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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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12
tests/cpp/tree/test_prune.cc
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@@ -21,15 +21,13 @@ TEST(Updater, Prune) {
std::vector<std::pair<std::string, std::string>> cfg;
cfg.emplace_back("num_feature", std::to_string(kCols));
cfg.emplace_back("min_split_loss", "10");
Context ctx;
// These data are just place holders.
HostDeviceVector<GradientPair> gpair =
{ {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f},
{0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f} };
std::shared_ptr<DMatrix> p_dmat {
RandomDataGenerator{32, 10, 0}.GenerateDMatrix() };
Context ctx;
linalg::Matrix<GradientPair> gpair
{{ {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f},
{0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f} }, {8, 1}, ctx.Device()};
std::shared_ptr<DMatrix> p_dmat{RandomDataGenerator{32, 10, 0}.GenerateDMatrix()};
// prepare tree
RegTree tree = RegTree{1u, kCols};