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Use matrix for gradient. (#9508)

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- Use the `linalg::Matrix` for storing gradients.
- New API for the custom objective.
- Custom objective for multi-class/multi-target is now required to return the correct shape.
- Custom objective for Python can accept arrays with any strides. (row-major, column-major)
This commit is contained in:
Jiaming Yuan
2023-08-24 05:29:52 +08:00
committed by GitHub
parent 6103dca0bb
commit 972730cde0
77 changed files with 1052 additions and 651 deletions
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17
tests/cpp/tree/test_tree_stat.cc
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@@ -16,7 +16,7 @@ namespace xgboost {
class UpdaterTreeStatTest : public ::testing::Test {
protected:
std::shared_ptr<DMatrix> p_dmat_;
HostDeviceVector<GradientPair> gpairs_;
linalg::Matrix<GradientPair> gpairs_;
size_t constexpr static kRows = 10;
size_t constexpr static kCols = 10;
@@ -24,8 +24,8 @@ class UpdaterTreeStatTest : public ::testing::Test {
void SetUp() override {
p_dmat_ = RandomDataGenerator(kRows, kCols, .5f).GenerateDMatrix(true);
auto g = GenerateRandomGradients(kRows);
gpairs_.Resize(kRows);
gpairs_.Copy(g);
gpairs_.Reshape(kRows, 1);
gpairs_.Data()->Copy(g);
}
void RunTest(std::string updater) {
@@ -63,7 +63,7 @@ TEST_F(UpdaterTreeStatTest, Approx) { this->RunTest("grow_histmaker"); }
class UpdaterEtaTest : public ::testing::Test {
protected:
std::shared_ptr<DMatrix> p_dmat_;
HostDeviceVector<GradientPair> gpairs_;
linalg::Matrix<GradientPair> gpairs_;
size_t constexpr static kRows = 10;
size_t constexpr static kCols = 10;
size_t constexpr static kClasses = 10;
@@ -71,8 +71,8 @@ class UpdaterEtaTest : public ::testing::Test {
void SetUp() override {
p_dmat_ = RandomDataGenerator(kRows, kCols, .5f).GenerateDMatrix(true, false, kClasses);
auto g = GenerateRandomGradients(kRows);
gpairs_.Resize(kRows);
gpairs_.Copy(g);
gpairs_.Reshape(kRows, 1);
gpairs_.Data()->Copy(g);
}
void RunTest(std::string updater) {
@@ -125,14 +125,15 @@ TEST_F(UpdaterEtaTest, GpuHist) { this->RunTest("grow_gpu_hist"); }
class TestMinSplitLoss : public ::testing::Test {
std::shared_ptr<DMatrix> dmat_;
HostDeviceVector<GradientPair> gpair_;
linalg::Matrix<GradientPair> gpair_;
void SetUp() override {
constexpr size_t kRows = 32;
constexpr size_t kCols = 16;
constexpr float kSparsity = 0.6;
dmat_ = RandomDataGenerator(kRows, kCols, kSparsity).Seed(3).GenerateDMatrix();
gpair_ = GenerateRandomGradients(kRows);
gpair_.Reshape(kRows, 1);
gpair_.Data()->Copy(GenerateRandomGradients(kRows));
}
std::int32_t Update(Context const* ctx, std::string updater, float gamma) {