Fix histogram truncation. (#7181)

* Fix truncation.

* Lint.

* lint.

python-package/setup.py

@@ -302,7 +302,7 @@ if __name__ == '__main__':
 
     with open(os.path.join(CURRENT_DIR, 'README.rst'), encoding='utf-8') as fd:
         description = fd.read()
-    with open(os.path.join(CURRENT_DIR, 'xgboost/VERSION')) as fd:
+    with open(os.path.join(CURRENT_DIR, 'xgboost/VERSION'), encoding="ascii") as fd:
         version = fd.read().strip()
 
     setup(name='xgboost',

python-package/xgboost/__init__.py

@@ -22,7 +22,7 @@ except ImportError:
     pass
 
 VERSION_FILE = os.path.join(os.path.dirname(__file__), 'VERSION')
-with open(VERSION_FILE) as f:
+with open(VERSION_FILE, encoding="ascii") as f:
     __version__ = f.read().strip()
 
 __all__ = ['DMatrix', 'DeviceQuantileDMatrix', 'Booster', 'DataIter',

python-package/xgboost/compat.py

@@ -70,7 +70,7 @@ try:
         '''Label encoder with JSON serialization methods.'''
         def to_json(self):
             '''Returns a JSON compatible dictionary'''
-            meta = dict()
+            meta = {}
             for k, v in self.__dict__.items():
                 if isinstance(v, np.ndarray):
                     meta[k] = v.tolist()
@@ -81,7 +81,7 @@ try:
         def from_json(self, doc):
             # pylint: disable=attribute-defined-outside-init
             '''Load the encoder back from a JSON compatible dict.'''
-            meta = dict()
+            meta = {}
             for k, v in doc.items():
                 if k == 'classes_':
                     self.classes_ = np.array(v)

python-package/xgboost/core.py

@@ -2197,7 +2197,8 @@ class Booster(object):
         """
         if isinstance(fout, (STRING_TYPES, os.PathLike)):
             fout = os.fspath(os.path.expanduser(fout))
-            fout = open(fout, 'w')  # pylint: disable=consider-using-with
+            # pylint: disable=consider-using-with
+            fout = open(fout, 'w', encoding="utf-8")
             need_close = True
         else:
             need_close = False

python-package/xgboost/sklearn.py

@@ -538,7 +538,7 @@ class XGBModel(XGBModelBase):
             'importance_type', 'kwargs', 'missing', 'n_estimators', 'use_label_encoder',
             "enable_categorical"
         }
-        filtered = dict()
+        filtered = {}
         for k, v in params.items():
             if k not in wrapper_specific and not callable(v):
                 filtered[k] = v
@@ -557,7 +557,7 @@ class XGBModel(XGBModelBase):
         return self._estimator_type  # pylint: disable=no-member
 
     def save_model(self, fname: Union[str, os.PathLike]) -> None:
-        meta = dict()
+        meta = {}
         for k, v in self.__dict__.items():
             if k == '_le':
                 meta['_le'] = self._le.to_json()
@@ -596,7 +596,7 @@ class XGBModel(XGBModelBase):
             )
             return
         meta = json.loads(meta_str)
-        states = dict()
+        states = {}
         for k, v in meta.items():
             if k == '_le':
                 self._le = XGBoostLabelEncoder()

src/tree/gpu_hist/histogram.cuh

@@ -1,5 +1,5 @@
 /*!
- * Copyright 2020 by XGBoost Contributors
+ * Copyright 2020-2021 by XGBoost Contributors
  */
 #ifndef HISTOGRAM_CUH_
 #define HISTOGRAM_CUH_
@@ -15,8 +15,9 @@ namespace tree {
 template <typename GradientSumT>
 GradientSumT CreateRoundingFactor(common::Span<GradientPair const> gpair);
 
-template <typename T>
+template <typename T, typename U>
-XGBOOST_DEV_INLINE T TruncateWithRoundingFactor(T const rounding_factor, float const x) {
+XGBOOST_DEV_INLINE T TruncateWithRoundingFactor(T const rounding_factor, U const x) {
+  static_assert(sizeof(T) >= sizeof(U), "Rounding must have higher or equal precision.");
   return (rounding_factor + static_cast<T>(x)) - rounding_factor;
 }