Fixed dpctl.tensor.result_type function for scalars

Author: npolina4

dpctl/tensor/_manipulation_functions.py

@@ -727,12 +727,16 @@ def result_type(*arrays_and_dtypes):
              The dtype resulting from an operation involving the
              input arrays and dtypes.
     """
-    dtypes = [
-        X.dtype if isinstance(X, dpt.usm_ndarray) else dpt.dtype(X)
-        for X in arrays_and_dtypes
-    ]
-
-    _supported_dtype(dtypes)
+    dtypes = []
+    for X in arrays_and_dtypes:
+        if isinstance(X, dpt.usm_ndarray):
+            dtypes.append(X.dtype)
+        elif np.isscalar(X) or isinstance(X, (tuple, list, range)):
+            dtypes.append(X)
+        else:
+            dtype = dpt.dtype(X)
+            _supported_dtype([dtype])
+            dtypes.append(dtype)
 
     return np.result_type(*dtypes)
 

dpctl/tests/test_usm_ndarray_manipulation.py

@@ -935,8 +935,8 @@ def test_can_cast():
 def test_result_type():
     q = get_queue_or_skip()
 
-    X = [dpt.ones((2), dtype=dpt.int64, sycl_queue=q), dpt.int32, "float16"]
-    X_np = [np.ones((2), dtype=np.int64), np.int32, "float16"]
+    X = [dpt.ones((2), dtype=dpt.int64, sycl_queue=q), dpt.int32, "float16", 2]
+    X_np = [np.ones((2), dtype=np.int64), np.int32, "float16", 2]
 
     assert dpt.result_type(*X) == np.result_type(*X_np)