Don't validate feature when number of rows is 0. (#6472)

python-package/xgboost/core.py

@@ -2025,6 +2025,9 @@ class Booster(object):
         Validate Booster and data's feature_names are identical.
         Set feature_names and feature_types from DMatrix
         """
+        if data.num_row() == 0:
+            return
+
         if self.feature_names is None:
             self.feature_names = data.feature_names
             self.feature_types = data.feature_types

python-package/xgboost/dask.py

@@ -763,7 +763,8 @@ async def _direct_predict_impl(client, data, predict_fn):
 
 
 # pylint: disable=too-many-statements
-async def _predict_async(client, global_config, model, data, missing=numpy.nan, **kwargs):
+async def _predict_async(client, global_config, model, data, missing, validate_features,
+                         **kwargs):
     if isinstance(model, Booster):
         booster = model
     elif isinstance(model, dict):
@@ -779,7 +780,7 @@ async def _predict_async(client, global_config, model, data, missing=numpy.nan,
         with config.config_context(**global_config):
             booster.set_param({'nthread': worker.nthreads})
             m = DMatrix(partition, missing=missing, nthread=worker.nthreads)
-            predt = booster.predict(m, validate_features=False, **kwargs)
+            predt = booster.predict(m, validate_features=validate_features, **kwargs)
             if is_df:
                 if lazy_isinstance(partition, 'cudf', 'core.dataframe.DataFrame'):
                     import cudf     # pylint: disable=import-error
@@ -821,7 +822,7 @@ async def _predict_async(client, global_config, model, data, missing=numpy.nan,
                 )
                 predt = booster.predict(
                     data=local_part,
-                    validate_features=local_part.num_row() != 0,
+                    validate_features=validate_features,
                     **kwargs)
                 columns = 1 if len(predt.shape) == 1 else predt.shape[1]
                 ret = ((dask.delayed(predt), columns), order)
@@ -878,7 +879,7 @@ async def _predict_async(client, global_config, model, data, missing=numpy.nan,
     return predictions
 
 
-def predict(client, model, data, missing=numpy.nan, **kwargs):
+def predict(client, model, data, missing=numpy.nan, validate_features=True, **kwargs):
     '''Run prediction with a trained booster.
 
     .. note::
@@ -910,7 +911,7 @@ def predict(client, model, data, missing=numpy.nan, **kwargs):
     client = _xgb_get_client(client)
     global_config = config.get_config()
     return client.sync(_predict_async, client, global_config, model, data,
-                       missing=missing, **kwargs)
+                       missing=missing, validate_features=validate_features, **kwargs)
 
 
 async def _inplace_predict_async(client, global_config, model, data,