git: 6ba8180534b1 - main - misc/{,py-}xgboost: Update 1.5.2 -> 1.6.0
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Date: Sun, 17 Apr 2022 23:24:18 UTC
The branch main has been updated by yuri:
URL: https://cgit.FreeBSD.org/ports/commit/?id=6ba8180534b1010593f9789bdbb758a889354390
commit 6ba8180534b1010593f9789bdbb758a889354390
Author: Yuri Victorovich <yuri@FreeBSD.org>
AuthorDate: 2022-04-17 21:38:20 +0000
Commit: Yuri Victorovich <yuri@FreeBSD.org>
CommitDate: 2022-04-17 23:24:12 +0000
misc/{,py-}xgboost: Update 1.5.2 -> 1.6.0
Reported by: portscout
---
misc/py-xgboost/Makefile | 2 +-
misc/py-xgboost/distinfo | 6 +-
misc/py-xgboost/files/patch-2to3 | 375 -----------------------------
misc/py-xgboost/files/patch-CMakeLists.txt | 8 +-
misc/py-xgboost/pkg-plist | 14 ++
misc/xgboost/Makefile | 2 +-
misc/xgboost/distinfo | 6 +-
misc/xgboost/files/patch-CMakeLists.txt | 26 +-
misc/xgboost/pkg-plist | 2 +
9 files changed, 45 insertions(+), 396 deletions(-)
diff --git a/misc/py-xgboost/Makefile b/misc/py-xgboost/Makefile
index ecce53c63555..bbe49e906a87 100644
--- a/misc/py-xgboost/Makefile
+++ b/misc/py-xgboost/Makefile
@@ -1,6 +1,6 @@
PORTNAME= xgboost
DISTVERSIONPREFIX= v
-DISTVERSION= 1.5.2
+DISTVERSION= 1.6.0
CATEGORIES= misc # machine-learning
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
diff --git a/misc/py-xgboost/distinfo b/misc/py-xgboost/distinfo
index 754ae83217d4..21125d76240c 100644
--- a/misc/py-xgboost/distinfo
+++ b/misc/py-xgboost/distinfo
@@ -1,3 +1,3 @@
-TIMESTAMP = 1643047834
-SHA256 (dmlc-xgboost-v1.5.2_GH0.tar.gz) = d77c71aa125bd7292cd670e5a575850d48aba03d1b05d75d791f3580748b1b0e
-SIZE (dmlc-xgboost-v1.5.2_GH0.tar.gz) = 1645645
+TIMESTAMP = 1650230831
+SHA256 (dmlc-xgboost-v1.6.0_GH0.tar.gz) = 035706af59d842d03e23d6eb2c9a146ae7c2832f66aed2a4703b4c32209cce40
+SIZE (dmlc-xgboost-v1.6.0_GH0.tar.gz) = 1755620
diff --git a/misc/py-xgboost/files/patch-2to3 b/misc/py-xgboost/files/patch-2to3
deleted file mode 100644
index 54eac41ed210..000000000000
--- a/misc/py-xgboost/files/patch-2to3
+++ /dev/null
@@ -1,375 +0,0 @@
---- xgboost/callback.py.orig 2022-01-17 08:52:31 UTC
-+++ xgboost/callback.py
-@@ -319,7 +319,7 @@ def _aggcv(rlist):
- cvmap[(metric_idx, k)].append(float(v))
- msg = idx
- results = []
-- for (metric_idx, k), v in sorted(cvmap.items(), key=lambda x: x[0][0]):
-+ for (metric_idx, k), v in sorted(list(cvmap.items()), key=lambda x: x[0][0]):
- v = numpy.array(v)
- if not isinstance(msg, STRING_TYPES):
- msg = msg.decode()
-@@ -595,10 +595,10 @@ class EarlyStopping(TrainingCallback):
- evals_log: TrainingCallback.EvalsLog) -> bool:
- epoch += self.starting_round # training continuation
- msg = 'Must have at least 1 validation dataset for early stopping.'
-- assert len(evals_log.keys()) >= 1, msg
-+ assert len(list(evals_log.keys())) >= 1, msg
- data_name = ''
- if self.data:
-- for d, _ in evals_log.items():
-+ for d, _ in list(evals_log.items()):
- if d == self.data:
- data_name = d
- if not data_name:
-@@ -672,8 +672,8 @@ class EvaluationMonitor(TrainingCallback):
-
- msg: str = f'[{epoch}]'
- if rabit.get_rank() == self.printer_rank:
-- for data, metric in evals_log.items():
-- for metric_name, log in metric.items():
-+ for data, metric in list(evals_log.items()):
-+ for metric_name, log in list(metric.items()):
- stdv: Optional[float] = None
- if isinstance(log[-1], tuple):
- score = log[-1][0]
---- xgboost/compat.py.orig 2022-01-17 08:52:31 UTC
-+++ xgboost/compat.py
-@@ -48,14 +48,14 @@ except ImportError:
-
- # sklearn
- try:
-- from sklearn.base import BaseEstimator
-- from sklearn.base import RegressorMixin, ClassifierMixin
-- from sklearn.preprocessing import LabelEncoder
-+ from .sklearn.base import BaseEstimator
-+ from .sklearn.base import RegressorMixin, ClassifierMixin
-+ from .sklearn.preprocessing import LabelEncoder
-
- try:
-- from sklearn.model_selection import KFold, StratifiedKFold
-+ from .sklearn.model_selection import KFold, StratifiedKFold
- except ImportError:
-- from sklearn.cross_validation import KFold, StratifiedKFold
-+ from .sklearn.cross_validation import KFold, StratifiedKFold
-
- SKLEARN_INSTALLED = True
-
-@@ -71,7 +71,7 @@ try:
- def to_json(self):
- '''Returns a JSON compatible dictionary'''
- meta = {}
-- for k, v in self.__dict__.items():
-+ for k, v in list(self.__dict__.items()):
- if isinstance(v, np.ndarray):
- meta[k] = v.tolist()
- else:
-@@ -82,7 +82,7 @@ try:
- # pylint: disable=attribute-defined-outside-init
- '''Load the encoder back from a JSON compatible dict.'''
- meta = {}
-- for k, v in doc.items():
-+ for k, v in list(doc.items()):
- if k == 'classes_':
- self.classes_ = np.array(v)
- continue
---- xgboost/core.py.orig 2022-01-17 08:52:31 UTC
-+++ xgboost/core.py
-@@ -142,7 +142,7 @@ def _expect(expectations, got):
-
- def _log_callback(msg: bytes) -> None:
- """Redirect logs from native library into Python console"""
-- print(py_str(msg))
-+ print((py_str(msg)))
-
-
- def _get_log_callback_func():
-@@ -479,7 +479,7 @@ def _deprecate_positional_args(f):
- kwonly_args = []
- all_args = []
-
-- for name, param in sig.parameters.items():
-+ for name, param in list(sig.parameters.items()):
- if param.kind == Parameter.POSITIONAL_OR_KEYWORD:
- all_args.append(name)
- elif param.kind == Parameter.KEYWORD_ONLY:
-@@ -1346,7 +1346,7 @@ class Booster(object):
- def _configure_metrics(self, params: Union[Dict, List]) -> Union[Dict, List]:
- if isinstance(params, dict) and 'eval_metric' in params \
- and isinstance(params['eval_metric'], list):
-- params = dict((k, v) for k, v in params.items())
-+ params = dict((k, v) for k, v in list(params.items()))
- eval_metrics = params['eval_metric']
- params.pop("eval_metric", None)
- params = list(params.items())
-@@ -1577,7 +1577,7 @@ class Booster(object):
- **kwargs
- The attributes to set. Setting a value to None deletes an attribute.
- """
-- for key, value in kwargs.items():
-+ for key, value in list(kwargs.items()):
- if value is not None:
- if not isinstance(value, STRING_TYPES):
- raise ValueError("Set Attr only accepts string values")
-@@ -1650,7 +1650,7 @@ class Booster(object):
- value of the specified parameter, when params is str key
- """
- if isinstance(params, Mapping):
-- params = params.items()
-+ params = list(params.items())
- elif isinstance(params, STRING_TYPES) and value is not None:
- params = [(params, value)]
- for key, val in params:
---- xgboost/dask.py.orig 2022-01-17 08:52:31 UTC
-+++ xgboost/dask.py
-@@ -49,9 +49,9 @@ from .sklearn import _cls_predict_proba
- from .sklearn import XGBRanker
-
- if TYPE_CHECKING:
-- from dask import dataframe as dd
-- from dask import array as da
-- import dask
-+ from .dask import dataframe as dd
-+ from .dask import array as da
-+ from . import dask
- import distributed
- else:
- dd = LazyLoader('dd', globals(), 'dask.dataframe')
-@@ -152,7 +152,7 @@ def _start_tracker(n_workers: int) -> Dict[str, Any]:
-
- def _assert_dask_support() -> None:
- try:
-- import dask # pylint: disable=W0621,W0611
-+ from . import dask # pylint: disable=W0621,W0611
- except ImportError as e:
- raise ImportError(
- "Dask needs to be installed in order to use this module"
-@@ -394,7 +394,7 @@ class DaskDMatrix:
- # [(x0, x1, ..), (y0, y1, ..), ..] in delayed form
-
- # delay the zipped result
-- parts = list(map(dask.delayed, zip(*parts))) # pylint: disable=no-member
-+ parts = list(map(dask.delayed, list(zip(*parts)))) # pylint: disable=no-member
- # At this point, the mental model should look like:
- # [(x0, y0, ..), (x1, y1, ..), ..] in delayed form
-
-@@ -414,7 +414,7 @@ class DaskDMatrix:
-
- worker_map: Dict[str, "distributed.Future"] = defaultdict(list)
-
-- for key, workers in who_has.items():
-+ for key, workers in list(who_has.items()):
- worker_map[next(iter(workers))].append(key_to_partition[key])
-
- self.worker_map = worker_map
-@@ -803,7 +803,7 @@ def _dmatrix_from_list_of_parts(
- async def _get_rabit_args(n_workers: int, client: "distributed.Client") -> List[bytes]:
- '''Get rabit context arguments from data distribution in DaskDMatrix.'''
- env = await client.run_on_scheduler(_start_tracker, n_workers)
-- rabit_args = [f"{k}={v}".encode() for k, v in env.items()]
-+ rabit_args = [f"{k}={v}".encode() for k, v in list(env.items())]
- return rabit_args
-
- # train and predict methods are supposed to be "functional", which meets the
-@@ -930,7 +930,7 @@ async def _train_async(
-
- results = await client.gather(futures, asynchronous=True)
-
-- return list(filter(lambda ret: ret is not None, results))[0]
-+ return list([ret for ret in results if ret is not None])[0]
-
-
- def train( # pylint: disable=unused-argument
-@@ -1579,7 +1579,7 @@ class DaskScikitLearnBase(XGBModel):
-
- def __getstate__(self) -> Dict:
- this = self.__dict__.copy()
-- if "_client" in this.keys():
-+ if "_client" in list(this.keys()):
- del this["_client"]
- return this
-
-@@ -1711,7 +1711,7 @@ class DaskXGBRegressor(DaskScikitLearnBase, XGBRegress
- callbacks: Optional[List[TrainingCallback]] = None,
- ) -> "DaskXGBRegressor":
- _assert_dask_support()
-- args = {k: v for k, v in locals().items() if k not in ("self", "__class__")}
-+ args = {k: v for k, v in list(locals().items()) if k not in ("self", "__class__")}
- return self._client_sync(self._fit_async, **args)
-
-
-@@ -1814,7 +1814,7 @@ class DaskXGBClassifier(DaskScikitLearnBase, XGBClassi
- callbacks: Optional[List[TrainingCallback]] = None
- ) -> "DaskXGBClassifier":
- _assert_dask_support()
-- args = {k: v for k, v in locals().items() if k not in ("self", "__class__")}
-+ args = {k: v for k, v in list(locals().items()) if k not in ("self", "__class__")}
- return self._client_sync(self._fit_async, **args)
-
- async def _predict_proba_async(
-@@ -2002,7 +2002,7 @@ class DaskXGBRanker(DaskScikitLearnBase, XGBRankerMixI
- callbacks: Optional[List[TrainingCallback]] = None
- ) -> "DaskXGBRanker":
- _assert_dask_support()
-- args = {k: v for k, v in locals().items() if k not in ("self", "__class__")}
-+ args = {k: v for k, v in list(locals().items()) if k not in ("self", "__class__")}
- return self._client_sync(self._fit_async, **args)
-
- # FIXME(trivialfis): arguments differ due to additional parameters like group and qid.
-@@ -2067,7 +2067,7 @@ class DaskXGBRFRegressor(DaskXGBRegressor):
- callbacks: Optional[List[TrainingCallback]] = None
- ) -> "DaskXGBRFRegressor":
- _assert_dask_support()
-- args = {k: v for k, v in locals().items() if k not in ("self", "__class__")}
-+ args = {k: v for k, v in list(locals().items()) if k not in ("self", "__class__")}
- _check_rf_callback(early_stopping_rounds, callbacks)
- super().fit(**args)
- return self
-@@ -2131,7 +2131,7 @@ class DaskXGBRFClassifier(DaskXGBClassifier):
- callbacks: Optional[List[TrainingCallback]] = None
- ) -> "DaskXGBRFClassifier":
- _assert_dask_support()
-- args = {k: v for k, v in locals().items() if k not in ("self", "__class__")}
-+ args = {k: v for k, v in list(locals().items()) if k not in ("self", "__class__")}
- _check_rf_callback(early_stopping_rounds, callbacks)
- super().fit(**args)
- return self
---- xgboost/plotting.py.orig 2022-01-17 08:52:31 UTC
-+++ xgboost/plotting.py
-@@ -81,7 +81,7 @@ def plot_importance(booster, ax=None, height=0.2,
- tuples = sorted(tuples, key=lambda x: x[1])[-max_num_features:]
- else:
- tuples = sorted(tuples, key=lambda x: x[1])
-- labels, values = zip(*tuples)
-+ labels, values = list(zip(*tuples))
-
- if ax is None:
- _, ax = plt.subplots(1, 1)
-@@ -177,13 +177,13 @@ def to_graphviz(booster, fmap='', num_trees=0, rankdir
- # squash everything back into kwargs again for compatibility
- parameters = 'dot'
- extra = {}
-- for key, value in kwargs.items():
-+ for key, value in list(kwargs.items()):
- extra[key] = value
-
- if rankdir is not None:
- kwargs['graph_attrs'] = {}
- kwargs['graph_attrs']['rankdir'] = rankdir
-- for key, value in extra.items():
-+ for key, value in list(extra.items()):
- if kwargs.get("graph_attrs", None) is not None:
- kwargs['graph_attrs'][key] = value
- else:
---- xgboost/sklearn.py.orig 2022-01-17 08:52:31 UTC
-+++ xgboost/sklearn.py
-@@ -455,7 +455,7 @@ class XGBModel(XGBModelBase):
- booster : a xgboost booster of underlying model
- """
- if not self.__sklearn_is_fitted__():
-- from sklearn.exceptions import NotFittedError
-+ from .sklearn.exceptions import NotFittedError
- raise NotFittedError('need to call fit or load_model beforehand')
- return self._Booster
-
-@@ -476,7 +476,7 @@ class XGBModel(XGBModelBase):
-
- # this concatenates kwargs into parameters, enabling `get_params` for
- # obtaining parameters from keyword parameters.
-- for key, value in params.items():
-+ for key, value in list(params.items()):
- if hasattr(self, key):
- setattr(self, key, value)
- else:
-@@ -526,14 +526,14 @@ class XGBModel(XGBModelBase):
- internal = {}
- while stack:
- obj = stack.pop()
-- for k, v in obj.items():
-+ for k, v in list(obj.items()):
- if k.endswith('_param'):
-- for p_k, p_v in v.items():
-+ for p_k, p_v in list(v.items()):
- internal[p_k] = p_v
- elif isinstance(v, dict):
- stack.append(v)
-
-- for k, v in internal.items():
-+ for k, v in list(internal.items()):
- if k in params and params[k] is None:
- params[k] = parse_parameter(v)
- except ValueError:
-@@ -549,7 +549,7 @@ class XGBModel(XGBModelBase):
- "enable_categorical"
- }
- filtered = {}
-- for k, v in params.items():
-+ for k, v in list(params.items()):
- if k not in wrapper_specific and not callable(v):
- filtered[k] = v
- return filtered
-@@ -568,7 +568,7 @@ class XGBModel(XGBModelBase):
-
- def save_model(self, fname: Union[str, os.PathLike]) -> None:
- meta = {}
-- for k, v in self.__dict__.items():
-+ for k, v in list(self.__dict__.items()):
- if k == '_le':
- meta['_le'] = self._le.to_json()
- continue
-@@ -607,7 +607,7 @@ class XGBModel(XGBModelBase):
- return
- meta = json.loads(meta_str)
- states = {}
-- for k, v in meta.items():
-+ for k, v in list(meta.items()):
- if k == '_le':
- self._le = XGBoostLabelEncoder()
- self._le.from_json(v)
-@@ -660,7 +660,7 @@ class XGBModel(XGBModelBase):
-
- def _set_evaluation_result(self, evals_result: TrainingCallback.EvalsLog) -> None:
- if evals_result:
-- for val in evals_result.items():
-+ for val in list(evals_result.items()):
- evals_result_key = list(val[1].keys())[0]
- evals_result[val[0]][evals_result_key] = val[1][evals_result_key]
- self.evals_result_ = evals_result
-@@ -1455,7 +1455,7 @@ class XGBRFClassifier(XGBClassifier):
- feature_weights: Optional[array_like] = None,
- callbacks: Optional[List[TrainingCallback]] = None
- ) -> "XGBRFClassifier":
-- args = {k: v for k, v in locals().items() if k not in ("self", "__class__")}
-+ args = {k: v for k, v in list(locals().items()) if k not in ("self", "__class__")}
- _check_rf_callback(early_stopping_rounds, callbacks)
- super().fit(**args)
- return self
-@@ -1526,7 +1526,7 @@ class XGBRFRegressor(XGBRegressor):
- feature_weights: Optional[array_like] = None,
- callbacks: Optional[List[TrainingCallback]] = None
- ) -> "XGBRFRegressor":
-- args = {k: v for k, v in locals().items() if k not in ("self", "__class__")}
-+ args = {k: v for k, v in list(locals().items()) if k not in ("self", "__class__")}
- _check_rf_callback(early_stopping_rounds, callbacks)
- super().fit(**args)
- return self
---- xgboost/training.py.orig 2022-01-17 08:52:31 UTC
-+++ xgboost/training.py
-@@ -452,7 +452,7 @@ def cv(params, dtrain, num_boost_round=10, nfold=3, st
- if 'eval_metric' in params:
- params['eval_metric'] = _metrics
- else:
-- params = dict((k, v) for k, v in params.items())
-+ params = dict((k, v) for k, v in list(params.items()))
-
- if (not metrics) and 'eval_metric' in params:
- if isinstance(params['eval_metric'], list):
-@@ -506,7 +506,7 @@ def cv(params, dtrain, num_boost_round=10, nfold=3, st
- results[key + '-std'].append(std)
-
- if should_break:
-- for k in results.keys(): # pylint: disable=consider-iterating-dictionary
-+ for k in list(results.keys()): # pylint: disable=consider-iterating-dictionary
- results[k] = results[k][:(booster.best_iteration + 1)]
- break
- if as_pandas:
diff --git a/misc/py-xgboost/files/patch-CMakeLists.txt b/misc/py-xgboost/files/patch-CMakeLists.txt
index 4b498a226047..593bcfbf2b9d 100644
--- a/misc/py-xgboost/files/patch-CMakeLists.txt
+++ b/misc/py-xgboost/files/patch-CMakeLists.txt
@@ -17,10 +17,10 @@
if (BUILD_STATIC_LIB AND (R_LIB OR JVM_BINDINGS))
message(SEND_ERROR "Cannot build a static library libxgboost.a when R or JVM packages are enabled.")
endif (BUILD_STATIC_LIB AND (R_LIB OR JVM_BINDINGS))
-@@ -160,7 +160,7 @@ endif (USE_NCCL)
-
- # dmlc-core
- msvc_use_static_runtime()
+@@ -168,7 +168,7 @@ msvc_use_static_runtime()
+ if (FORCE_SHARED_CRT)
+ set(DMLC_FORCE_SHARED_CRT ON)
+ endif ()
-add_subdirectory(${xgboost_SOURCE_DIR}/dmlc-core)
+#add_subdirectory(${xgboost_SOURCE_DIR}/dmlc-core)
diff --git a/misc/py-xgboost/pkg-plist b/misc/py-xgboost/pkg-plist
new file mode 100644
index 000000000000..1ddb5b1777da
--- /dev/null
+++ b/misc/py-xgboost/pkg-plist
@@ -0,0 +1,14 @@
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/__init__%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/_typing%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/callback%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/compat%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/config%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/core%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/dask%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/data%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/libpath%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/plotting%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/rabit%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/sklearn%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/tracker%%PYTHON_EXT_SUFFIX%%.pyc
+%%PYTHON_SITELIBDIR%%/xgboost/__pycache__/training%%PYTHON_EXT_SUFFIX%%.pyc
diff --git a/misc/xgboost/Makefile b/misc/xgboost/Makefile
index 50678d11d2ec..3cd910c0192e 100644
--- a/misc/xgboost/Makefile
+++ b/misc/xgboost/Makefile
@@ -1,6 +1,6 @@
PORTNAME= xgboost
DISTVERSIONPREFIX= v
-DISTVERSION= 1.5.2
+DISTVERSION= 1.6.0
CATEGORIES= misc # machine-learning
MAINTAINER= yuri@FreeBSD.org
diff --git a/misc/xgboost/distinfo b/misc/xgboost/distinfo
index 9dcec333530f..2ec1e3eb3c43 100644
--- a/misc/xgboost/distinfo
+++ b/misc/xgboost/distinfo
@@ -1,6 +1,6 @@
-TIMESTAMP = 1643047765
-SHA256 (dmlc-xgboost-v1.5.2_GH0.tar.gz) = d77c71aa125bd7292cd670e5a575850d48aba03d1b05d75d791f3580748b1b0e
-SIZE (dmlc-xgboost-v1.5.2_GH0.tar.gz) = 1645645
+TIMESTAMP = 1650229980
+SHA256 (dmlc-xgboost-v1.6.0_GH0.tar.gz) = 035706af59d842d03e23d6eb2c9a146ae7c2832f66aed2a4703b4c32209cce40
+SIZE (dmlc-xgboost-v1.6.0_GH0.tar.gz) = 1755620
SHA256 (NVlabs-cub-af39ee2_GH0.tar.gz) = 3444f1d0af16d3680bf5089c1a91e707769d946580b80f12463860366fb6884b
SIZE (NVlabs-cub-af39ee2_GH0.tar.gz) = 413215
SHA256 (rapidsai-gputreeshap-5bba198_GH0.tar.gz) = bad0d98eddff46e298f4c6be71b140ac8573b2d1740f109f3151097c56f18463
diff --git a/misc/xgboost/files/patch-CMakeLists.txt b/misc/xgboost/files/patch-CMakeLists.txt
index 7fbe42423d27..97097cd460c6 100644
--- a/misc/xgboost/files/patch-CMakeLists.txt
+++ b/misc/xgboost/files/patch-CMakeLists.txt
@@ -1,6 +1,6 @@
---- CMakeLists.txt.orig 2021-10-15 04:21:04 UTC
+--- CMakeLists.txt.orig 2022-04-16 00:43:21 UTC
+++ CMakeLists.txt
-@@ -104,11 +104,11 @@ endif (PLUGIN_RMM AND NOT ((CMAKE_CXX_COMPILER_ID STRE
+@@ -105,11 +105,11 @@ endif (PLUGIN_RMM AND NOT ((CMAKE_CXX_COMPILER_ID STRE
if (PLUGIN_RMM AND NOT (CMAKE_SYSTEM_NAME STREQUAL "Linux"))
message(SEND_ERROR "`PLUGIN_RMM` must be used with Linux.")
endif (PLUGIN_RMM AND NOT (CMAKE_SYSTEM_NAME STREQUAL "Linux"))
@@ -17,16 +17,16 @@
if (BUILD_STATIC_LIB AND (R_LIB OR JVM_BINDINGS))
message(SEND_ERROR "Cannot build a static library libxgboost.a when R or JVM packages are enabled.")
endif (BUILD_STATIC_LIB AND (R_LIB OR JVM_BINDINGS))
-@@ -160,7 +160,7 @@ endif (USE_NCCL)
-
- # dmlc-core
- msvc_use_static_runtime()
+@@ -168,7 +168,7 @@ msvc_use_static_runtime()
+ if (FORCE_SHARED_CRT)
+ set(DMLC_FORCE_SHARED_CRT ON)
+ endif ()
-add_subdirectory(${xgboost_SOURCE_DIR}/dmlc-core)
+#add_subdirectory(${xgboost_SOURCE_DIR}/dmlc-core)
if (MSVC)
if (TARGET dmlc_unit_tests)
-@@ -177,7 +177,7 @@ endif (RABIT_BUILD_MPI)
+@@ -185,7 +185,7 @@ endif (RABIT_BUILD_MPI)
# core xgboost
add_subdirectory(${xgboost_SOURCE_DIR}/src)
@@ -35,7 +35,15 @@
# Exports some R specific definitions and objects
if (R_LIB)
-@@ -218,7 +218,7 @@ set_target_properties(runxgboost PROPERTIES OUTPUT_NAM
+@@ -219,14 +219,14 @@ target_link_libraries(runxgboost PRIVATE objxgboost)
+ target_include_directories(runxgboost
+ PRIVATE
+ ${xgboost_SOURCE_DIR}/include
+- ${xgboost_SOURCE_DIR}/dmlc-core/include
++ #${xgboost_SOURCE_DIR}/dmlc-core/include
+ ${xgboost_SOURCE_DIR}/rabit/include
+ )
+ set_target_properties(runxgboost PROPERTIES OUTPUT_NAME xgboost)
#-- End CLI for xgboost
# Common setup for all targets
@@ -44,7 +52,7 @@
xgboost_target_properties(${target})
xgboost_target_link_libraries(${target})
xgboost_target_defs(${target})
-@@ -269,7 +269,7 @@ install(DIRECTORY ${xgboost_SOURCE_DIR}/include/xgboos
+@@ -277,7 +277,7 @@ install(DIRECTORY ${xgboost_SOURCE_DIR}/include/xgboos
#
# https://github.com/dmlc/xgboost/issues/6085
if (BUILD_STATIC_LIB)
diff --git a/misc/xgboost/pkg-plist b/misc/xgboost/pkg-plist
index 3b9b92585a29..b04d4dc1b24b 100644
--- a/misc/xgboost/pkg-plist
+++ b/misc/xgboost/pkg-plist
@@ -20,6 +20,8 @@ include/xgboost/objective.h
include/xgboost/parameter.h
include/xgboost/predictor.h
include/xgboost/span.h
+include/xgboost/string_view.h
+include/xgboost/task.h
include/xgboost/tree_model.h
include/xgboost/tree_updater.h
include/xgboost/version_config.h