Use array interface for testing numpy arrays. (dmlc#9602)

trivialfis · Oct 8, 2023 · 88d3db0 · 88d3db0
1 parent 032bcc5
commit 88d3db0
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Showing 2 changed files with 8 additions and 7 deletions.
diff --git a/python-package/xgboost/core.py b/python-package/xgboost/core.py
@@ -2399,6 +2399,7 @@ def inplace_predict(
             _is_cudf_df,
             _is_cupy_array,
             _is_list,
+            _is_np_array_like,
             _is_pandas_df,
             _is_pandas_series,
             _is_tuple,
@@ -2428,7 +2429,7 @@ def inplace_predict(
                     f"got {data.shape[1]}"
                 )
 
-        if isinstance(data, np.ndarray):
+        if _is_np_array_like(data):
             from .data import _ensure_np_dtype
 
             data, _ = _ensure_np_dtype(data, data.dtype)

diff --git a/python-package/xgboost/data.py b/python-package/xgboost/data.py
@@ -164,8 +164,8 @@ def _is_scipy_coo(data: DataType) -> bool:
     return isinstance(data, scipy.sparse.coo_matrix)
 
 
-def _is_numpy_array(data: DataType) -> bool:
-    return isinstance(data, (np.ndarray, np.matrix))
+def _is_np_array_like(data: DataType) -> bool:
+    return hasattr(data, "__array_interface__")
 
 
 def _ensure_np_dtype(
@@ -1051,7 +1051,7 @@ def dispatch_data_backend(
         return _from_scipy_csr(
             data.tocsr(), missing, threads, feature_names, feature_types
         )
-    if _is_numpy_array(data):
+    if _is_np_array_like(data):
         return _from_numpy_array(
             data, missing, threads, feature_names, feature_types, data_split_mode
         )
@@ -1194,7 +1194,7 @@ def dispatch_meta_backend(
     if _is_tuple(data):
         _meta_from_tuple(data, name, dtype, handle)
         return
-    if _is_numpy_array(data):
+    if _is_np_array_like(data):
         _meta_from_numpy(data, name, dtype, handle)
         return
     if _is_pandas_df(data):
@@ -1281,7 +1281,7 @@ def _proxy_transform(
         return _transform_dlpack(data), None, feature_names, feature_types
     if _is_list(data) or _is_tuple(data):
         data = np.array(data)
-    if _is_numpy_array(data):
+    if _is_np_array_like(data):
         data, _ = _ensure_np_dtype(data, data.dtype)
         return data, None, feature_names, feature_types
     if _is_scipy_csr(data):
@@ -1331,7 +1331,7 @@ def dispatch_proxy_set_data(
     if not allow_host:
         raise err
 
-    if _is_numpy_array(data):
+    if _is_np_array_like(data):
         _check_data_shape(data)
         proxy._set_data_from_array(data)  # pylint: disable=W0212
         return