xgboost_lib-sys 3.0.5

Native bindings to the xgboost library
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71

/*!
 * Copyright 2018-2019 by Contributors
 */
#include <xgboost/linear_updater.h>
#include <xgboost/gbm.h>

#include "../helpers.h"
#include "test_json_io.h"
#include "../../../src/gbm/gblinear_model.h"
#include "xgboost/base.h"

namespace xgboost {

TEST(Linear, Shotgun) {
  size_t constexpr kRows = 10;
  size_t constexpr kCols = 10;

  auto p_fmat = xgboost::RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();

  auto ctx = MakeCUDACtx(GPUIDX);
  LearnerModelParam mparam{MakeMP(kCols, .5, 1)};

  {
    auto updater =
        std::unique_ptr<xgboost::LinearUpdater>(xgboost::LinearUpdater::Create("shotgun", &ctx));
    updater->Configure({{"eta", "1."}});
    linalg::Matrix<xgboost::GradientPair> gpair{
        linalg::Constant(&ctx, xgboost::GradientPair(-5, 1.0), p_fmat->Info().num_row_, 1)};
    xgboost::gbm::GBLinearModel model{&mparam};
    model.LazyInitModel();
    updater->Update(&gpair, p_fmat.get(), &model, gpair.Size());

    ASSERT_EQ(model.Bias()[0], 5.0f);
  }
  {
    auto updater = std::unique_ptr<xgboost::LinearUpdater>(
        xgboost::LinearUpdater::Create("shotgun", &ctx));
    EXPECT_ANY_THROW(updater->Configure({{"feature_selector", "random"}}));
  }
}

TEST(Shotgun, JsonIO) {
  TestUpdaterJsonIO("shotgun");
}

TEST(Linear, coordinate) {
  size_t constexpr kRows = 10;
  size_t constexpr kCols = 10;

  auto p_fmat = xgboost::RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();

  auto ctx = MakeCUDACtx(GPUIDX);
  LearnerModelParam mparam{MakeMP(kCols, .5, 1)};

  auto updater = std::unique_ptr<xgboost::LinearUpdater>(
      xgboost::LinearUpdater::Create("coord_descent", &ctx));
  updater->Configure({{"eta", "1."}});
  linalg::Matrix<xgboost::GradientPair> gpair{
      linalg::Constant(&ctx, xgboost::GradientPair(-5, 1.0), p_fmat->Info().num_row_, 1)};
  xgboost::gbm::GBLinearModel model{&mparam};
  model.LazyInitModel();
  updater->Update(&gpair, p_fmat.get(), &model, gpair.Size());

  ASSERT_EQ(model.Bias()[0], 5.0f);
}

TEST(Coordinate, JsonIO){
  TestUpdaterJsonIO("coord_descent");
}

}  // namespace xgboost