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merge v2.0.3 from upstream

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This commit is contained in:
Hui Liu 2024-01-25 07:40:06 -08:00
commit 420f8d6fde
31 changed files with 542 additions and 163 deletions
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2
CMakeLists.txt
View File

@ -1,5 +1,5 @@
cmake_minimum_required(VERSION 3.18 FATAL_ERROR)
project(xgboost LANGUAGES CXX C VERSION 2.0.1)
project(xgboost LANGUAGES CXX C VERSION 2.0.3)
include(cmake/Utils.cmake)
list(APPEND CMAKE_MODULE_PATH "${xgboost_SOURCE_DIR}/cmake/modules")
cmake_policy(SET CMP0022 NEW)

4
R-package/DESCRIPTION
View File

@ -1,8 +1,8 @@
Package: xgboost
Type: Package
Title: Extreme Gradient Boosting
Version: 2.0.1.1
Date: 2023-10-12
Version: 2.0.3.1
Date: 2023-12-14
Authors@R: c(
person("Tianqi", "Chen", role = c("aut"),
email = "tianqi.tchen@gmail.com"),

18
R-package/configure vendored
View File

@ -1,6 +1,6 @@
#! /bin/sh
# Guess values for system-dependent variables and create Makefiles.
# Generated by GNU Autoconf 2.71 for xgboost 2.0.1.
# Generated by GNU Autoconf 2.71 for xgboost 2.0.3.
#
#
# Copyright (C) 1992-1996, 1998-2017, 2020-2021 Free Software Foundation,
@ -607,8 +607,8 @@ MAKEFLAGS=
# Identity of this package.
PACKAGE_NAME='xgboost'
PACKAGE_TARNAME='xgboost'
PACKAGE_VERSION='2.0.1'
PACKAGE_STRING='xgboost 2.0.1'
PACKAGE_VERSION='2.0.3'
PACKAGE_STRING='xgboost 2.0.3'
PACKAGE_BUGREPORT=''
PACKAGE_URL=''
@ -1225,7 +1225,7 @@ if test "$ac_init_help" = "long"; then
# Omit some internal or obsolete options to make the list less imposing.
# This message is too long to be a string in the A/UX 3.1 sh.
cat <<_ACEOF
\`configure' configures xgboost 2.0.1 to adapt to many kinds of systems.
\`configure' configures xgboost 2.0.3 to adapt to many kinds of systems.
Usage: $0 [OPTION]... [VAR=VALUE]...
@ -1287,7 +1287,7 @@ fi
if test -n "$ac_init_help"; then
case $ac_init_help in
short | recursive ) echo "Configuration of xgboost 2.0.1:";;
short | recursive ) echo "Configuration of xgboost 2.0.3:";;
esac
cat <<\_ACEOF
@ -1367,7 +1367,7 @@ fi
test -n "$ac_init_help" && exit $ac_status
if $ac_init_version; then
cat <<\_ACEOF
xgboost configure 2.0.1
xgboost configure 2.0.3
generated by GNU Autoconf 2.71
Copyright (C) 2021 Free Software Foundation, Inc.
@ -1533,7 +1533,7 @@ cat >config.log <<_ACEOF
This file contains any messages produced by compilers while
running configure, to aid debugging if configure makes a mistake.
It was created by xgboost $as_me 2.0.1, which was
It was created by xgboost $as_me 2.0.3, which was
generated by GNU Autoconf 2.71. Invocation command line was
$ $0$ac_configure_args_raw
@ -3412,7 +3412,7 @@ cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1
# report actual input values of CONFIG_FILES etc. instead of their
# values after options handling.
ac_log="
This file was extended by xgboost $as_me 2.0.1, which was
This file was extended by xgboost $as_me 2.0.3, which was
generated by GNU Autoconf 2.71. Invocation command line was
CONFIG_FILES = $CONFIG_FILES
@ -3467,7 +3467,7 @@ ac_cs_config_escaped=`printf "%s\n" "$ac_cs_config" | sed "s/^ //; s/'/'\\\\\\\\
cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1
ac_cs_config='$ac_cs_config_escaped'
ac_cs_version="\\
xgboost config.status 2.0.1
xgboost config.status 2.0.3
configured by $0, generated by GNU Autoconf 2.71,
with options \\"\$ac_cs_config\\"

2
R-package/configure.ac
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@ -2,7 +2,7 @@
AC_PREREQ(2.69)
AC_INIT([xgboost],[2.0.1],[],[xgboost],[])
AC_INIT([xgboost],[2.0.3],[],[xgboost],[])
: ${R_HOME=`R RHOME`}
if test -z "${R_HOME}"; then

79
dev/change_scala_version.py Normal file
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@ -0,0 +1,79 @@
import argparse
import pathlib
import re
import shutil
def main(args):
if args.scala_version == "2.12":
scala_ver = "2.12"
scala_patchver = "2.12.18"
elif args.scala_version == "2.13":
scala_ver = "2.13"
scala_patchver = "2.13.11"
else:
raise ValueError(f"Unsupported Scala version: {args.scala_version}")
# Clean artifacts
if args.purge_artifacts:
for target in pathlib.Path("jvm-packages/").glob("**/target"):
if target.is_dir():
print(f"Removing {target}...")
shutil.rmtree(target)
# Update pom.xml
for pom in pathlib.Path("jvm-packages/").glob("**/pom.xml"):
print(f"Updating {pom}...")
with open(pom, "r", encoding="utf-8") as f:
lines = f.readlines()
with open(pom, "w", encoding="utf-8") as f:
replaced_scalaver = False
replaced_scala_binver = False
for line in lines:
for artifact in [
"xgboost-jvm",
"xgboost4j",
"xgboost4j-gpu",
"xgboost4j-spark",
"xgboost4j-spark-gpu",
"xgboost4j-flink",
"xgboost4j-example",
]:
line = re.sub(
f"<artifactId>{artifact}_[0-9\\.]*",
f"<artifactId>{artifact}_{scala_ver}",
line,
)
# Only replace the first occurrence of scala.version
if not replaced_scalaver:
line, nsubs = re.subn(
r"<scala.version>[0-9\.]*",
f"<scala.version>{scala_patchver}",
line,
)
if nsubs > 0:
replaced_scalaver = True
# Only replace the first occurrence of scala.binary.version
if not replaced_scala_binver:
line, nsubs = re.subn(
r"<scala.binary.version>[0-9\.]*",
f"<scala.binary.version>{scala_ver}",
line,
)
if nsubs > 0:
replaced_scala_binver = True
f.write(line)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--purge-artifacts", action="store_true")
parser.add_argument(
"--scala-version",
type=str,
required=True,
help="Version of Scala to use in the JVM packages",
choices=["2.12", "2.13"],
)
parsed_args = parser.parse_args()
main(parsed_args)

148
dev/prepare_jvm_release.py
View File

@ -2,7 +2,6 @@ import argparse
import errno
import glob
import os
import platform
import re
import shutil
import subprocess
@ -21,12 +20,14 @@ def normpath(path):
else:
return normalized
def cp(source, target):
source = normpath(source)
target = normpath(target)
print("cp {0} {1}".format(source, target))
shutil.copy(source, target)
def maybe_makedirs(path):
path = normpath(path)
print("mkdir -p " + path)
@ -36,6 +37,7 @@ def maybe_makedirs(path):
if e.errno != errno.EEXIST:
raise
@contextmanager
def cd(path):
path = normpath(path)
@ -47,18 +49,22 @@ def cd(path):
finally:
os.chdir(cwd)
def run(command, **kwargs):
print(command)
subprocess.check_call(command, shell=True, **kwargs)
def get_current_git_tag():
out = subprocess.check_output(["git", "tag", "--points-at", "HEAD"])
return out.decode().split("\n")[0]
def get_current_commit_hash():
out = subprocess.check_output(["git", "rev-parse", "HEAD"])
return out.decode().split("\n")[0]
def get_current_git_branch():
out = subprocess.check_output(["git", "log", "-n", "1", "--pretty=%d", "HEAD"])
m = re.search(r"release_[0-9\.]+", out.decode())
@ -66,38 +72,49 @@ def get_current_git_branch():
raise ValueError("Expected branch name of form release_xxx")
return m.group(0)
def retrieve(url, filename=None):
print(f"{url} -> {filename}")
return urlretrieve(url, filename)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--release-version", type=str, required=True,
help="Version of the release being prepared")
parser.add_argument(
"--release-version",
type=str,
required=True,
help="Version of the release being prepared",
)
args = parser.parse_args()
if sys.platform != "darwin" or platform.machine() != "x86_64":
raise NotImplementedError("Please run this script using an Intel Mac")
version = args.release_version
expected_git_tag = "v" + version
current_git_tag = get_current_git_tag()
if current_git_tag != expected_git_tag:
if not current_git_tag:
raise ValueError(f"Expected git tag {expected_git_tag} but current HEAD has no tag. "
f"Run: git checkout {expected_git_tag}")
raise ValueError(f"Expected git tag {expected_git_tag} but current HEAD is at tag "
f"{current_git_tag}. Run: git checkout {expected_git_tag}")
raise ValueError(
f"Expected git tag {expected_git_tag} but current HEAD has no tag. "
f"Run: git checkout {expected_git_tag}"
)
raise ValueError(
f"Expected git tag {expected_git_tag} but current HEAD is at tag "
f"{current_git_tag}. Run: git checkout {expected_git_tag}"
)
commit_hash = get_current_commit_hash()
git_branch = get_current_git_branch()
print(f"Using commit {commit_hash} of branch {git_branch}, git tag {current_git_tag}")
print(
f"Using commit {commit_hash} of branch {git_branch}, git tag {current_git_tag}"
)
with cd("jvm-packages/"):
print("====copying pure-Python tracker====")
for use_cuda in [True, False]:
xgboost4j = "xgboost4j-gpu" if use_cuda else "xgboost4j"
cp("../python-package/xgboost/tracker.py", f"{xgboost4j}/src/main/resources")
cp(
"../python-package/xgboost/tracker.py",
f"{xgboost4j}/src/main/resources",
)
print("====copying resources for testing====")
with cd("../demo/CLI/regression"):
@ -115,7 +132,12 @@ def main():
cp(file, f"{xgboost4j_spark}/src/test/resources")
print("====Creating directories to hold native binaries====")
for os_ident, arch in [("linux", "x86_64"), ("windows", "x86_64"), ("macos", "x86_64")]:
for os_ident, arch in [
("linux", "x86_64"),
("windows", "x86_64"),
("macos", "x86_64"),
("macos", "aarch64"),
]:
output_dir = f"xgboost4j/src/main/resources/lib/{os_ident}/{arch}"
maybe_makedirs(output_dir)
for os_ident, arch in [("linux", "x86_64")]:
@ -123,52 +145,98 @@ def main():
maybe_makedirs(output_dir)
print("====Downloading native binaries from CI====")
nightly_bucket_prefix = "https://s3-us-west-2.amazonaws.com/xgboost-nightly-builds"
maven_repo_prefix = "https://s3-us-west-2.amazonaws.com/xgboost-maven-repo/release/ml/dmlc"
nightly_bucket_prefix = (
"https://s3-us-west-2.amazonaws.com/xgboost-nightly-builds"
)
maven_repo_prefix = (
"https://s3-us-west-2.amazonaws.com/xgboost-maven-repo/release/ml/dmlc"
)
retrieve(url=f"{nightly_bucket_prefix}/{git_branch}/xgboost4j_{commit_hash}.dll",
filename="xgboost4j/src/main/resources/lib/windows/x86_64/xgboost4j.dll")
retrieve(
url=f"{nightly_bucket_prefix}/{git_branch}/libxgboost4j/xgboost4j_{commit_hash}.dll",
filename="xgboost4j/src/main/resources/lib/windows/x86_64/xgboost4j.dll",
)
retrieve(
url=f"{nightly_bucket_prefix}/{git_branch}/libxgboost4j/libxgboost4j_{commit_hash}.dylib",
filename="xgboost4j/src/main/resources/lib/macos/x86_64/libxgboost4j.dylib",
)
retrieve(
url=f"{nightly_bucket_prefix}/{git_branch}/libxgboost4j/libxgboost4j_m1_{commit_hash}.dylib",
filename="xgboost4j/src/main/resources/lib/macos/aarch64/libxgboost4j.dylib",
)
with tempfile.TemporaryDirectory() as tempdir:
# libxgboost4j.so for Linux x86_64, CPU only
zip_path = os.path.join(tempdir, "xgboost4j_2.12.jar")
extract_dir = os.path.join(tempdir, "xgboost4j")
retrieve(url=f"{maven_repo_prefix}/xgboost4j_2.12/{version}/"
f"xgboost4j_2.12-{version}.jar",
filename=zip_path)
retrieve(
url=f"{maven_repo_prefix}/xgboost4j_2.12/{version}/"
f"xgboost4j_2.12-{version}.jar",
filename=zip_path,
)
os.mkdir(extract_dir)
with zipfile.ZipFile(zip_path, "r") as t:
t.extractall(extract_dir)
cp(os.path.join(extract_dir, "lib", "linux", "x86_64", "libxgboost4j.so"),
"xgboost4j/src/main/resources/lib/linux/x86_64/libxgboost4j.so")
cp(
os.path.join(extract_dir, "lib", "linux", "x86_64", "libxgboost4j.so"),
"xgboost4j/src/main/resources/lib/linux/x86_64/libxgboost4j.so",
)
# libxgboost4j.so for Linux x86_64, GPU support
zip_path = os.path.join(tempdir, "xgboost4j-gpu_2.12.jar")
extract_dir = os.path.join(tempdir, "xgboost4j-gpu")
retrieve(url=f"{maven_repo_prefix}/xgboost4j-gpu_2.12/{version}/"
f"xgboost4j-gpu_2.12-{version}.jar",
filename=zip_path)
retrieve(
url=f"{maven_repo_prefix}/xgboost4j-gpu_2.12/{version}/"
f"xgboost4j-gpu_2.12-{version}.jar",
filename=zip_path,
)
os.mkdir(extract_dir)
with zipfile.ZipFile(zip_path, "r") as t:
t.extractall(extract_dir)
cp(os.path.join(extract_dir, "lib", "linux", "x86_64", "libxgboost4j.so"),
"xgboost4j-gpu/src/main/resources/lib/linux/x86_64/libxgboost4j.so")
cp(
os.path.join(extract_dir, "lib", "linux", "x86_64", "libxgboost4j.so"),
"xgboost4j-gpu/src/main/resources/lib/linux/x86_64/libxgboost4j.so",
)
print("====Next Steps====")
print("1. Gain upload right to Maven Central repo.")
print("1-1. Sign up for a JIRA account at Sonatype: ")
print("1-2. File a JIRA ticket: "
"https://issues.sonatype.org/secure/CreateIssue.jspa?issuetype=21&pid=10134. Example: "
"https://issues.sonatype.org/browse/OSSRH-67724")
print("2. Store the Sonatype credentials in .m2/settings.xml. See insturctions in "
"https://central.sonatype.org/publish/publish-maven/")
print("3. Now on a Mac machine, run:")
print(" GPG_TTY=$(tty) mvn deploy -Prelease -DskipTests")
print("4. Log into https://oss.sonatype.org/. On the left menu panel, click Staging "
"Repositories. Visit the URL https://oss.sonatype.org/content/repositories/mldmlc-1085 "
"to inspect the staged JAR files. Finally, press Release button to publish the "
"artifacts to the Maven Central repository.")
print(
"1-2. File a JIRA ticket: "
"https://issues.sonatype.org/secure/CreateIssue.jspa?issuetype=21&pid=10134. Example: "
"https://issues.sonatype.org/browse/OSSRH-67724"
)
print(
"2. Store the Sonatype credentials in .m2/settings.xml. See insturctions in "
"https://central.sonatype.org/publish/publish-maven/"
)
print(
"3. Now on a Linux machine, run the following to build Scala 2.12 artifacts. "
"Make sure to use an Internet connection with fast upload speed:"
)
print(
" # Skip native build, since we have all needed native binaries from CI\n"
" export MAVEN_SKIP_NATIVE_BUILD=1\n"
" GPG_TTY=$(tty) mvn deploy -Prelease -DskipTests"
)
print(
"4. Log into https://oss.sonatype.org/. On the left menu panel, click Staging "
"Repositories. Visit the URL https://oss.sonatype.org/content/repositories/mldmlc-xxxx "
"to inspect the staged JAR files. Finally, press Release button to publish the "
"artifacts to the Maven Central repository. The top-level metapackage should be "
"named xgboost-jvm_2.12."
)
print(
"5. Remove the Scala 2.12 artifacts and build Scala 2.13 artifacts:\n"
" export MAVEN_SKIP_NATIVE_BUILD=1\n"
" python dev/change_scala_version.py --scala-version 2.13 --purge-artifacts\n"
" GPG_TTY=$(tty) mvn deploy -Prelease-cpu-only,scala-2.13 -DskipTests"
)
print(
"6. Go to https://oss.sonatype.org/ to release the Scala 2.13 artifacts. "
"The top-level metapackage should be named xgboost-jvm_2.13."
)
if __name__ == "__main__":
main()

2
include/xgboost/version_config.h
View File

@ -6,6 +6,6 @@
#define XGBOOST_VER_MAJOR 2 /* NOLINT */
#define XGBOOST_VER_MINOR 0 /* NOLINT */
#define XGBOOST_VER_PATCH 1 /* NOLINT */
#define XGBOOST_VER_PATCH 3 /* NOLINT */
#endif // XGBOOST_VERSION_CONFIG_H_

72
jvm-packages/create_jni.py
View File

@ -1,6 +1,6 @@
#!/usr/bin/env python
import errno
import argparse
import errno
import glob
import os
import platform
@ -19,13 +19,12 @@ CONFIG = {
"USE_HDFS": "OFF",
"USE_AZURE": "OFF",
"USE_S3": "OFF",
"USE_CUDA": "OFF",
"USE_NCCL": "OFF",
"USE_HIP": "OFF",
"USE_RCCL": "OFF",
"JVM_BINDINGS": "ON",
"LOG_CAPI_INVOCATION": "OFF"
"LOG_CAPI_INVOCATION": "OFF",
}
@ -72,27 +71,22 @@ def normpath(path):
return normalized
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--log-capi-invocation', type=str, choices=['ON', 'OFF'], default='OFF')
parser.add_argument('--use-cuda', type=str, choices=['ON', 'OFF'], default='OFF')
parser.add_argument('--use-hip', type=str, choices=['ON', 'OFF'], default='OFF')
cli_args = parser.parse_args()
def native_build(args):
if sys.platform == "darwin":
# Enable of your compiler supports OpenMP.
CONFIG["USE_OPENMP"] = "OFF"
os.environ["JAVA_HOME"] = subprocess.check_output(
"/usr/libexec/java_home").strip().decode()
os.environ["JAVA_HOME"] = (
subprocess.check_output("/usr/libexec/java_home").strip().decode()
)
print("building Java wrapper")
with cd(".."):
build_dir = 'build-gpu' if cli_args.use_cuda == 'ON' or cli_args.use_hip == 'ON' else 'build'
build_dir = "build-gpu" if cli_args.use_cuda == "ON" or cli_args.use_hip == "ON" else "build"
maybe_makedirs(build_dir)
with cd(build_dir):
if sys.platform == "win32":
# Force x64 build on Windows.
maybe_generator = ' -A x64'
maybe_generator = " -A x64"
else:
maybe_generator = ""
if sys.platform == "linux":
@ -100,15 +94,15 @@ if __name__ == "__main__":
else:
maybe_parallel_build = ""
if cli_args.log_capi_invocation == 'ON':
CONFIG['LOG_CAPI_INVOCATION'] = 'ON'
if cli_args.log_capi_invocation == "ON":
CONFIG["LOG_CAPI_INVOCATION"] = "ON"
if cli_args.use_cuda == 'ON':
CONFIG['USE_CUDA'] = 'ON'
CONFIG['USE_NCCL'] = 'ON'
elif cli_args.use_hip== 'ON':
CONFIG['USE_HIP'] = 'ON'
CONFIG['USE_RCCL'] = 'ON'
if cli_args.use_cuda == "ON":
CONFIG["USE_CUDA"] = "ON"
CONFIG["USE_NCCL"] = "ON"
elif cli_args.use_hip == "ON":
CONFIG["USE_HIP"] = "ON"
CONFIG["USE_RCCL"] = "ON"
args = ["-D{0}:BOOL={1}".format(k, v) for k, v in CONFIG.items()]
@ -121,7 +115,7 @@ if __name__ == "__main__":
if gpu_arch_flag is not None:
args.append("%s" % gpu_arch_flag)
lib_dir = os.path.join(os.pardir, 'lib')
lib_dir = os.path.join(os.pardir, "lib")
if os.path.exists(lib_dir):
shutil.rmtree(lib_dir)
run("cmake .. " + " ".join(args) + maybe_generator)
@ -131,8 +125,10 @@ if __name__ == "__main__":
run(f'"{sys.executable}" mapfeat.py')
run(f'"{sys.executable}" mknfold.py machine.txt 1')
xgboost4j = 'xgboost4j-gpu' if cli_args.use_cuda == 'ON' or cli_args.use_hip== 'ON' else 'xgboost4j'
xgboost4j_spark = 'xgboost4j-spark-gpu' if cli_args.use_cuda == 'ON' or cli_args.use_hip == 'ON' else 'xgboost4j-spark'
xgboost4j = "xgboost4j-gpu" if cli_args.use_cuda == "ON" or cli_args.use_hip == "ON" else "xgboost4j"
xgboost4j_spark = (
"xgboost4j-spark-gpu" if cli_args.use_cuda == "ON" or cli_args.use_hip == "ON" else "xgboost4j-spark"
)
print("copying native library")
library_name, os_folder = {
@ -147,14 +143,19 @@ if __name__ == "__main__":
"i86pc": "x86_64", # on Solaris x86_64
"sun4v": "sparc", # on Solaris sparc
"arm64": "aarch64", # on macOS & Windows ARM 64-bit
"aarch64": "aarch64"
"aarch64": "aarch64",
}[platform.machine().lower()]
output_folder = "{}/src/main/resources/lib/{}/{}".format(xgboost4j, os_folder, arch_folder)
output_folder = "{}/src/main/resources/lib/{}/{}".format(
xgboost4j, os_folder, arch_folder
)
maybe_makedirs(output_folder)
cp("../lib/" + library_name, output_folder)
print("copying pure-Python tracker")
cp("../python-package/xgboost/tracker.py", "{}/src/main/resources".format(xgboost4j))
cp(
"../python-package/xgboost/tracker.py",
"{}/src/main/resources".format(xgboost4j),
)
print("copying train/test files")
maybe_makedirs("{}/src/test/resources".format(xgboost4j_spark))
@ -170,3 +171,18 @@ if __name__ == "__main__":
maybe_makedirs("{}/src/test/resources".format(xgboost4j))
for file in glob.glob("../demo/data/agaricus.*"):
cp(file, "{}/src/test/resources".format(xgboost4j))
if __name__ == "__main__":
if "MAVEN_SKIP_NATIVE_BUILD" in os.environ:
print("MAVEN_SKIP_NATIVE_BUILD is set. Skipping native build...")
else:
parser = argparse.ArgumentParser()
parser.add_argument(
"--log-capi-invocation", type=str, choices=["ON", "OFF"], default="OFF"
)
parser.add_argument(
"--use-cuda", type=str, choices=["ON", "OFF"], default="OFF"
)
cli_args = parser.parse_args()
native_build(cli_args)

91
jvm-packages/pom.xml
View File

@ -5,8 +5,8 @@
<modelVersion>4.0.0</modelVersion>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost-jvm</artifactId>
<version>2.0.1</version>
<artifactId>xgboost-jvm_2.12</artifactId>
<version>2.0.3</version>
<packaging>pom</packaging>
<name>XGBoost JVM Package</name>
<description>JVM Package for XGBoost</description>
@ -190,6 +190,93 @@
</plugins>
</build>
</profile>
<profile>
<id>release-cpu-only</id>
<modules>
<module>xgboost4j</module>
<module>xgboost4j-example</module>
<module>xgboost4j-spark</module>
<module>xgboost4j-flink</module>
</modules>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-jar-plugin</artifactId>
<version>3.3.0</version>
<executions>
<execution>
<id>empty-javadoc-jar</id>
<phase>package</phase>
<goals>
<goal>jar</goal>
</goals>
<configuration>
<classifier>javadoc</classifier>
<classesDirectory>${basedir}/javadoc</classesDirectory>
</configuration>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-release-plugin</artifactId>
<version>3.0.1</version>
<configuration>
<autoVersionSubmodules>true</autoVersionSubmodules>
<useReleaseProfile>false</useReleaseProfile>
<releaseProfiles>release</releaseProfiles>
<goals>deploy</goals>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-gpg-plugin</artifactId>
<version>3.1.0</version>
<executions>
<execution>
<id>sign-artifacts</id>
<phase>verify</phase>
<goals>
<goal>sign</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-source-plugin</artifactId>
<version>3.3.0</version>
<executions>
<execution>
<id>attach-sources</id>
<goals>
<goal>jar-no-fork</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.sonatype.plugins</groupId>
<artifactId>nexus-staging-maven-plugin</artifactId>
<version>1.6.13</version>
<extensions>true</extensions>
<configuration>
<serverId>ossrh</serverId>
<nexusUrl>https://oss.sonatype.org/</nexusUrl>
<autoReleaseAfterClose>false</autoReleaseAfterClose>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-surefire-plugin</artifactId>
<configuration>
<skipTests>true</skipTests>
</configuration>
</plugin>
</plugins>
</build>
</profile>
<profile>
<id>assembly</id>
<build>

12
jvm-packages/xgboost4j-example/pom.xml
View File

@ -5,12 +5,12 @@
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost-jvm</artifactId>
<version>2.0.1</version>
<artifactId>xgboost-jvm_2.12</artifactId>
<version>2.0.3</version>
</parent>
<name>xgboost4j-example</name>
<artifactId>xgboost4j-example_${scala.binary.version}</artifactId>
<version>2.0.1</version>
<artifactId>xgboost4j-example_2.12</artifactId>
<version>2.0.3</version>
<packaging>jar</packaging>
<build>
<plugins>
@ -26,7 +26,7 @@
<dependencies>
<dependency>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost4j-spark_${scala.binary.version}</artifactId>
<artifactId>xgboost4j-spark_2.12</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
@ -37,7 +37,7 @@
</dependency>
<dependency>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost4j-flink_${scala.binary.version}</artifactId>
<artifactId>xgboost4j-flink_2.12</artifactId>
<version>${project.version}</version>
</dependency>
</dependencies>

10
jvm-packages/xgboost4j-flink/pom.xml
View File

@ -5,13 +5,13 @@
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost-jvm</artifactId>
<version>2.0.1</version>
<artifactId>xgboost-jvm_2.12</artifactId>
<version>2.0.3</version>
</parent>
<name>xgboost4j-flink</name>
<artifactId>xgboost4j-flink_${scala.binary.version}</artifactId>
<version>2.0.1</version>
<artifactId>xgboost4j-flink_2.12</artifactId>
<version>2.0.3</version>
<properties>
<flink-ml.version>2.2.0</flink-ml.version>
</properties>
@ -30,7 +30,7 @@
<dependencies>
<dependency>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost4j_${scala.binary.version}</artifactId>
<artifactId>xgboost4j_2.12</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>

8
jvm-packages/xgboost4j-gpu/pom.xml
View File

@ -5,12 +5,12 @@
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost-jvm</artifactId>
<version>2.0.1</version>
<artifactId>xgboost-jvm_2.12</artifactId>
<version>2.0.3</version>
</parent>
<artifactId>xgboost4j-gpu_${scala.binary.version}</artifactId>
<artifactId>xgboost4j-gpu_2.12</artifactId>
<name>xgboost4j-gpu</name>
<version>2.0.1</version>
<version>2.0.3</version>
<packaging>jar</packaging>
<dependencies>

8
jvm-packages/xgboost4j-spark-gpu/pom.xml
View File

@ -5,11 +5,11 @@
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost-jvm</artifactId>
<version>2.0.1</version>
<artifactId>xgboost-jvm_2.12</artifactId>
<version>2.0.3</version>
</parent>
<name>xgboost4j-spark-gpu</name>
<artifactId>xgboost4j-spark-gpu_${scala.binary.version}</artifactId>
<artifactId>xgboost4j-spark-gpu_2.12</artifactId>
<build>
<plugins>
<plugin>
@ -24,7 +24,7 @@
<dependencies>
<dependency>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost4j-gpu_${scala.binary.version}</artifactId>
<artifactId>xgboost4j-gpu_2.12</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>

8
jvm-packages/xgboost4j-spark/pom.xml
View File

@ -5,11 +5,11 @@
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost-jvm</artifactId>
<version>2.0.1</version>
<artifactId>xgboost-jvm_2.12</artifactId>
<version>2.0.3</version>
</parent>
<name>xgboost4j-spark</name>
<artifactId>xgboost4j-spark_${scala.binary.version}</artifactId>
<artifactId>xgboost4j-spark_2.12</artifactId>
<build>
<plugins>
<plugin>
@ -24,7 +24,7 @@
<dependencies>
<dependency>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost4j_${scala.binary.version}</artifactId>
<artifactId>xgboost4j_2.12</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>

8
jvm-packages/xgboost4j/pom.xml
View File

@ -5,12 +5,12 @@
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost-jvm</artifactId>
<version>2.0.1</version>
<artifactId>xgboost-jvm_2.12</artifactId>
<version>2.0.3</version>
</parent>
<name>xgboost4j</name>
<artifactId>xgboost4j_${scala.binary.version}</artifactId>
<version>2.0.1</version>
<artifactId>xgboost4j_2.12</artifactId>
<version>2.0.3</version>
<packaging>jar</packaging>
<dependencies>

2
python-package/pyproject.toml
View File

@ -7,7 +7,7 @@ build-backend = "packager.pep517"
[project]
name = "xgboost"
version = "2.0.1"
version = "2.0.3"
authors = [
{ name = "Hyunsu Cho", email = "chohyu01@cs.washington.edu" },
{ name = "Jiaming Yuan", email = "jm.yuan@outlook.com" }

2
python-package/xgboost/VERSION
View File

@ -1 +1 @@
2.0.1
2.0.3

1
python-package/xgboost/core.py
View File

@ -206,6 +206,7 @@ def _load_lib() -> ctypes.CDLL:
lib = ctypes.cdll.LoadLibrary(lib_path)
setattr(lib, "path", os.path.normpath(lib_path))
lib_success = True
break
except OSError as e:
os_error_list.append(str(e))
continue

7
python-package/xgboost/dask.py
View File

@ -78,7 +78,6 @@ from .data import _is_cudf_ser, _is_cupy_array
from .sklearn import (
XGBClassifier,
XGBClassifierBase,
XGBClassifierMixIn,
XGBModel,
XGBRanker,
XGBRankerMixIn,
@ -1854,7 +1853,7 @@ class DaskXGBRegressor(DaskScikitLearnBase, XGBRegressorBase):
"Implementation of the scikit-learn API for XGBoost classification.",
["estimators", "model"],
)
class DaskXGBClassifier(DaskScikitLearnBase, XGBClassifierMixIn, XGBClassifierBase):
class DaskXGBClassifier(DaskScikitLearnBase, XGBClassifierBase):
# pylint: disable=missing-class-docstring
async def _fit_async(
self,
@ -2036,10 +2035,6 @@ class DaskXGBClassifier(DaskScikitLearnBase, XGBClassifierMixIn, XGBClassifierBa
preds = da.map_blocks(_argmax, pred_probs, drop_axis=1)
return preds
def load_model(self, fname: ModelIn) -> None:
super().load_model(fname)
self._load_model_attributes(self.get_booster())
@xgboost_model_doc(
"""Implementation of the Scikit-Learn API for XGBoost Ranking.

66
python-package/xgboost/sklearn.py
View File

@ -43,19 +43,6 @@ from .data import _is_cudf_df, _is_cudf_ser, _is_cupy_array, _is_pandas_df
from .training import train
class XGBClassifierMixIn: # pylint: disable=too-few-public-methods
"""MixIn for classification."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
def _load_model_attributes(self, booster: Booster) -> None:
config = json.loads(booster.save_config())
self.n_classes_ = int(config["learner"]["learner_model_param"]["num_class"])
# binary classification is treated as regression in XGBoost.
self.n_classes_ = 2 if self.n_classes_ < 2 else self.n_classes_
class XGBRankerMixIn: # pylint: disable=too-few-public-methods
"""MixIn for ranking, defines the _estimator_type usually defined in scikit-learn
base classes.
@ -845,21 +832,38 @@ class XGBModel(XGBModelBase):
self.get_booster().load_model(fname)
meta_str = self.get_booster().attr("scikit_learn")
if meta_str is None:
return
if meta_str is not None:
meta = json.loads(meta_str)
t = meta.get("_estimator_type", None)
if t is not None and t != self._get_type():
raise TypeError(
"Loading an estimator with different type. Expecting: "
f"{self._get_type()}, got: {t}"
)
meta = json.loads(meta_str)
t = meta.get("_estimator_type", None)
if t is not None and t != self._get_type():
raise TypeError(
"Loading an estimator with different type. Expecting: "
f"{self._get_type()}, got: {t}"
)
self.feature_types = self.get_booster().feature_types
self.get_booster().set_attr(scikit_learn=None)
config = json.loads(self.get_booster().save_config())
self._load_model_attributes(config)
load_model.__doc__ = f"""{Booster.load_model.__doc__}"""
def _load_model_attributes(self, config: dict) -> None:
"""Load model attributes without hyper-parameters."""
from sklearn.base import is_classifier
booster = self.get_booster()
self.objective = config["learner"]["objective"]["name"]
self.booster = config["learner"]["gradient_booster"]["name"]
self.base_score = config["learner"]["learner_model_param"]["base_score"]
self.feature_types = booster.feature_types
if is_classifier(self):
self.n_classes_ = int(config["learner"]["learner_model_param"]["num_class"])
# binary classification is treated as regression in XGBoost.
self.n_classes_ = 2 if self.n_classes_ < 2 else self.n_classes_
# pylint: disable=too-many-branches
def _configure_fit(
self,
@ -1409,7 +1413,7 @@ def _cls_predict_proba(n_classes: int, prediction: PredtT, vstack: Callable) ->
Number of boosting rounds.
""",
)
class XGBClassifier(XGBModel, XGBClassifierMixIn, XGBClassifierBase):
class XGBClassifier(XGBModel, XGBClassifierBase):
# pylint: disable=missing-docstring,invalid-name,too-many-instance-attributes
@_deprecate_positional_args
def __init__(
@ -1637,10 +1641,6 @@ class XGBClassifier(XGBModel, XGBClassifierMixIn, XGBClassifierBase):
def classes_(self) -> np.ndarray:
return np.arange(self.n_classes_)
def load_model(self, fname: ModelIn) -> None:
super().load_model(fname)
self._load_model_attributes(self.get_booster())
@xgboost_model_doc(
"scikit-learn API for XGBoost random forest classification.",
@ -2093,7 +2093,17 @@ class XGBRanker(XGBModel, XGBRankerMixIn):
"""
X, qid = _get_qid(X, None)
Xyq = DMatrix(X, y, qid=qid)
# fixme(jiamingy): base margin and group weight is not yet supported. We might
# need to make extra special fields in the dataframe.
Xyq = DMatrix(
X,
y,
qid=qid,
missing=self.missing,
enable_categorical=self.enable_categorical,
nthread=self.n_jobs,
feature_types=self.feature_types,
)
if callable(self.eval_metric):
metric = ltr_metric_decorator(self.eval_metric, self.n_jobs)
result_str = self.get_booster().eval_set([(Xyq, "eval")], feval=metric)

25
python-package/xgboost/testing/ranking.py
View File

@ -75,3 +75,28 @@ def run_ranking_qid_df(impl: ModuleType, tree_method: str) -> None:
with pytest.raises(ValueError, match="Either `group` or `qid`."):
ranker.fit(df, y, eval_set=[(X, y)])
def run_ranking_categorical(device: str) -> None:
"""Test LTR with categorical features."""
from sklearn.model_selection import cross_val_score
X, y = tm.make_categorical(
n_samples=512, n_features=10, n_categories=3, onehot=False
)
rng = np.random.default_rng(1994)
qid = rng.choice(3, size=y.shape[0])
qid = np.sort(qid)
X["qid"] = qid
ltr = xgb.XGBRanker(enable_categorical=True, device=device)
ltr.fit(X, y)
score = ltr.score(X, y)
assert score > 0.9
ltr = xgb.XGBRanker(enable_categorical=True, device=device)
# test using the score function inside sklearn.
scores = cross_val_score(ltr, X, y)
for s in scores:
assert s > 0.7

7
tests/buildkite/build-jvm-packages.sh
View File

@ -8,13 +8,18 @@ echo "--- Build XGBoost JVM packages scala 2.12"
tests/ci_build/ci_build.sh jvm docker tests/ci_build/build_jvm_packages.sh \
${SPARK_VERSION}
echo "--- Stash XGBoost4J JARs (Scala 2.12)"
buildkite-agent artifact upload "jvm-packages/xgboost4j/target/*.jar"
buildkite-agent artifact upload "jvm-packages/xgboost4j-spark/target/*.jar"
buildkite-agent artifact upload "jvm-packages/xgboost4j-flink/target/*.jar"
buildkite-agent artifact upload "jvm-packages/xgboost4j-example/target/*.jar"
echo "--- Build XGBoost JVM packages scala 2.13"
tests/ci_build/ci_build.sh jvm docker tests/ci_build/build_jvm_packages.sh \
${SPARK_VERSION} "" "" "true"
echo "--- Stash XGBoost4J JARs"
echo "--- Stash XGBoost4J JARs (Scala 2.13)"
buildkite-agent artifact upload "jvm-packages/xgboost4j/target/*.jar"
buildkite-agent artifact upload "jvm-packages/xgboost4j-spark/target/*.jar"
buildkite-agent artifact upload "jvm-packages/xgboost4j-flink/target/*.jar"

8
tests/buildkite/pipeline-mac-m1.yml Normal file
View File

@ -0,0 +1,8 @@
steps:
- block: ":rocket: Run this test job"
if: build.pull_request.id != null || build.branch =~ /^dependabot\//
- label: ":macos: Build and Test XGBoost for MacOS M1 with Clang 11"
command: "tests/buildkite/test-macos-m1-clang11.sh"
key: mac-m1-appleclang11
agents:
queue: mac-mini-m1

50
tests/buildkite/test-macos-m1-clang11.sh Executable file
View File

@ -0,0 +1,50 @@
#!/bin/bash
set -euo pipefail
source tests/buildkite/conftest.sh
# Display system info
echo "--- Display system information"
set -x
system_profiler SPSoftwareDataType
sysctl -n machdep.cpu.brand_string
uname -m
set +x
# Build XGBoost4J binary
echo "--- Build libxgboost4j.dylib"
set -x
mkdir build
pushd build
export JAVA_HOME=$(/usr/libexec/java_home)
cmake .. -GNinja -DJVM_BINDINGS=ON -DUSE_OPENMP=OFF -DCMAKE_OSX_DEPLOYMENT_TARGET=10.15
ninja -v
popd
rm -rf build
set +x
echo "--- Upload Python wheel"
set -x
pushd lib
mv -v libxgboost4j.dylib libxgboost4j_m1_${BUILDKITE_COMMIT}.dylib
buildkite-agent artifact upload libxgboost4j_m1_${BUILDKITE_COMMIT}.dylib
if [[ ($is_pull_request == 0) && ($is_release_branch == 1) ]]
then
aws s3 cp libxgboost4j_m1_${BUILDKITE_COMMIT}.dylib \
s3://xgboost-nightly-builds/${BRANCH_NAME}/libxgboost4j/ \
--acl public-read --no-progress
fi
popd
set +x
# Ensure that XGBoost can be built with Clang 11
echo "--- Build and Test XGBoost with MacOS M1, Clang 11"
set -x
LLVM11_PATH=$(brew --prefix llvm\@11)
mkdir build
pushd build
cmake .. -GNinja -DCMAKE_C_COMPILER=${LLVM11_PATH}/bin/clang \
-DCMAKE_CXX_COMPILER=${LLVM11_PATH}/bin/clang++ -DGOOGLE_TEST=ON \
-DUSE_DMLC_GTEST=ON
ninja -v

3
tests/ci_build/build_jvm_packages.sh
View File

@ -27,6 +27,9 @@ fi
mvn_profile_string=""
if [ "x$use_scala213" != "x" ]; then
export mvn_profile_string="-Pdefault,scala-2.13"
cd ..
python dev/change_scala_version.py --scala-version 2.13 --purge-artifacts
cd jvm-packages
fi
mvn --no-transfer-progress package $mvn_profile_string -Dspark.version=${spark_version} $gpu_options

3
tests/ci_build/conda_env/macos_cpu_test.yml
View File

@ -32,11 +32,10 @@ dependencies:
- jsonschema
- boto3
- awscli
- py-ubjson
- cffi
- pyarrow
- pyspark>=3.4.0
- cloudpickle
- pip:
- sphinx_rtd_theme
- datatable
- py-ubjson

3
tests/ci_build/deploy_jvm_packages.sh
View File

@ -27,6 +27,9 @@ rm -rf ../build/
# Deploy to S3 bucket xgboost-maven-repo
mvn --no-transfer-progress package deploy -P default,gpu,release-to-s3 -Dspark.version=${spark_version} -DskipTests
# Deploy scala 2.13 to S3 bucket xgboost-maven-repo
cd ..
python dev/change_scala_version.py --scala-version 2.13 --purge-artifacts
cd jvm-packages/
mvn --no-transfer-progress package deploy -P release-to-s3,default,scala-2.13 -Dspark.version=${spark_version} -DskipTests

13
tests/ci_build/test_jvm_cross.sh
View File

@ -21,9 +21,18 @@ if [ ! -z "$RUN_INTEGRATION_TEST" ]; then
fi
# including maven profiles for different scala versions: 2.12 is the default at the moment.
for _maven_profile_string in "" "-Pdefault,scala-2.13"; do
for scala_binary_version in "2.12" "2.13"; do
cd ..
python dev/change_scala_version.py --scala-version ${scala_binary_version}
cd jvm-packages
scala_version=$(mvn help:evaluate $_maven_profile_string -Dexpression=scala.version -q -DforceStdout)
scala_binary_version=$(mvn help:evaluate $_maven_profile_string -Dexpression=scala.binary.version -q -DforceStdout)
if [[ "$scala_binary_version" == "2.12" ]]; then
_maven_profile_string=""
elif [[ "$scala_binary_version" == "2.13" ]]; then
_maven_profile_string="-Pdefault,scala-2.13"
else
echo "Unexpected scala version: $scala_version ($scala_binary_version)."
fi
# Install XGBoost4J JAR into local Maven repository
mvn --no-transfer-progress install:install-file -Dfile=./xgboost4j/target/xgboost4j_${scala_binary_version}-${xgboost4j_version}.jar -DgroupId=ml.dmlc -DartifactId=xgboost4j_${scala_binary_version} -Dversion=${xgboost4j_version} -Dpackaging=jar

7
tests/python-gpu/test_gpu_with_sklearn.py
View File

@ -9,7 +9,7 @@ import pytest
import xgboost as xgb
from xgboost import testing as tm
from xgboost.testing.ranking import run_ranking_qid_df
from xgboost.testing.ranking import run_ranking_categorical, run_ranking_qid_df
sys.path.append("tests/python")
import test_with_sklearn as twskl # noqa
@ -165,6 +165,11 @@ def test_ranking_qid_df():
run_ranking_qid_df(cudf, "gpu_hist")
@pytest.mark.skipif(**tm.no_pandas())
def test_ranking_categorical() -> None:
run_ranking_categorical(device="cuda")
@pytest.mark.skipif(**tm.no_cupy())
@pytest.mark.mgpu
def test_device_ordinal() -> None:

29
tests/python/test_with_sklearn.py
View File

@ -12,7 +12,7 @@ from sklearn.utils.estimator_checks import parametrize_with_checks
import xgboost as xgb
from xgboost import testing as tm
from xgboost.testing.ranking import run_ranking_qid_df
from xgboost.testing.ranking import run_ranking_categorical, run_ranking_qid_df
from xgboost.testing.shared import get_feature_weights, validate_data_initialization
from xgboost.testing.updater import get_basescore
@ -173,6 +173,11 @@ def test_ranking():
np.testing.assert_almost_equal(pred, pred_orig)
@pytest.mark.skipif(**tm.no_pandas())
def test_ranking_categorical() -> None:
run_ranking_categorical(device="cpu")
def test_ranking_metric() -> None:
from sklearn.metrics import roc_auc_score
@ -935,6 +940,7 @@ def save_load_model(model_path):
predt_0 = clf.predict(X)
clf.save_model(model_path)
clf.load_model(model_path)
assert clf.booster == "gblinear"
predt_1 = clf.predict(X)
np.testing.assert_allclose(predt_0, predt_1)
assert clf.best_iteration == best_iteration
@ -950,25 +956,26 @@ def save_load_model(model_path):
def test_save_load_model():
with tempfile.TemporaryDirectory() as tempdir:
model_path = os.path.join(tempdir, 'digits.model')
model_path = os.path.join(tempdir, "digits.model")
save_load_model(model_path)
with tempfile.TemporaryDirectory() as tempdir:
model_path = os.path.join(tempdir, 'digits.model.json')
model_path = os.path.join(tempdir, "digits.model.json")
save_load_model(model_path)
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
with tempfile.TemporaryDirectory() as tempdir:
model_path = os.path.join(tempdir, 'digits.model.ubj')
model_path = os.path.join(tempdir, "digits.model.ubj")
digits = load_digits(n_class=2)
y = digits['target']
X = digits['data']
booster = xgb.train({'tree_method': 'hist',
'objective': 'binary:logistic'},
dtrain=xgb.DMatrix(X, y),
num_boost_round=4)
y = digits["target"]
X = digits["data"]
booster = xgb.train(
{"tree_method": "hist", "objective": "binary:logistic"},
dtrain=xgb.DMatrix(X, y),
num_boost_round=4,
)
predt_0 = booster.predict(xgb.DMatrix(X))
booster.save_model(model_path)
cls = xgb.XGBClassifier()
@ -1002,6 +1009,8 @@ def test_save_load_model():
clf = xgb.XGBClassifier()
clf.load_model(model_path)
assert clf.classes_.size == 10
assert clf.objective == "multi:softprob"
np.testing.assert_equal(clf.classes_, np.arange(10))
assert clf.n_classes_ == 10

7
tests/test_distributed/test_with_dask/test_with_dask.py
View File

@ -1932,6 +1932,7 @@ class TestWithDask:
cls.client = client
cls.fit(X, y)
predt_0 = cls.predict(X)
proba_0 = cls.predict_proba(X)
with tempfile.TemporaryDirectory() as tmpdir:
path = os.path.join(tmpdir, "model.pkl")
@ -1941,7 +1942,9 @@ class TestWithDask:
with open(path, "rb") as fd:
cls = pickle.load(fd)
predt_1 = cls.predict(X)
proba_1 = cls.predict_proba(X)
np.testing.assert_allclose(predt_0.compute(), predt_1.compute())
np.testing.assert_allclose(proba_0.compute(), proba_1.compute())
path = os.path.join(tmpdir, "cls.json")
cls.save_model(path)
@ -1950,16 +1953,20 @@ class TestWithDask:
cls.load_model(path)
assert cls.n_classes_ == 10
predt_2 = cls.predict(X)
proba_2 = cls.predict_proba(X)
np.testing.assert_allclose(predt_0.compute(), predt_2.compute())
np.testing.assert_allclose(proba_0.compute(), proba_2.compute())
# Use single node to load
cls = xgb.XGBClassifier()
cls.load_model(path)
assert cls.n_classes_ == 10
predt_3 = cls.predict(X_)
proba_3 = cls.predict_proba(X_)
np.testing.assert_allclose(predt_0.compute(), predt_3)
np.testing.assert_allclose(proba_0.compute(), proba_3)
def test_dask_unsupported_features(client: "Client") -> None: