Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Multi-target support for L1 error. (#8652)

Browse Source 
- Add matrix support to the median function.
- Iterate through each target for quantile computation.
This commit is contained in:
Jiaming Yuan
2023-01-11 05:51:14 +08:00
committed by GitHub
parent badeff1d74
commit cfa994d57f
19 changed files with 430 additions and 215 deletions
Download Patch File Download Diff File Expand all files Collapse all files

87
tests/cpp/objective/test_regression_obj.cc
View File

@@ -1,13 +1,17 @@
/*!
* Copyright 2017-2022 XGBoost contributors
/**
* Copyright 2017-2023 by XGBoost contributors
*/
#include <gtest/gtest.h>
#include <xgboost/context.h>
#include <xgboost/json.h>
#include <xgboost/objective.h>
#include "../../../src/common/linalg_op.h" // begin,end
#include "../../../src/objective/adaptive.h"
#include "../helpers.h"
#include "xgboost/base.h"
#include "xgboost/data.h"
#include "xgboost/linalg.h"
namespace xgboost {
@@ -404,56 +408,61 @@ TEST(Objective, DeclareUnifiedTest(AbsoluteError)) {
h_predt[i] = labels[i] + i;
}
obj->UpdateTreeLeaf(position, info, predt, &tree);
obj->UpdateTreeLeaf(position, info, predt, 0, &tree);
ASSERT_EQ(tree[1].LeafValue(), -1);
ASSERT_EQ(tree[2].LeafValue(), -4);
}
TEST(Objective, DeclareUnifiedTest(AbsoluteErrorLeaf)) {
Context ctx = CreateEmptyGenericParam(GPUIDX);
bst_target_t constexpr kTargets = 3, kRows = 16;
std::unique_ptr<ObjFunction> obj{ObjFunction::Create("reg:absoluteerror", &ctx)};
obj->Configure({});
MetaInfo info;
info.labels.Reshape(16, 1);
info.num_row_ = info.labels.Size();
CHECK_EQ(info.num_row_, 16);
auto h_labels = info.labels.HostView().Values();
std::iota(h_labels.begin(), h_labels.end(), 0);
HostDeviceVector<float> predt(h_labels.size());
auto& h_predt = predt.HostVector();
for (size_t i = 0; i < h_predt.size(); ++i) {
h_predt[i] = h_labels[i] + i;
}
info.num_row_ = kRows;
info.labels.Reshape(16, kTargets);
HostDeviceVector<float> predt(info.labels.Size());
HostDeviceVector<bst_node_t> position(info.labels.Size(), 0);
auto& h_position = position.HostVector();
for (int32_t i = 0; i < 3; ++i) {
h_position[i] = ~i; // negation for sampled nodes.
}
for (size_t i = 3; i < 8; ++i) {
h_position[i] = 3;
}
// empty leaf for node 4
for (size_t i = 8; i < 13; ++i) {
h_position[i] = 5;
}
for (size_t i = 13; i < h_labels.size(); ++i) {
h_position[i] = 6;
}
for (bst_target_t t{0}; t < kTargets; ++t) {
auto h_labels = info.labels.HostView().Slice(linalg::All(), t);
std::iota(linalg::begin(h_labels), linalg::end(h_labels), 0);
RegTree tree;
tree.ExpandNode(0, /*split_index=*/1, 2, true, 0.0f, 2.f, 3.f, 4.f, 2.f, 1.f, 1.f);
tree.ExpandNode(1, /*split_index=*/1, 2, true, 0.0f, 2.f, 3.f, 4.f, 2.f, 1.f, 1.f);
tree.ExpandNode(2, /*split_index=*/1, 2, true, 0.0f, 2.f, 3.f, 4.f, 2.f, 1.f, 1.f);
ASSERT_EQ(tree.GetNumLeaves(), 4);
auto h_predt = linalg::MakeTensorView(predt.HostSpan(), {kRows, kTargets}, Context::kCpuId)
.Slice(linalg::All(), t);
for (size_t i = 0; i < h_predt.Size(); ++i) {
h_predt(i) = h_labels(i) + i;
}
auto empty_leaf = tree[4].LeafValue();
obj->UpdateTreeLeaf(position, info, predt, &tree);
ASSERT_EQ(tree[3].LeafValue(), -5);
ASSERT_EQ(tree[4].LeafValue(), empty_leaf);
ASSERT_EQ(tree[5].LeafValue(), -10);
ASSERT_EQ(tree[6].LeafValue(), -14);
HostDeviceVector<bst_node_t> position(h_labels.Size(), 0);
auto& h_position = position.HostVector();
for (int32_t i = 0; i < 3; ++i) {
h_position[i] = ~i; // negation for sampled nodes.
}
for (size_t i = 3; i < 8; ++i) {
h_position[i] = 3;
}
// empty leaf for node 4
for (size_t i = 8; i < 13; ++i) {
h_position[i] = 5;
}
for (size_t i = 13; i < h_labels.Size(); ++i) {
h_position[i] = 6;
}
RegTree tree;
tree.ExpandNode(0, /*split_index=*/1, 2, true, 0.0f, 2.f, 3.f, 4.f, 2.f, 1.f, 1.f);
tree.ExpandNode(1, /*split_index=*/1, 2, true, 0.0f, 2.f, 3.f, 4.f, 2.f, 1.f, 1.f);
tree.ExpandNode(2, /*split_index=*/1, 2, true, 0.0f, 2.f, 3.f, 4.f, 2.f, 1.f, 1.f);
ASSERT_EQ(tree.GetNumLeaves(), 4);
auto empty_leaf = tree[4].LeafValue();
obj->UpdateTreeLeaf(position, info, predt, t, &tree);
ASSERT_EQ(tree[3].LeafValue(), -5);
ASSERT_EQ(tree[4].LeafValue(), empty_leaf);
ASSERT_EQ(tree[5].LeafValue(), -10);
ASSERT_EQ(tree[6].LeafValue(), -14);
}
}
TEST(Adaptive, DeclareUnifiedTest(MissingLeaf)) {