d9a47794a5
* Fix CPU hist init for sparse dataset. * Implement sparse histogram cut. * Allow empty features. * Fix windows build, don't use sparse in distributed environment. * Comments. * Smaller threshold. * Fix windows omp. * Fix msvc lambda capture. * Fix MSVC macro. * Fix MSVC initialization list. * Fix MSVC initialization list x2. * Preserve categorical feature behavior. * Rename matrix to sparse cuts. * Reuse UseGroup. * Check for categorical data when adding cut. Co-Authored-By: Philip Hyunsu Cho <chohyu01@cs.washington.edu> * Sanity check. * Fix comments. * Fix comment.
81 lines
2.1 KiB
C++
81 lines
2.1 KiB
C++
#include <valarray>
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#include "../../../src/common/random.h"
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#include "../helpers.h"
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#include "gtest/gtest.h"
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namespace xgboost {
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namespace common {
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TEST(ColumnSampler, Test) {
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int n = 128;
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ColumnSampler cs;
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// No node sampling
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cs.Init(n, 1.0f, 0.5f, 0.5f);
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auto set0 = *cs.GetFeatureSet(0);
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ASSERT_EQ(set0.Size(), 32);
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auto set1 = *cs.GetFeatureSet(0);
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ASSERT_EQ(set0.HostVector(), set1.HostVector());
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auto set2 = *cs.GetFeatureSet(1);
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ASSERT_NE(set1.HostVector(), set2.HostVector());
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ASSERT_EQ(set2.Size(), 32);
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// Node sampling
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cs.Init(n, 0.5f, 1.0f, 0.5f);
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auto set3 = *cs.GetFeatureSet(0);
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ASSERT_EQ(set3.Size(), 32);
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auto set4 = *cs.GetFeatureSet(0);
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ASSERT_NE(set3.HostVector(), set4.HostVector());
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ASSERT_EQ(set4.Size(), 32);
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// No level or node sampling, should be the same at different depth
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cs.Init(n, 1.0f, 1.0f, 0.5f);
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ASSERT_EQ(cs.GetFeatureSet(0)->HostVector(),
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cs.GetFeatureSet(1)->HostVector());
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cs.Init(n, 1.0f, 1.0f, 1.0f);
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auto set5 = *cs.GetFeatureSet(0);
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ASSERT_EQ(set5.Size(), n);
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cs.Init(n, 1.0f, 1.0f, 1.0f);
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auto set6 = *cs.GetFeatureSet(0);
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ASSERT_EQ(set5.HostVector(), set6.HostVector());
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// Should always be a minimum of one feature
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cs.Init(n, 1e-16f, 1e-16f, 1e-16f);
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ASSERT_EQ(cs.GetFeatureSet(0)->Size(), 1);
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}
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// Test if different threads using the same seed produce the same result
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TEST(ColumnSampler, ThreadSynchronisation) {
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const int64_t num_threads = 100;
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int n = 128;
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size_t iterations = 10;
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size_t levels = 5;
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std::vector<int> reference_result;
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bool success =
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true; // Cannot use google test asserts in multithreaded region
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#pragma omp parallel num_threads(num_threads)
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{
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for (auto j = 0ull; j < iterations; j++) {
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ColumnSampler cs(j);
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cs.Init(n, 0.5f, 0.5f, 0.5f);
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for (auto level = 0ull; level < levels; level++) {
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auto result = cs.GetFeatureSet(level)->ConstHostVector();
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#pragma omp single
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{ reference_result = result; }
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if (result != reference_result) {
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success = false;
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}
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#pragma omp barrier
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}
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}
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}
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ASSERT_TRUE(success);
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}
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} // namespace common
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} // namespace xgboost
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