Fix matrix transpose reference construction

array_api_tests/test_linalg.py

@@ -516,10 +516,12 @@ def test_matrix_rank(x, kw):
 def _test_matrix_transpose(namespace, x):
     matrix_transpose = namespace.matrix_transpose
     res = matrix_transpose(x)
-    true_val = lambda a: _array_module.asarray([[a[i, j] for i in
-                                                range(a.shape[0])] for j in
-                                                range(a.shape[1])],
-                                               dtype=a.dtype)
+    def true_val(a):
+        if 0 in a.shape:
+            return xp.empty((a.shape[1], a.shape[0]),
+                            dtype=a.dtype, device=a.device)
+        return xp.stack([a[i, :] for i in range(a.shape[0])], axis=1)
+
     shape = list(x.shape)
     shape[-1], shape[-2] = shape[-2], shape[-1]
     shape = tuple(shape)

meta_tests/test_linalg.py

@@ -5,6 +5,31 @@
 from array_api_tests .hypothesis_helpers import symmetric_matrices
 from array_api_tests import array_helpers as ah
 from array_api_tests import _array_module as xp
+from array_api_tests.test_linalg import _test_matrix_transpose
+
+
+@pytest.mark.parametrize('shape', [(2, 3), (2, 2, 3), (0, 3), (3, 0), (0, 0)])
+def test_matrix_transpose_without_nested_arrays(monkeypatch, shape):
+    size = 1
+    for dim in shape:
+        size *= dim
+    x = xp.reshape(xp.arange(size, dtype=xp.int64), shape)
+    original_asarray = xp.asarray
+
+    def asarray(obj, **kwargs):
+        def check_sequence(value):
+            if isinstance(value, (list, tuple)):
+                for item in value:
+                    check_sequence(item)
+            else:
+                assert isinstance(value, (bool, int, float, complex))
+
+        if isinstance(obj, (list, tuple)):
+            check_sequence(obj)
+        return original_asarray(obj, **kwargs)
+
+    monkeypatch.setattr(xp, 'asarray', asarray)
+    _test_matrix_transpose(xp, x)
 
 @pytest.mark.xp_extension('linalg')
 @given(x=symmetric_matrices(finite=True))