* Add Python iterator interface. * Add tests. * Add demo. * Add documents. * Handle empty dataset.
174 lines
6.0 KiB
C
174 lines
6.0 KiB
C
/*!
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* Copyright 2019 XGBoost contributors
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*
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* \file c-api-demo.c
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* \brief A simple example of using xgboost C API.
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*/
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#include <assert.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <xgboost/c_api.h>
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#define safe_xgboost(call) { \
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int err = (call); \
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if (err != 0) { \
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fprintf(stderr, "%s:%d: error in %s: %s\n", __FILE__, __LINE__, #call, XGBGetLastError()); \
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exit(1); \
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} \
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}
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int main(int argc, char** argv) {
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int silent = 0;
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int use_gpu = 0; // set to 1 to use the GPU for training
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// load the data
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DMatrixHandle dtrain, dtest;
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safe_xgboost(XGDMatrixCreateFromFile("../../data/agaricus.txt.train", silent, &dtrain));
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safe_xgboost(XGDMatrixCreateFromFile("../../data/agaricus.txt.test", silent, &dtest));
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// create the booster
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BoosterHandle booster;
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DMatrixHandle eval_dmats[2] = {dtrain, dtest};
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safe_xgboost(XGBoosterCreate(eval_dmats, 2, &booster));
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// configure the training
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// available parameters are described here:
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// https://xgboost.readthedocs.io/en/latest/parameter.html
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safe_xgboost(XGBoosterSetParam(booster, "tree_method", use_gpu ? "gpu_hist" : "hist"));
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if (use_gpu) {
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// set the GPU to use;
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// this is not necessary, but provided here as an illustration
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safe_xgboost(XGBoosterSetParam(booster, "gpu_id", "0"));
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} else {
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// avoid evaluating objective and metric on a GPU
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safe_xgboost(XGBoosterSetParam(booster, "gpu_id", "-1"));
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}
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safe_xgboost(XGBoosterSetParam(booster, "objective", "binary:logistic"));
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safe_xgboost(XGBoosterSetParam(booster, "min_child_weight", "1"));
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safe_xgboost(XGBoosterSetParam(booster, "gamma", "0.1"));
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safe_xgboost(XGBoosterSetParam(booster, "max_depth", "3"));
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safe_xgboost(XGBoosterSetParam(booster, "verbosity", silent ? "0" : "1"));
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// train and evaluate for 10 iterations
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int n_trees = 10;
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const char* eval_names[2] = {"train", "test"};
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const char* eval_result = NULL;
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for (int i = 0; i < n_trees; ++i) {
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safe_xgboost(XGBoosterUpdateOneIter(booster, i, dtrain));
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safe_xgboost(XGBoosterEvalOneIter(booster, i, eval_dmats, eval_names, 2, &eval_result));
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printf("%s\n", eval_result);
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}
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bst_ulong num_feature = 0;
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safe_xgboost(XGBoosterGetNumFeature(booster, &num_feature));
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printf("num_feature: %lu\n", (unsigned long)(num_feature));
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// predict
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bst_ulong out_len = 0;
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const float* out_result = NULL;
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int n_print = 10;
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safe_xgboost(XGBoosterPredict(booster, dtest, 0, 0, 0, &out_len, &out_result));
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printf("y_pred: ");
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for (int i = 0; i < n_print; ++i) {
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printf("%1.4f ", out_result[i]);
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}
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printf("\n");
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// print true labels
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safe_xgboost(XGDMatrixGetFloatInfo(dtest, "label", &out_len, &out_result));
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printf("y_test: ");
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for (int i = 0; i < n_print; ++i) {
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printf("%1.4f ", out_result[i]);
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}
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printf("\n");
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{
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printf("Dense Matrix Example (XGDMatrixCreateFromMat): ");
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const float values[] = {0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0,
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1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
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0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0,
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1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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1, 0, 0, 0, 0, 1, 0, 0, 0, 0};
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DMatrixHandle dmat;
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safe_xgboost(XGDMatrixCreateFromMat(values, 1, 127, 0.0, &dmat));
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bst_ulong out_len = 0;
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const float* out_result = NULL;
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safe_xgboost(XGBoosterPredict(booster, dmat, 0, 0, 0, &out_len,
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&out_result));
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assert(out_len == 1);
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printf("%1.4f \n", out_result[0]);
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safe_xgboost(XGDMatrixFree(dmat));
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}
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{
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printf("Sparse Matrix Example (XGDMatrixCreateFromCSREx): ");
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const size_t indptr[] = {0, 22};
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const unsigned indices[] = {1, 9, 19, 21, 24, 34, 36, 39, 42, 53, 56, 65,
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69, 77, 86, 88, 92, 95, 102, 106, 117, 122};
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const float data[] = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
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1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};
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DMatrixHandle dmat;
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safe_xgboost(XGDMatrixCreateFromCSREx(indptr, indices, data, 2, 22, 127,
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&dmat));
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bst_ulong out_len = 0;
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const float* out_result = NULL;
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safe_xgboost(XGBoosterPredict(booster, dmat, 0, 0, 0, &out_len,
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&out_result));
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assert(out_len == 1);
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printf("%1.4f \n", out_result[0]);
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safe_xgboost(XGDMatrixFree(dmat));
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}
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{
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printf("Sparse Matrix Example (XGDMatrixCreateFromCSCEx): ");
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const size_t col_ptr[] = {0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2,
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2, 2, 2, 2, 3, 3, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 7, 7, 7, 8,
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8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 11, 11, 11, 11, 11, 11,
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11, 11, 11, 12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 14, 14, 14,
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14, 14, 14, 14, 14, 14, 15, 15, 16, 16, 16, 16, 17, 17, 17, 18, 18, 18,
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18, 18, 18, 18, 19, 19, 19, 19, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,
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20, 21, 21, 21, 21, 21, 22, 22, 22, 22, 22};
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const unsigned indices[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0};
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const float data[] = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
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1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};
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DMatrixHandle dmat;
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safe_xgboost(XGDMatrixCreateFromCSCEx(col_ptr, indices, data, 128, 22, 1,
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&dmat));
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bst_ulong out_len = 0;
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const float* out_result = NULL;
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safe_xgboost(XGBoosterPredict(booster, dmat, 0, 0, 0, &out_len,
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&out_result));
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assert(out_len == 1);
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printf("%1.4f \n", out_result[0]);
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safe_xgboost(XGDMatrixFree(dmat));
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}
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// free everything
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safe_xgboost(XGBoosterFree(booster));
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safe_xgboost(XGDMatrixFree(dtrain));
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safe_xgboost(XGDMatrixFree(dtest));
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return 0;
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}
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