module `onnxrt.ops_cpu.op_tree_ensemble_regressor_`#

Short summary#

module mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_

Implements runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc in onnxruntime.

source on GitHub

Classes#

class	truncated documentation
`RuntimeTreeEnsembleRegressorDouble`	Implements double runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc …
`RuntimeTreeEnsembleRegressorFloat`	Implements float runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc …

Properties#

property	truncated documentation
`base_values_`	See lpyort-TreeEnsembleRegressorDouble.
`base_values_`	See lpyort-TreeEnsembleRegressor.
`consecutive_leaf_data_`	Tells if there are two consecutive targets sharing the same node and the same tree (it should not happen in 1D target).
`consecutive_leaf_data_`	Tells if there are two consecutive targets sharing the same node and the same tree (it should not happen in 1D target).
`missing_tracks_true_`	See lpyort-TreeEnsembleRegressorDouble.
`missing_tracks_true_`	See lpyort-TreeEnsembleRegressor.
`n_targets_`	See lpyort-TreeEnsembleRegressorDouble.
`n_targets_`	See lpyort-TreeEnsembleRegressor.
`nodes_falsenodeids_`	See lpyort-TreeEnsembleRegressorDouble.
`nodes_falsenodeids_`	See lpyort-TreeEnsembleRegressor.
`nodes_featureids_`	See lpyort-TreeEnsembleRegressorDouble.
`nodes_featureids_`	See lpyort-TreeEnsembleRegressor.
`nodes_hitrates_`	See lpyort-TreeEnsembleRegressorDouble.
`nodes_hitrates_`	See lpyort-TreeEnsembleRegressor.
`nodes_modes_`
`nodes_modes_`
`nodes_nodeids_`	See lpyort-TreeEnsembleRegressorDouble.
`nodes_nodeids_`	See lpyort-TreeEnsembleRegressor.
`nodes_treeids_`	See lpyort-TreeEnsembleRegressorDouble.
`nodes_treeids_`	See lpyort-TreeEnsembleRegressor.
`nodes_truenodeids_`	See lpyort-TreeEnsembleRegressorDouble.
`nodes_truenodeids_`	See lpyort-TreeEnsembleRegressor.
`nodes_values_`	See lpyort-TreeEnsembleRegressorDouble.
`nodes_values_`	See lpyort-TreeEnsembleRegressor.
`post_transform_`	See lpyort-TreeEnsembleRegressorDouble.
`post_transform_`	See lpyort-TreeEnsembleRegressor.
`roots_`	Returns the roots indices.
`roots_`	Returns the roots indices.
`same_mode_`	Tells if all nodes applies the same rule for thresholds.
`same_mode_`	Tells if all nodes applies the same rule for thresholds.
`target_ids_`	See lpyort-TreeEnsembleRegressorDouble.
`target_ids_`	See lpyort-TreeEnsembleRegressor.
`target_nodeids_`	See lpyort-TreeEnsembleRegressorDouble.
`target_nodeids_`	See lpyort-TreeEnsembleRegressor.
`target_treeids_`	See lpyort-TreeEnsembleRegressorDouble.
`target_treeids_`	See lpyort-TreeEnsembleRegressor.
`target_weights_`	See lpyort-TreeEnsembleRegressorDouble.
`target_weights_`	See lpyort-TreeEnsembleRegressor.

Documentation#

Implements runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc in onnxruntime.

class mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorDouble(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorDouble)#

Bases: pybind11_object

Implements double runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc in onnxruntime. Supports double only.

__init__(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorDouble) → None#

property base_values_#: See lpyort-TreeEnsembleRegressorDouble.

compute(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorDouble, arg0: numpy.ndarray[numpy.float64]) → numpy.ndarray[numpy.float64]#: Computes the predictions for the random forest.

compute_tree_outputs(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorDouble, arg0: numpy.ndarray[numpy.float64]) → numpy.ndarray[numpy.float64]#: Computes every tree output.

property consecutive_leaf_data_#: Tells if there are two consecutive targets sharing the same node and the same tree (it should not happen in 1D target).

debug_threshold(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorDouble, arg0: numpy.ndarray[numpy.float64]) → numpy.ndarray[numpy.int32]#: Checks every features against every features against every threshold. Returns a matrix of boolean.

init(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorDouble, arg0: str, arg1: numpy.ndarray[numpy.float64], arg2: int, arg3: numpy.ndarray[numpy.int64], arg4: numpy.ndarray[numpy.int64], arg5: numpy.ndarray[numpy.float64], arg6: numpy.ndarray[numpy.int64], arg7: List[str], arg8: numpy.ndarray[numpy.int64], arg9: numpy.ndarray[numpy.int64], arg10: numpy.ndarray[numpy.int64], arg11: numpy.ndarray[numpy.float64], arg12: str, arg13: numpy.ndarray[numpy.int64], arg14: numpy.ndarray[numpy.int64], arg15: numpy.ndarray[numpy.int64], arg16: numpy.ndarray[numpy.float64]) → None#: Initializes the runtime with the ONNX attributes in alphabetical order.

property missing_tracks_true_#: See lpyort-TreeEnsembleRegressorDouble.

property n_targets_#: See lpyort-TreeEnsembleRegressorDouble.

property nodes_falsenodeids_#: See lpyort-TreeEnsembleRegressorDouble.

property nodes_featureids_#: See lpyort-TreeEnsembleRegressorDouble.

property nodes_hitrates_#: See lpyort-TreeEnsembleRegressorDouble.

property nodes_nodeids_#: See lpyort-TreeEnsembleRegressorDouble.

property nodes_treeids_#: See lpyort-TreeEnsembleRegressorDouble.

property nodes_truenodeids_#: See lpyort-TreeEnsembleRegressorDouble.

property nodes_values_#: See lpyort-TreeEnsembleRegressorDouble.

omp_get_max_threads(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorDouble) → int#: Returns omp_get_max_threads from openmp library.

property post_transform_#: See lpyort-TreeEnsembleRegressorDouble.

property roots_#: Returns the roots indices.

runtime_options(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorDouble) → str#: Returns indications about how the runtime was compiled.

property same_mode_#: Tells if all nodes applies the same rule for thresholds.

property target_ids_#: See lpyort-TreeEnsembleRegressorDouble.

property target_nodeids_#: See lpyort-TreeEnsembleRegressorDouble.

property target_treeids_#: See lpyort-TreeEnsembleRegressorDouble.

property target_weights_#: See lpyort-TreeEnsembleRegressorDouble.

class mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorFloat(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_regressor_.RuntimeTreeEnsembleRegressorFloat)#