Fix wrap_evaluation_matrices with xgb master (#215)

Compatibility fix for the latest xgboost master

Author: Yard1

.github/workflows/test.yaml

@@ -159,10 +159,9 @@ jobs:
     timeout-minutes: 160
     strategy:
       matrix:
-        python-version: [3.6.9, 3.7, 3.8]
+        # no new versions for xgboost are published for 3.6
+        python-version: [3.7, 3.8]
         include:
-          - python-version: 3.6.9
-            ray-wheel: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
           - python-version: 3.7
             ray-wheel: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl
           - python-version: 3.8

xgboost_ray/sklearn.py

@@ -59,6 +59,8 @@ def inner_f(*args, **kwargs):
         return inner_f
 
 
+# If _wrap_evaluation_matrices has new arguments added in xgboost, update
+# RayXGBMixin._ray_get_wrap_evaluation_matrices_compat_kwargs
 try:
     from xgboost.sklearn import _wrap_evaluation_matrices
 except ImportError:
@@ -358,13 +360,20 @@ def _ray_predict(
     def _ray_get_wrap_evaluation_matrices_compat_kwargs(
             self, label_transform=None) -> dict:
         ret = {}
-        if "label_transform" in inspect.signature(
-                _wrap_evaluation_matrices).parameters:
+        wrap_evaluation_matrices_parameters = inspect.signature(
+            _wrap_evaluation_matrices).parameters
+        if "label_transform" in wrap_evaluation_matrices_parameters:
             # XGBoost < 1.6.0
             identity_func = lambda x: x  # noqa
             ret["label_transform"] = label_transform or identity_func
-        if hasattr(self, "enable_categorical"):
+        if hasattr(
+                self, "enable_categorical"
+        ) and "enable_categorical" in wrap_evaluation_matrices_parameters:
             ret["enable_categorical"] = self.enable_categorical
+        if hasattr(
+                self, "feature_types"
+        ) and "feature_types" in wrap_evaluation_matrices_parameters:
+            ret["feature_types"] = self.feature_types
         return ret
 
     # copied from the file in the top comment