Handle UTF-8 paths correctly on Windows platform (#9443)

* Fix round-trip serialization with UTF-8 paths

* Add compiler version check

* Add comment to C API functions

* Add Python tests

* [CI] Updatre MacOS deployment target

* Use std::filesystem instead of dmlc::TemporaryDirectory

CMakeLists.txt

@@ -14,8 +14,24 @@ endif ((${CMAKE_VERSION} VERSION_GREATER 3.13) OR (${CMAKE_VERSION} VERSION_EQUA
 
 message(STATUS "CMake version ${CMAKE_VERSION}")
 
-if (CMAKE_COMPILER_IS_GNUCC AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 5.0)
-  message(FATAL_ERROR "GCC version must be at least 5.0!")
+# Check compiler versions
+# Use recent compilers to ensure that std::filesystem is available
+if(MSVC)
+  if(MSVC_VERSION LESS 1920)
+    message(FATAL_ERROR "Need Visual Studio 2019 or newer to build XGBoost")
+  endif()
+elseif(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
+  if(CMAKE_CXX_COMPILER_VERSION VERSION_LESS "8.1")
+    message(FATAL_ERROR "Need GCC 8.1 or newer to build XGBoost")
+  endif()
+elseif(CMAKE_CXX_COMPILER_ID STREQUAL "AppleClang")
+  if(CMAKE_CXX_COMPILER_VERSION VERSION_LESS "11.0")
+    message(FATAL_ERROR "Need Xcode 11.0 (AppleClang 11.0) or newer to build XGBoost")
+  endif()
+elseif(CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
+  if(CMAKE_CXX_COMPILER_VERSION VERSION_LESS "9.0")
+    message(FATAL_ERROR "Need Clang 9.0 or newer to build XGBoost")
+  endif()
 endif()
 
 include(${xgboost_SOURCE_DIR}/cmake/FindPrefetchIntrinsics.cmake)

include/xgboost/c_api.h

@@ -1221,7 +1221,7 @@ XGB_DLL int XGBoosterPredictFromCudaColumnar(BoosterHandle handle, char const *v
  * \brief Load model from existing file
  *
  * \param handle handle
- * \param fname File URI or file name.
+ * \param fname File URI or file name. The string must be UTF-8 encoded.
  * \return 0 when success, -1 when failure happens
  */
 XGB_DLL int XGBoosterLoadModel(BoosterHandle handle,
@@ -1230,7 +1230,7 @@ XGB_DLL int XGBoosterLoadModel(BoosterHandle handle,
  * \brief Save model into existing file
  *
  * \param handle handle
- * \param fname File URI or file name.
+ * \param fname File URI or file name. The string must be UTF-8 encoded.
  * \return 0 when success, -1 when failure happens
  */
 XGB_DLL int XGBoosterSaveModel(BoosterHandle handle,

src/common/io.cc

@@ -28,6 +28,7 @@
 #include <cstddef>       // for size_t
 #include <cstdint>       // for int32_t, uint32_t
 #include <cstring>       // for memcpy
+#include <filesystem>    // for filesystem
 #include <fstream>       // for ifstream
 #include <iterator>      // for distance
 #include <limits>        // for numeric_limits
@@ -153,7 +154,7 @@ std::string LoadSequentialFile(std::string uri, bool stream) {
     // Open in binary mode so that correct file size can be computed with
     // seekg(). This accommodates Windows platform:
     // https://docs.microsoft.com/en-us/cpp/standard-library/basic-istream-class?view=vs-2019#seekg
-    std::ifstream ifs(uri, std::ios_base::binary | std::ios_base::in);
+    std::ifstream ifs(std::filesystem::u8path(uri), std::ios_base::binary | std::ios_base::in);
     if (!ifs) {
       // https://stackoverflow.com/a/17338934
       OpenErr();

tests/ci_build/build_python_wheels.sh

@@ -35,7 +35,7 @@ if [[ "$platform_id" == macosx_* ]]; then
         # MacOS, Intel
         wheel_tag=macosx_10_15_x86_64.macosx_11_0_x86_64.macosx_12_0_x86_64
         cpython_ver=38
-        export MACOSX_DEPLOYMENT_TARGET=10.13
+        export MACOSX_DEPLOYMENT_TARGET=10.15
         #OPENMP_URL="https://anaconda.org/conda-forge/llvm-openmp/11.1.0/download/osx-64/llvm-openmp-11.1.0-hda6cdc1_1.tar.bz2"
         OPENMP_URL="https://xgboost-ci-jenkins-artifacts.s3.us-west-2.amazonaws.com/llvm-openmp-11.1.0-hda6cdc1_1-osx-64.tar.bz2"
     else

tests/cpp/c_api/test_c_api.cc

@@ -10,6 +10,7 @@
 
 #include <array>      // for array
 #include <cstddef>    // std::size_t
+#include <filesystem> // std::filesystem
 #include <limits>     // std::numeric_limits
 #include <string>     // std::string
 #include <vector>
@@ -162,7 +163,7 @@ TEST(CAPI, ConfigIO) {
 TEST(CAPI, JsonModelIO) {
   size_t constexpr kRows = 10;
   size_t constexpr kCols = 10;
-  dmlc::TemporaryDirectory tempdir;
+  auto tempdir = std::filesystem::temp_directory_path();
 
   auto p_dmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
   std::vector<std::shared_ptr<DMatrix>> mat {p_dmat};
@@ -178,19 +179,19 @@ TEST(CAPI, JsonModelIO) {
   learner->UpdateOneIter(0, p_dmat);
   BoosterHandle handle = learner.get();
 
-  std::string modelfile_0 = tempdir.path + "/model_0.json";
-  XGBoosterSaveModel(handle, modelfile_0.c_str());
-  XGBoosterLoadModel(handle, modelfile_0.c_str());
+  auto modelfile_0 = tempdir / std::filesystem::u8path(u8"모델_0.json");
+  XGBoosterSaveModel(handle, modelfile_0.u8string().c_str());
+  XGBoosterLoadModel(handle, modelfile_0.u8string().c_str());
 
   bst_ulong num_feature {0};
   ASSERT_EQ(XGBoosterGetNumFeature(handle, &num_feature), 0);
   ASSERT_EQ(num_feature, kCols);
 
-  std::string modelfile_1 = tempdir.path + "/model_1.json";
-  XGBoosterSaveModel(handle, modelfile_1.c_str());
+  auto modelfile_1 = tempdir / "model_1.json";
+  XGBoosterSaveModel(handle, modelfile_1.u8string().c_str());
 
-  auto model_str_0 = common::LoadSequentialFile(modelfile_0);
-  auto model_str_1 = common::LoadSequentialFile(modelfile_1);
+  auto model_str_0 = common::LoadSequentialFile(modelfile_0.u8string());
+  auto model_str_1 = common::LoadSequentialFile(modelfile_1.u8string());
 
   ASSERT_EQ(model_str_0.front(), '{');
   ASSERT_EQ(model_str_0, model_str_1);

tests/python/test_basic.py

@@ -1,5 +1,6 @@
 import json
 import os
+import pathlib
 import tempfile
 from pathlib import Path
 
@@ -167,6 +168,17 @@ class TestBasic:
         with pytest.raises(xgb.core.XGBoostError):
             xgb.Booster(model_file=u'不正なパス')
 
+    @pytest.mark.parametrize("path", ["모델.ubj", "がうる・ぐら.json"], ids=["path-0", "path-1"])
+    def test_unicode_path(self, tmpdir, path):
+        model_path = pathlib.Path(tmpdir) / path
+        dtrain, _ = tm.load_agaricus(__file__)
+        param = {"max_depth": 2, "eta": 1, "objective": "binary:logistic"}
+        bst = xgb.train(param, dtrain, num_boost_round=2)
+        bst.save_model(model_path)
+
+        bst2 = xgb.Booster(model_file=model_path)
+        assert bst.get_dump(dump_format="text") == bst2.get_dump(dump_format="text")
+
     def test_dmatrix_numpy_init_omp(self):
 
         rows = [1000, 11326, 15000]