FlatHashMap: add tests
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@ -127,7 +127,7 @@ class FlatHashMapImpl {
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DCHECK(empty());
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first = std::move(key);
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new (&second) ValueT(std::forward<ArgsT>(args)...);
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CHECK(!empty());
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DCHECK(!empty());
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}
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};
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using Self = FlatHashMapImpl<KeyT, ValueT, HashT>;
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@ -420,7 +420,7 @@ class FlatHashMapImpl {
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}
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void grow() {
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size_t want_size = normalize(td::max(nodes_.size() * 2 - 1, (used_nodes_ + 1) * 5 / 3 + 1));
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size_t want_size = normalize((used_nodes_ + 1) * 5 / 3 + 1);
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// size_t want_size = td::max(nodes_.size(), (used_nodes_ + 1)) * 2;
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resize(want_size);
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}
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@ -12,6 +12,13 @@
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#include "td/utils/Random.h"
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#include "td/utils/algorithm.h"
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template <class T>
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auto extract_kv(const T &reference) {
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auto expected = td::transform(reference, [](auto &it) {return std::make_pair(it.first, it.second);});
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std::sort(expected.begin(), expected.end());
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return expected;
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}
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TEST(FlatHashMap, basic) {
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{
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td::FlatHashMap<int, int> map;
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@ -48,23 +55,80 @@ TEST(FlatHashMap, basic) {
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ASSERT_EQ("world", map[1]);
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ASSERT_EQ(1u, map.size());
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}
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}
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template <class T>
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auto extract_kv(const T &reference) {
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auto expected = td::transform(reference, [](auto &it) {return std::make_pair(it.first, it.second);});
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std::sort(expected.begin(), expected.end());
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return expected;
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using KV = td::FlatHashMapImpl<std::string, std::string>;
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using Data = std::vector<std::pair<std::string, std::string>>;
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auto data = Data{{"a", "b"}, {"c", "d"}};
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{
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ASSERT_EQ(Data{}, extract_kv(KV()));
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}
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{
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KV kv(data.begin(), data.end());
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ASSERT_EQ(data, extract_kv(kv));
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KV copied_kv(kv);
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ASSERT_EQ(data, extract_kv(copied_kv));
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KV moved_kv(std::move(kv));
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ASSERT_EQ(data, extract_kv(moved_kv));
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ASSERT_EQ(Data{}, extract_kv(kv));
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ASSERT_TRUE(kv.empty());
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kv = std::move(moved_kv);
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ASSERT_EQ(data, extract_kv(kv));
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KV assign_copied_kv;
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assign_copied_kv = kv;
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ASSERT_EQ(data, extract_kv(assign_copied_kv));
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KV assign_moved_kv;
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assign_moved_kv = std::move(kv);
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ASSERT_EQ(data, extract_kv(assign_moved_kv));
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ASSERT_EQ(Data{}, extract_kv(kv));
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ASSERT_TRUE(kv.empty());
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kv = std::move(assign_moved_kv);
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KV it_copy_kv(kv.begin(), kv.end());
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ASSERT_EQ(data, extract_kv(it_copy_kv));
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}
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{
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KV kv;
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ASSERT_TRUE(kv.empty());
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ASSERT_EQ(0u, kv.size());
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kv = KV(data.begin(), data.end());
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ASSERT_TRUE(!kv.empty());
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ASSERT_EQ(2u, kv.size());
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ASSERT_EQ("a", kv.find("a")->first);
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ASSERT_EQ("b", kv.find("a")->second);
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ASSERT_EQ("a", kv.find("a")->key());
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ASSERT_EQ("b", kv.find("a")->value());
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kv.find("a")->second = "c";
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ASSERT_EQ("c", kv.find("a")->second);
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ASSERT_EQ("c", kv["a"]);
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ASSERT_EQ(0u, kv.count("x"));
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ASSERT_EQ(1u, kv.count("a"));
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}
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{
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KV kv;
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kv["d"];
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ASSERT_EQ((Data{{"d", ""}}), extract_kv(kv));
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kv.erase(kv.find("d"));
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ASSERT_EQ(Data{}, extract_kv(kv));
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}
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}
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TEST(FlatHashMap, remove_if_basic) {
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td::Random::Xorshift128plus rnd(123);
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for (int test_i = 0; test_i < 1000000; test_i++) {
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constexpr int TESTS_N = 10000;
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constexpr int MAX_TABLE_SIZE = 1000;
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for (int test_i = 0; test_i < TESTS_N; test_i++) {
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std::unordered_map<td::uint64, td::uint64> reference;
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td::FlatHashMap<td::uint64, td::uint64> table;
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LOG_IF(ERROR, test_i % 1000 == 0) << test_i;
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int N = rnd.fast(1, 1000);
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int N = rnd.fast(1, MAX_TABLE_SIZE);
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for (int i = 0; i < N; i++) {
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auto key = rnd();
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auto value = i;
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@ -82,3 +146,114 @@ TEST(FlatHashMap, remove_if_basic) {
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ASSERT_EQ(extract_kv(reference), extract_kv(table));
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}
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}
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TEST(FlatHashMap, stress_test) {
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std::vector<td::RandomSteps::Step> steps;
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auto add_step = [&steps](td::Slice, td::uint32 weight, auto f) {
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steps.emplace_back(td::RandomSteps::Step{std::move(f), weight});
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};
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td::Random::Xorshift128plus rnd(123);
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size_t max_table_size = 1000; // dynamic value
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std::unordered_map<td::uint64, td::uint64> ref;
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td::FlatHashMapImpl<td::uint64, td::uint64> tbl;
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auto validate = [&]() {
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ASSERT_EQ(ref.empty(), tbl.empty());
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ASSERT_EQ(ref.size(), tbl.size());
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ASSERT_EQ(extract_kv(ref), extract_kv(tbl));
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for (auto &kv : ref) {
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ASSERT_EQ(ref[kv.first], tbl[kv.first]);
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}
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};
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auto gen_key = [&]() {
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auto key = rnd() % 4000 + 1;
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return key;
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};
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add_step("Reset hash table", 1, [&]() {
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validate();
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td::reset_to_empty(ref);
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td::reset_to_empty(tbl);
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max_table_size = rnd.fast(1, 1000);
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});
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add_step("Clear hash table", 1, [&]() {
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validate();
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ref.clear();
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tbl.clear();
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max_table_size = rnd.fast(1, 1000);
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});
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add_step("Insert random value", 1000, [&]() {
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if (tbl.size() > max_table_size) {
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return;
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}
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auto key = gen_key();
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auto value = rnd();
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ref[key] = value;
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tbl[key] = value;
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ASSERT_EQ(ref[key], tbl[key]);
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});
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add_step("Emplace random value", 1000, [&]() {
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if (tbl.size() > max_table_size) {
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return;
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}
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auto key = gen_key();
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auto value = rnd();
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auto ref_it = ref.emplace(key, value);
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auto tbl_it = tbl.emplace(key, value);
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ASSERT_EQ(ref_it.second, tbl_it.second);
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ASSERT_EQ(key, tbl_it.first->first);
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});
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add_step("empty operator[]", 1000, [&]() {
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if (tbl.size() > max_table_size) {
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return;
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}
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auto key = gen_key();
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ASSERT_EQ(ref[key], tbl[key]);
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});
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add_step("reserve", 10, [&]() {
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tbl.reserve(rnd() % max_table_size);
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});
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add_step("find", 1000, [&] {
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auto key = gen_key();
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auto ref_it = ref.find(key) ;
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auto tbl_it = tbl.find(key) ;
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ASSERT_EQ(ref_it == ref.end(), tbl_it == tbl.end());
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if (ref_it != ref.end()) {
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ASSERT_EQ(ref_it->first, tbl_it->first);
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ASSERT_EQ(ref_it->second, tbl_it->second);
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}
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});
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add_step("find_and_erase", 100, [&] {
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auto key = gen_key();
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auto ref_it = ref.find(key) ;
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auto tbl_it = tbl.find(key) ;
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ASSERT_EQ(ref_it == ref.end(), tbl_it == tbl.end());
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if (ref_it != ref.end()) {
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ref.erase(ref_it);
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tbl.erase(tbl_it);
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}
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});
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add_step("remove_if", 5, [&] {
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auto mul = rnd();
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auto bit = rnd() % 64;
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auto cnd = [&](auto &it) {
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return (((it.second * mul) >> bit) & 1) == 0;
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};
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td::table_remove_if(tbl, cnd);
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td::table_remove_if(ref, cnd);
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});
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td::RandomSteps runner(std::move(steps));
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for (size_t i = 0; i < 1000000; i++) {
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runner.step(rnd);
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}
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}
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