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Remove update prediction cache from predictors. (#5312)

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Move this function into gbtree, and uses only updater for doing so. As now the predictor knows exactly how many trees to predict, there's no need for it to update the prediction cache.
This commit is contained in:
Jiaming Yuan
2020-02-17 11:35:47 +08:00
committed by GitHub
parent e433a379e4
commit 0110754a76
16 changed files with 118 additions and 164 deletions
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29
tests/cpp/common/test_hist_util.h
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@@ -1,9 +1,15 @@
#pragma once
#include <gtest/gtest.h>
#include <dmlc/filesystem.h>
#include <random>
#include <vector>
#include <string>
#include <fstream>
#include "../../../src/common/hist_util.h"
#include "../../../src/data/simple_dmatrix.h"
// Some helper functions used to test both GPU and CPU algorithms
//
//
namespace xgboost {
namespace common {
@@ -13,8 +19,8 @@ inline std::vector<float> GenerateRandom(int num_rows, int num_columns) {
std::mt19937 rng(0);
std::uniform_real_distribution<float> dist(0.0, 1.0);
std::generate(x.begin(), x.end(), [&]() { return dist(rng); });
for (auto i = 0ull; i < num_columns; i++) {
for (auto j = 0ull; j < num_rows; j++) {
for (auto i = 0; i < num_columns; i++) {
for (auto j = 0; j < num_rows; j++) {
x[j * num_columns + i] += i;
}
}
@@ -22,14 +28,13 @@ inline std::vector<float> GenerateRandom(int num_rows, int num_columns) {
}
inline std::vector<float> GenerateRandomCategoricalSingleColumn(int n,
int num_categories) {
int num_categories) {
std::vector<float> x(n);
std::mt19937 rng(0);
std::uniform_int_distribution<int> dist(0, num_categories - 1);
std::generate(x.begin(), x.end(), [&]() { return dist(rng); });
// Make sure each category is present
for(auto i = 0ull; i < num_categories; i++)
{
for(auto i = 0; i < num_categories; i++) {
x[i] = i;
}
return x;
@@ -47,9 +52,9 @@ inline std::shared_ptr<DMatrix> GetExternalMemoryDMatrixFromData(
// Create the svm file in a temp dir
const std::string tmp_file = tempdir.path + "/temp.libsvm";
std::ofstream fo(tmp_file.c_str());
for (auto i = 0ull; i < num_rows; i++) {
for (auto i = 0; i < num_rows; i++) {
std::stringstream row_data;
for (auto j = 0ull; j < num_columns; j++) {
for (auto j = 0; j < num_columns; j++) {
row_data << 1 << " " << j << ":" << std::setprecision(15)
<< x[i * num_columns + j];
}
@@ -62,7 +67,7 @@ inline std::shared_ptr<DMatrix> GetExternalMemoryDMatrixFromData(
// Test that elements are approximately equally distributed among bins
inline void TestBinDistribution(const HistogramCuts& cuts, int column_idx,
const std::vector<float>& column,
const std::vector<float>& column,
int num_bins) {
std::map<int, int> counts;
for (auto& v : column) {
@@ -144,11 +149,11 @@ inline void ValidateColumn(const HistogramCuts& cuts, int column_idx,
// x is dense and row major
inline void ValidateCuts(const HistogramCuts& cuts, std::vector<float>& x,
int num_rows, int num_columns,
int num_bins) {
for (auto i = 0ull; i < num_columns; i++) {
int num_bins) {
for (auto i = 0; i < num_columns; i++) {
// Extract the column
std::vector<float> column(num_rows);
for (auto j = 0ull; j < num_rows; j++) {
for (auto j = 0; j < num_rows; j++) {
column[j] = x[j*num_columns + i];
}
ValidateColumn(cuts,i, column, num_bins);