | ||
| "xgboost.sklearn.XGBRanker._configure_fit": "tuple", | ||
| "xgboost.dask.XGBRanker._get_iteration_range": "tuple", | ||
| "xgboost.sklearn.XGBClassifier.apply": "numpy.ndarray", | ||
| "xgboost.dask.Booster._set_feature_info": "NoneType", | ||
| "xgboost.dask.DaskDeviceQuantileDMatrix.__init__": "NoneType", | ||
| "xgboost.data.DMatrix.slice": "xgboost.core.DMatrix", | ||
| "xgboost.sklearn.XGBRanker._get_iteration_range": "tuple", | ||
| "xgboost.dask.DaskPartitionIter.next": "int", | ||
| "xgboost.sklearn.XGBModel._get_type": "str", | ||
| "xgboost.plotting.Booster._set_feature_info": "NoneType", | ||
| "xgboost.dask.DMatrix.set_info": "NoneType", | ||
| "xgboost.sklearn.XGBRFRegressor._configure_fit": "tuple", | ||
| "xgboost.sklearn.XGBClassifier._can_use_inplace_predict": "bool", | ||
| "xgboost.dask.DaskXGBRFClassifier.__init__": "NoneType", | ||
| "xgboost.sklearn.XGBRanker._get_type": "str", | ||
| "xgboost.dask.DaskDeviceQuantileDMatrix.num_col": "int", | ||
| "xgboost.plotting.Booster.num_features": "int" | ||
| }, | ||
| "lib": "xgboost" | ||
| } |
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