allow mixed types in array func protocol

python/mxnet/numpy/multiarray.py

@@ -392,11 +392,17 @@ def __array_function__(self, func, types, args, kwargs):  # pylint: disable=bad-
             out = func(*new_args, **new_kwargs)
             return _as_mx_np_array(out, ctx=cur_ctx)
         else:
-            # Note: this allows subclasses that don't override
-            # __array_function__ to handle mxnet.numpy.ndarray objects
-            if not py_all(issubclass(t, ndarray) for t in types):
-                return NotImplemented
-            return mx_np_func(*args, **kwargs)
+            if py_all(issubclass(t, ndarray) for t in types):
+                return mx_np_func(*args, **kwargs)
+            else:
+                try:
+                    cur_ctx = next(a.ctx for a in args if hasattr(a, 'ctx'))
+                except StopIteration:
+                    cur_ctx = next(a.ctx for a in kwargs.values() if hasattr(a, 'ctx'))
+                new_args = _as_mx_np_array(args, ctx=cur_ctx)
+                new_kwargs = {k: _as_mx_np_array(v, cur_ctx) for k, v in kwargs.items()}
+                return mx_np_func(*new_args, **new_kwargs)
+
 
     def _get_np_basic_indexing(self, key):
         """

tests/python/unittest/test_numpy_ndarray.py

@@ -1401,3 +1401,8 @@ def test_from_numpy_exception():
     np_array = _np.array([[1, 2], [3, 4], [5, 6]], dtype="float32")
     mx_array = mx.npx.from_numpy(np_array, zero_copy=False)
     np_array[2, 1] = 0 # no error
+
+def test_mixed_array_types():
+    np_array = _np.array([[1, 2], [3, 4], [5, 6]], dtype="float32")
+    mx_array = mx.np.ones((3, 1))
+    assert_almost_equal(mx_array + np_array, 1+np_array)