137 lines
3.8 KiB
Plaintext
137 lines
3.8 KiB
Plaintext
/*!
|
|
* Copyright 2017-2019 XGBoost contributors
|
|
*/
|
|
#pragma once
|
|
#include <thrust/random.h>
|
|
#include <cstdio>
|
|
#include <cub/cub.cuh>
|
|
#include <stdexcept>
|
|
#include <string>
|
|
#include <vector>
|
|
#include "../common/device_helpers.cuh"
|
|
#include "../common/random.h"
|
|
#include "param.h"
|
|
|
|
namespace xgboost {
|
|
namespace tree {
|
|
|
|
struct GPUTrainingParam {
|
|
// minimum amount of hessian(weight) allowed in a child
|
|
float min_child_weight;
|
|
// L2 regularization factor
|
|
float reg_lambda;
|
|
// L1 regularization factor
|
|
float reg_alpha;
|
|
// maximum delta update we can add in weight estimation
|
|
// this parameter can be used to stabilize update
|
|
// default=0 means no constraint on weight delta
|
|
float max_delta_step;
|
|
float learning_rate;
|
|
|
|
GPUTrainingParam() = default;
|
|
|
|
XGBOOST_DEVICE explicit GPUTrainingParam(const TrainParam& param)
|
|
: min_child_weight(param.min_child_weight),
|
|
reg_lambda(param.reg_lambda),
|
|
reg_alpha(param.reg_alpha),
|
|
max_delta_step(param.max_delta_step),
|
|
learning_rate{param.learning_rate} {}
|
|
};
|
|
|
|
using NodeIdT = int32_t;
|
|
|
|
/** used to assign default id to a Node */
|
|
static const bst_node_t kUnusedNode = -1;
|
|
|
|
/**
|
|
* @enum DefaultDirection node.cuh
|
|
* @brief Default direction to be followed in case of missing values
|
|
*/
|
|
enum DefaultDirection {
|
|
/** move to left child */
|
|
kLeftDir = 0,
|
|
/** move to right child */
|
|
kRightDir
|
|
};
|
|
|
|
struct DeviceSplitCandidate {
|
|
float loss_chg {-FLT_MAX};
|
|
DefaultDirection dir {kLeftDir};
|
|
int findex {-1};
|
|
float fvalue {0};
|
|
bool is_cat { false };
|
|
|
|
GradientPair left_sum;
|
|
GradientPair right_sum;
|
|
|
|
XGBOOST_DEVICE DeviceSplitCandidate() {} // NOLINT
|
|
|
|
template <typename ParamT>
|
|
XGBOOST_DEVICE void Update(const DeviceSplitCandidate& other,
|
|
const ParamT& param) {
|
|
if (other.loss_chg > loss_chg &&
|
|
other.left_sum.GetHess() >= param.min_child_weight &&
|
|
other.right_sum.GetHess() >= param.min_child_weight) {
|
|
*this = other;
|
|
}
|
|
}
|
|
|
|
XGBOOST_DEVICE void Update(float loss_chg_in, DefaultDirection dir_in,
|
|
float fvalue_in, int findex_in,
|
|
GradientPair left_sum_in,
|
|
GradientPair right_sum_in,
|
|
bool cat,
|
|
const GPUTrainingParam& param) {
|
|
if (loss_chg_in > loss_chg &&
|
|
left_sum_in.GetHess() >= param.min_child_weight &&
|
|
right_sum_in.GetHess() >= param.min_child_weight) {
|
|
loss_chg = loss_chg_in;
|
|
dir = dir_in;
|
|
fvalue = fvalue_in;
|
|
is_cat = cat;
|
|
left_sum = left_sum_in;
|
|
right_sum = right_sum_in;
|
|
findex = findex_in;
|
|
}
|
|
}
|
|
XGBOOST_DEVICE bool IsValid() const { return loss_chg > 0.0f; }
|
|
|
|
friend std::ostream& operator<<(std::ostream& os, DeviceSplitCandidate const& c) {
|
|
os << "loss_chg:" << c.loss_chg << ", "
|
|
<< "dir: " << c.dir << ", "
|
|
<< "findex: " << c.findex << ", "
|
|
<< "fvalue: " << c.fvalue << ", "
|
|
<< "is_cat: " << c.is_cat << ", "
|
|
<< "left sum: " << c.left_sum << ", "
|
|
<< "right sum: " << c.right_sum << std::endl;
|
|
return os;
|
|
}
|
|
};
|
|
|
|
struct DeviceSplitCandidateReduceOp {
|
|
GPUTrainingParam param;
|
|
explicit DeviceSplitCandidateReduceOp(GPUTrainingParam param) : param(std::move(param)) {}
|
|
XGBOOST_DEVICE DeviceSplitCandidate operator()(
|
|
const DeviceSplitCandidate& a, const DeviceSplitCandidate& b) const {
|
|
DeviceSplitCandidate best;
|
|
best.Update(a, param);
|
|
best.Update(b, param);
|
|
return best;
|
|
}
|
|
};
|
|
|
|
template <typename T>
|
|
struct SumCallbackOp {
|
|
// Running prefix
|
|
T running_total;
|
|
// Constructor
|
|
XGBOOST_DEVICE SumCallbackOp() : running_total(T()) {}
|
|
XGBOOST_DEVICE T operator()(T block_aggregate) {
|
|
T old_prefix = running_total;
|
|
running_total += block_aggregate;
|
|
return old_prefix;
|
|
}
|
|
};
|
|
} // namespace tree
|
|
} // namespace xgboost
|