C API: General Tree Inference Library (GTIL)

Functions
int	TreeliteGTILParseConfig (char const *config_json, TreeliteGTILConfigHandle *out)
	Load a configuration for GTIL predictor from a JSON string. More...
int	TreeliteGTILDeleteConfig (TreeliteGTILConfigHandle handle)
	Delete a GTIL configuration from memory. More...
int	TreeliteGTILGetOutputShape (TreeliteModelHandle model, uint64_t num_row, TreeliteGTILConfigHandle config, uint64_t const **out, uint64_t *out_ndim)
	Given a data matrix, query the necessary shape of array to hold predictions for all data points. More...
int	TreeliteGTILPredict (TreeliteModelHandle model, void const *input, char const *input_type, uint64_t num_row, void *output, TreeliteGTILConfigHandle config)
	Predict with a 2D dense array. More...
int	TreeliteGTILPredictSparse (TreeliteModelHandle model, void const *data, char const *input_type, uint64_t const *col_ind, uint64_t const *row_ptr, uint64_t num_row, void *output, TreeliteGTILConfigHandle config)
	Predict with sparse data with CSR (compressed sparse row) layout. More...

Detailed Description

GTIL provides a reference implementation for predicting with decision trees.

Function Documentation

TreeliteGTILDeleteConfig()

int TreeliteGTILDeleteConfig

(

TreeliteGTILConfigHandle

handle

)

Delete a GTIL configuration from memory.

Parameters

handle

Handle to the GTIL configuration to be deleted

Returns

0 for success; -1 for failure

TreeliteGTILGetOutputShape()

int TreeliteGTILGetOutputShape	(	TreeliteModelHandle	model,
		uint64_t	num_row,
		TreeliteGTILConfigHandle	config,
		uint64_t const **	out,
		uint64_t *	out_ndim
	)

Given a data matrix, query the necessary shape of array to hold predictions for all data points.

Parameters

model	Treelite Model object
num_row	Number of rows in the input
config	Configuration of GTIL predictor. Set this by calling TreeliteGTILParseConfig.
out_shape	Array of dimensions
out_ndim	Number of dimensions in out_shape

Returns

0 for success; -1 for failure

TreeliteGTILParseConfig()

int TreeliteGTILParseConfig	(	char const *	config_json,
		TreeliteGTILConfigHandle *	out
	)

Load a configuration for GTIL predictor from a JSON string.

Parameters

config_json

a JSON string with the following fields: "nthread" (optional): Number of threads used for initializing DMatrix. Set <= 0 to use all CPU cores. "predict_type" (required): Must be one of the following. "default": Sum over trees and apply post-processing "raw": Sum over trees, but don't apply post-processing; get raw margin scores instead. "leaf_id": Output one (integer) leaf ID per tree. "score_per_tree": Output one or more margin scores per tree.

out

Parsed configuration

Returns

0 for success; -1 for failure

TreeliteGTILPredict()

int TreeliteGTILPredict	(	TreeliteModelHandle	model,
		void const *	input,
		char const *	input_type,
		uint64_t	num_row,
		void *	output,
		TreeliteGTILConfigHandle	config
	)

Predict with a 2D dense array.

Parameters

model	Treelite Model object
input	The 2D data array, laid out in row-major layout
input_type	Data type of the data matrix
num_row	Number of rows in the data matrix.
output	Pointer to buffer to store the output. Call TreeliteGTILGetOutputShape to get the amount of buffer you should allocate for this parameter.
config	Configuration of GTIL predictor. Set this by calling TreeliteGTILParseConfig.

Returns

0 for success; -1 for failure

TreeliteGTILPredictSparse()

int TreeliteGTILPredictSparse	(	TreeliteModelHandle	model,
		void const *	data,
		char const *	input_type,
		uint64_t const *	col_ind,
		uint64_t const *	row_ptr,
		uint64_t	num_row,
		void *	output,
		TreeliteGTILConfigHandle	config
	)

Predict with sparse data with CSR (compressed sparse row) layout.

In the CSR layout, data[row_ptr[i]:row_ptr[i+1]] store the nonzero entries of row i, and col_ind[row_ptr[i]:row_ptr[i+1]] stores the corresponding column indices.

Parameters

model	Treelite Model object
data	Nonzero elements in the data matrix
input_type	Data type of the data matrix
col_ind	Feature indices. col_ind[i] indicates the feature index associated with data[i].
row_ptr	Pointer to row headers. Length is [num_row] + 1.
num_row	Number of rows in the data matrix.
output	Pointer to buffer to store the output. Call GetOutputShape to get the amount of buffer you should allocate for this parameter.
config	Configuration of GTIL predictor. Set this by calling TreeliteGTILParseConfig.

Returns

0 for success; -1 for failure