Use matrix for gradient. (#9508)
- 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)
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@@ -24,8 +24,8 @@ TEST(Linear, Shotgun) {
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auto updater =
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std::unique_ptr<xgboost::LinearUpdater>(xgboost::LinearUpdater::Create("shotgun", &ctx));
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updater->Configure({{"eta", "1."}});
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xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
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p_fmat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
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linalg::Matrix<xgboost::GradientPair> gpair{
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linalg::Constant(&ctx, xgboost::GradientPair(-5, 1.0), p_fmat->Info().num_row_, 1)};
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xgboost::gbm::GBLinearModel model{&mparam};
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model.LazyInitModel();
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updater->Update(&gpair, p_fmat.get(), &model, gpair.Size());
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@@ -55,8 +55,8 @@ TEST(Linear, coordinate) {
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auto updater = std::unique_ptr<xgboost::LinearUpdater>(
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xgboost::LinearUpdater::Create("coord_descent", &ctx));
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updater->Configure({{"eta", "1."}});
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xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
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p_fmat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
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linalg::Matrix<xgboost::GradientPair> gpair{
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linalg::Constant(&ctx, xgboost::GradientPair(-5, 1.0), p_fmat->Info().num_row_, 1)};
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xgboost::gbm::GBLinearModel model{&mparam};
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model.LazyInitModel();
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updater->Update(&gpair, p_fmat.get(), &model, gpair.Size());
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