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CPU evaluation for cat data. (#7393)

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* Implementation for one hot based.
* Implementation for partition based. (LightGBM)
This commit is contained in:
Jiaming Yuan
2021-11-06 14:41:35 +08:00
committed by GitHub
parent 6ede12412c
commit d7d1b6e3a6
15 changed files with 540 additions and 166 deletions
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43
tests/cpp/helpers.h
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@@ -106,42 +106,39 @@ bool IsNear(std::vector<xgboost::bst_float>::const_iterator _beg1,
*/
class SimpleLCG {
private:
using StateType = int64_t;
using StateType = uint64_t;
static StateType constexpr kDefaultInit = 3;
static StateType constexpr default_alpha_ = 61;
static StateType constexpr max_value_ = ((StateType)1 << 32) - 1;
static StateType constexpr kDefaultAlpha = 61;
static StateType constexpr kMaxValue = (static_cast<StateType>(1) << 32) - 1;
StateType state_;
StateType const alpha_;
StateType const mod_;
StateType seed_;
public:
using result_type = StateType; // NOLINT
public:
SimpleLCG() : state_{kDefaultInit},
alpha_{default_alpha_}, mod_{max_value_}, seed_{state_}{}
SimpleLCG() : state_{kDefaultInit}, alpha_{kDefaultAlpha}, mod_{kMaxValue} {}
SimpleLCG(SimpleLCG const& that) = default;
SimpleLCG(SimpleLCG&& that) = default;
void Seed(StateType seed) {
seed_ = seed;
}
void Seed(StateType seed) { state_ = seed % mod_; }
/*!
* \brief Initialize SimpleLCG.
*
* \param state Initial state, can also be considered as seed. If set to
* zero, SimpleLCG will use internal default value.
* \param alpha multiplier
* \param mod modulo
*/
explicit SimpleLCG(StateType state,
StateType alpha=default_alpha_, StateType mod=max_value_)
: state_{state == 0 ? kDefaultInit : state},
alpha_{alpha}, mod_{mod} , seed_{state} {}
explicit SimpleLCG(StateType state)
: state_{state == 0 ? kDefaultInit : state}, alpha_{kDefaultAlpha}, mod_{kMaxValue} {}
StateType operator()();
StateType Min() const;
StateType Max() const;
constexpr result_type static min() { return 0; }; // NOLINT
constexpr result_type static max() { return kMaxValue; } // NOLINT
};
template <typename ResultT>
@@ -217,10 +214,12 @@ class RandomDataGenerator {
float upper_;
int32_t device_;
int32_t seed_;
uint64_t seed_;
SimpleLCG lcg_;
size_t bins_;
std::vector<FeatureType> ft_;
bst_cat_t max_cat_;
Json ArrayInterfaceImpl(HostDeviceVector<float> *storage, size_t rows,
size_t cols) const;
@@ -242,7 +241,7 @@ class RandomDataGenerator {
device_ = d;
return *this;
}
RandomDataGenerator& Seed(int32_t s) {
RandomDataGenerator& Seed(uint64_t s) {
seed_ = s;
lcg_.Seed(seed_);
return *this;
@@ -251,6 +250,16 @@ class RandomDataGenerator {
bins_ = b;
return *this;
}
RandomDataGenerator& Type(common::Span<FeatureType> ft) {
CHECK_EQ(ft.size(), cols_);
ft_.resize(ft.size());
std::copy(ft.cbegin(), ft.cend(), ft_.begin());
return *this;
}
RandomDataGenerator& MaxCategory(bst_cat_t cat) {
max_cat_ = cat;
return *this;
}
void GenerateDense(HostDeviceVector<float>* out) const;