Merge tag 'v1.5.2' into branch-22.02

.github/workflows/jvm_tests.yml

@@ -9,7 +9,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [windows-latest, ubuntu-latest]
+        os: [windows-latest, ubuntu-latest, macos-10.15]
 
     steps:
     - uses: actions/checkout@v2

.github/workflows/python_tests.yml

@@ -45,13 +45,13 @@ jobs:
         cd ..
         python -c 'import xgboost'
 
-  python-tests:
+  python-tests-on-win:
     name: Test XGBoost Python package on ${{ matrix.config.os }}
     runs-on: ${{ matrix.config.os }}
     strategy:
       matrix:
         config:
-          - {os: windows-2016, compiler: 'msvc', python-version: '3.8'}
+          - {os: windows-2016, python-version: '3.8'}
 
     steps:
     - uses: actions/checkout@v2
@@ -62,7 +62,7 @@ jobs:
       with:
         auto-update-conda: true
         python-version: ${{ matrix.config.python-version }}
-        activate-environment: win64_test
+        activate-environment: win64_env
         environment-file: tests/ci_build/conda_env/win64_cpu_test.yml
 
     - name: Display Conda env
@@ -71,9 +71,8 @@ jobs:
         conda info
         conda list
 
-    - name: Build XGBoost with msvc
+    - name: Build XGBoost on Windows
       shell: bash -l {0}
-      if: matrix.config.compiler == 'msvc'
       run: |
         mkdir build_msvc
         cd build_msvc
@@ -92,3 +91,74 @@ jobs:
       shell: bash -l {0}
       run: |
         pytest -s -v ./tests/python
+
+  python-tests-on-macos:
+    name: Test XGBoost Python package on ${{ matrix.config.os }}
+    runs-on: ${{ matrix.config.os }}
+    strategy:
+      matrix:
+        config:
+          - {os: macos-10.15, python-version "3.8" }
+
+    steps:
+    - uses: actions/checkout@v2
+      with:
+        submodules: 'true'
+
+    - uses: conda-incubator/setup-miniconda@v2
+      with:
+        auto-update-conda: true
+        python-version: ${{ matrix.config.python-version }}
+        activate-environment: macos_test
+        environment-file: tests/ci_build/conda_env/macos_cpu_test.yml
+
+    - name: Display Conda env
+      shell: bash -l {0}
+      run: |
+        conda info
+        conda list
+
+    - name: Build XGBoost on macos
+      run: |
+        wget https://raw.githubusercontent.com/Homebrew/homebrew-core/679923b4eb48a8dc7ecc1f05d06063cd79b3fc00/Formula/libomp.rb -O $(find $(brew --repository) -name libomp.rb)
+        brew install ninja libomp
+        brew pin libomp
+
+        mkdir build
+        cd build
+        cmake .. -GNinja -DGOOGLE_TEST=ON -DUSE_DMLC_GTEST=ON
+        ninja
+
+    - name: Install Python package
+      shell: bash -l {0}
+      run: |
+        cd python-package
+        python --version
+        python setup.py bdist_wheel --universal
+        pip install ./dist/*.whl
+
+    - name: Test Python package
+      shell: bash -l {0}
+      run: |
+        pytest -s -v ./tests/python
+
+    - name: Rename Python wheel
+      shell: bash -l {0}
+      run: |
+        TAG=macosx_10_15_x86_64.macosx_11_0_x86_64.macosx_12_0_x86_64
+        python tests/ci_build/rename_whl.py python-package/dist/*.whl ${{ github.sha }} ${TAG}
+
+    - name: Extract branch name
+      shell: bash
+      run: echo "##[set-output name=branch;]$(echo ${GITHUB_REF#refs/heads/})"
+      id: extract_branch
+      if: github.ref == 'refs/heads/master' || contains(github.ref, 'refs/heads/release_')
+
+    - name: Upload Python wheel
+      shell: bash -l {0}
+      if: github.ref == 'refs/heads/master' || contains(github.ref, 'refs/heads/release_')
+      run: |
+        python -m awscli s3 cp python-package/dist/*.whl s3://xgboost-nightly-builds/${{ steps.extract_branch.outputs.branch }}/ --acl public-read
+      env:
+        AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID_IAM_S3_UPLOADER }}
+        AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY_IAM_S3_UPLOADER }}

.github/workflows/r_tests.yml

@@ -3,7 +3,7 @@ name: XGBoost-R-Tests
 on: [push, pull_request]
 
 env:
-  R_PACKAGES: c('XML', 'igraph', 'data.table', 'ggplot2', 'DiagrammeR', 'Ckmeans.1d.dp', 'vcd', 'testthat', 'lintr', 'knitr', 'rmarkdown', 'e1071', 'cplm', 'devtools', 'float', 'titanic')
+  R_PACKAGES: c('XML', 'data.table', 'ggplot2', 'DiagrammeR', 'Ckmeans.1d.dp', 'vcd', 'testthat', 'lintr', 'knitr', 'rmarkdown', 'e1071', 'cplm', 'devtools', 'float', 'titanic')
   GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
 
 jobs:
@@ -40,6 +40,11 @@ jobs:
         install.packages(${{ env.R_PACKAGES }},
                          repos = 'http://cloud.r-project.org',
                          dependencies = c('Depends', 'Imports', 'LinkingTo'))
+    - name: Install igraph on Windows
+      shell: Rscript {0}
+      if: matrix.config.os == 'windows-latest'
+      run: |
+        install.packages('igraph', type='binary')
 
     - name: Run lintr
       run: |
@@ -83,6 +88,11 @@ jobs:
         install.packages(${{ env.R_PACKAGES }},
                          repos = 'http://cloud.r-project.org',
                          dependencies = c('Depends', 'Imports', 'LinkingTo'))
+    - name: Install igraph on Windows
+      shell: Rscript {0}
+      if: matrix.config.os == 'windows-2016'
+      run: |
+        install.packages('igraph', type='binary', dependencies = c('Depends', 'Imports', 'LinkingTo'))
 
     - uses: actions/setup-python@v2
       with:
@@ -91,7 +101,7 @@ jobs:
 
     - name: Test R
       run: |
-        python tests/ci_build/test_r_package.py --compiler="${{ matrix.config.compiler }}" --build-tool="${{ matrix.config.build }}"
+        python tests/ci_build/test_r_package.py --compiler='${{ matrix.config.compiler }}' --build-tool='${{ matrix.config.build }}'
 
   test-R-CRAN:
     runs-on: ubuntu-latest
@@ -115,7 +125,7 @@ jobs:
 
     - name: Install system packages
       run: |
-        sudo apt-get update && sudo apt-get install libcurl4-openssl-dev libssl-dev libssh2-1-dev libgit2-dev pandoc pandoc-citeproc
+        sudo apt-get update && sudo apt-get install libcurl4-openssl-dev libssl-dev libssh2-1-dev libgit2-dev pandoc pandoc-citeproc libglpk-dev
 
     - name: Cache R packages
       uses: actions/cache@v2
@@ -130,6 +140,7 @@ jobs:
         install.packages(${{ env.R_PACKAGES }},
                          repos = 'http://cloud.r-project.org',
                          dependencies = c('Depends', 'Imports', 'LinkingTo'))
+        install.packages('igraph', repos = 'http://cloud.r-project.org', dependencies = c('Depends', 'Imports', 'LinkingTo'))
 
     - name: Check R Package
       run: |

.travis.yml

@@ -10,14 +10,6 @@ env:
 
 jobs:
   include:
-    - os: osx
-      arch: amd64
-      osx_image: xcode10.2
-      env: TASK=python_test
-    - os: osx
-      arch: amd64
-      osx_image: xcode10.2
-      env: TASK=java_test
     - os: linux
       arch: s390x
       env: TASK=s390x_test
@@ -33,8 +25,6 @@ addons:
 
 before_install:
   - source tests/travis/travis_setup_env.sh
-  - if [ "${TASK}" != "python_sdist_test" ]; then export PYTHONPATH=${PYTHONPATH}:${PWD}/python-package; fi
-  - echo "MAVEN_OPTS='-Xmx2g -XX:MaxPermSize=1024m -XX:ReservedCodeCacheSize=512m -Dorg.slf4j.simpleLogger.defaultLogLevel=error'" > ~/.mavenrc
 
 install:
   - source tests/travis/setup.sh

CMakeLists.txt

@@ -1,5 +1,5 @@
 cmake_minimum_required(VERSION 3.14 FATAL_ERROR)
-project(xgboost LANGUAGES CXX C VERSION 1.5.0)
+project(xgboost LANGUAGES CXX C VERSION 1.5.2)
 include(cmake/Utils.cmake)
 list(APPEND CMAKE_MODULE_PATH "${xgboost_SOURCE_DIR}/cmake/modules")
 cmake_policy(SET CMP0022 NEW)

R-package/DESCRIPTION

@@ -1,8 +1,8 @@
 Package: xgboost
 Type: Package
 Title: Extreme Gradient Boosting
-Version: 1.5.0.1
-Date: 2021-10-13
+Version: 1.5.2.1
+Date: 2022-1-17
 Authors@R: c(
   person("Tianqi", "Chen", role = c("aut"),
          email = "tianqi.tchen@gmail.com"),

R-package/R/xgb.Booster.R

@@ -397,6 +397,7 @@ predict.xgb.Booster <- function(object, newdata, missing = NA, outputmargin = FA
   shape <- predts$shape
   ret <- predts$results
 
+  n_ret <- length(ret)
   n_row <- nrow(newdata)
   if (n_row != shape[1]) {
     stop("Incorrect predict shape.")
@@ -405,36 +406,57 @@ predict.xgb.Booster <- function(object, newdata, missing = NA, outputmargin = FA
   arr <- array(data = ret, dim = rev(shape))
 
   cnames <- if (!is.null(colnames(newdata))) c(colnames(newdata), "BIAS") else NULL
+  n_groups <- shape[2]
+
+  ## Needed regardless of whether strict shape is being used.
   if (predcontrib) {
     dimnames(arr) <- list(cnames, NULL, NULL)
-    if (!strict_shape) {
-      arr <- aperm(a = arr, perm = c(2, 3, 1)) # [group, row, col]
-    }
   } else if (predinteraction) {
     dimnames(arr) <- list(cnames, cnames, NULL, NULL)
-    if (!strict_shape) {
-      arr <- aperm(a = arr, perm = c(3, 4, 1, 2)) # [group, row, col, col]
-    }
+  }
+  if (strict_shape) {
+    return(arr) # strict shape is calculated by libxgboost uniformly.
   }
 
-  if (!strict_shape) {
-    n_groups <- shape[2]
-    if (predleaf) {
-      arr <- matrix(arr, nrow = n_row, byrow = TRUE)
-    } else if (predcontrib && n_groups != 1) {
-      arr <- lapply(seq_len(n_groups), function(g) arr[g, , ])
-    } else if (predinteraction && n_groups != 1) {
-      arr <- lapply(seq_len(n_groups), function(g) arr[g, , , ])
-    } else if (!reshape && n_groups != 1) {
-      arr <- ret
-    } else if (reshape && n_groups != 1) {
-      arr <- matrix(arr, ncol = n_groups, byrow = TRUE)
+  if (predleaf) {
+    ## Predict leaf
+    arr <- if (n_ret == n_row) {
+      matrix(arr, ncol = 1)
+    } else {
+      matrix(arr, nrow = n_row, byrow = TRUE)
     }
-    arr <- drop(arr)
-    if (length(dim(arr)) == 1) {
-      arr <- as.vector(arr)
-    } else if (length(dim(arr)) == 2) {
-      arr <- as.matrix(arr)
+  } else if (predcontrib) {
+    ## Predict contribution
+    arr <- aperm(a = arr, perm = c(2, 3, 1)) # [group, row, col]
+    arr <- if (n_ret == n_row) {
+      matrix(arr, ncol =  1, dimnames = list(NULL, cnames))
+    } else if (n_groups != 1) {
+      ## turns array into list of matrices
+      lapply(seq_len(n_groups), function(g) arr[g, , ])
+    } else {
+      ## remove the first axis (group)
+      dn <- dimnames(arr)
+      matrix(arr[1, , ], nrow = dim(arr)[2], ncol = dim(arr)[3], dimnames = c(dn[2], dn[3]))
+    }
+  } else if (predinteraction) {
+    ## Predict interaction
+    arr <- aperm(a = arr, perm = c(3, 4, 1, 2)) # [group, row, col, col]
+    arr <- if (n_ret == n_row) {
+      matrix(arr, ncol = 1, dimnames = list(NULL, cnames))
+    } else if (n_groups != 1) {
+      ## turns array into list of matrices
+      lapply(seq_len(n_groups), function(g) arr[g, , , ])
+    } else {
+      ## remove the first axis (group)
+      arr <- arr[1, , , , drop = FALSE]
+      array(arr, dim = dim(arr)[2:4], dimnames(arr)[2:4])
+    }
+  } else {
+    ## Normal prediction
+    arr <- if (reshape && n_groups != 1) {
+      matrix(arr, ncol = n_groups, byrow = TRUE)
+    } else {
+      as.vector(ret)
     }
   }
   return(arr)

R-package/R/xgb.importance.R

@@ -115,14 +115,14 @@ xgb.importance <- function(feature_names = NULL, model = NULL, trees = NULL,
   } else {
     concatenated <- list()
     output_names <- vector()
-    for (importance_type in c("weight", "gain", "cover")) {
-      args <- list(importance_type = importance_type, feature_names = feature_names)
+    for (importance_type in c("weight", "total_gain", "total_cover")) {
+      args <- list(importance_type = importance_type, feature_names = feature_names, tree_idx = trees)
       results <- .Call(
         XGBoosterFeatureScore_R, model$handle, jsonlite::toJSON(args, auto_unbox = TRUE, null = "null")
       )
       names(results) <- c("features", "shape", importance_type)
       concatenated[
-        switch(importance_type, "weight" = "Frequency", "gain" = "Gain", "cover" = "Cover")
+        switch(importance_type, "weight" = "Frequency", "total_gain" = "Gain", "total_cover" = "Cover")
       ] <- results[importance_type]
       output_names <- results$features
     }

R-package/R/xgboost.R

@@ -9,8 +9,8 @@ xgboost <- function(data = NULL, label = NULL, missing = NA, weight = NULL,
                     early_stopping_rounds = NULL, maximize = NULL,
                     save_period = NULL, save_name = "xgboost.model",
                     xgb_model = NULL, callbacks = list(), ...) {
-
-  dtrain <- xgb.get.DMatrix(data, label, missing, weight, nthread = params$nthread)
+  merged <- check.booster.params(params, ...)
+  dtrain <- xgb.get.DMatrix(data, label, missing, weight, nthread = merged$nthread)
 
   watchlist <- list(train = dtrain)
 

R-package/tests/testthat/test_glm.R

@@ -46,3 +46,31 @@ test_that("gblinear works", {
   expect_equal(dim(h), c(n, ncol(dtrain) + 1))
   expect_s4_class(h, "dgCMatrix")
 })
+
+test_that("gblinear early stopping works", {
+  data(agaricus.train, package = 'xgboost')
+  data(agaricus.test, package = 'xgboost')
+  dtrain <- xgb.DMatrix(agaricus.train$data, label = agaricus.train$label)
+  dtest <- xgb.DMatrix(agaricus.test$data, label = agaricus.test$label)
+
+  param <- list(
+    objective = "binary:logistic", eval_metric = "error", booster = "gblinear",
+    nthread = 2, eta = 0.8, alpha = 0.0001, lambda = 0.0001,
+    updater = "coord_descent"
+  )
+
+  es_round <- 1
+  n <- 10
+  booster <- xgb.train(
+    param, dtrain, n, list(eval = dtest, train = dtrain), early_stopping_rounds = es_round
+  )
+  expect_equal(booster$best_iteration, 5)
+  predt_es <- predict(booster, dtrain)
+
+  n <- booster$best_iteration + es_round
+  booster <- xgb.train(
+    param, dtrain, n, list(eval = dtest, train = dtrain), early_stopping_rounds = es_round
+  )
+  predt <- predict(booster, dtrain)
+  expect_equal(predt_es, predt)
+})