Reduce number of parametrizations in `test_tril_triu`

tests/tensor/test_basic.py

@@ -1044,7 +1044,7 @@ class TestTriangle:
             assert np.allclose(result_indx, result_from)
             assert result.dtype == np.dtype(dtype)
 
-        def check_l_batch(m, k=0):
+        def check_l_batch(m):
             m_symb = tensor3(dtype=m.dtype)
             k_symb = iscalar()
             f = function([m_symb, k_symb], tril(m_symb, k_symb))
@@ -1062,28 +1062,31 @@ class TestTriangle:
                 assert np.allclose(result, np.triu(m, k))
                 assert result.dtype == np.dtype(dtype)
 
-        for dtype in ["int32", "int64", "float32", "float64", "uint16", "complex64"]:
+        for dtype in ["int32", "int64", "uint16"]:
             m = random_of_dtype((10, 10), dtype)
             check_l(m, 0)
             check_l(m, 1)
             check_l(m, -1)
 
+            m = random_of_dtype((10, 5), dtype)
             check_u(m, 0)
             check_u(m, 1)
             check_u(m, -1)
 
-            m = random_of_dtype((10, 5), dtype)
-            check_l(m, 0)
-            check_l(m, 1)
-            check_l(m, -1)
+            m = random_of_dtype((5, 5, 5), dtype)
+            check_l_batch(m)
+            check_u_batch(m)
 
+        for dtype in ["float32", "float64", "complex64"]:
+            m = random_of_dtype((10, 10), dtype)
             check_u(m, 0)
             check_u(m, 1)
             check_u(m, -1)
 
-            m = random_of_dtype((5, 5, 5), dtype)
-            check_l_batch(m)
-            check_u_batch(m)
+            m = random_of_dtype((10, 5), dtype)
+            check_l(m, 0)
+            check_l(m, 1)
+            check_l(m, -1)
 
             m = random_of_dtype((5, 10, 5), dtype)
             check_l_batch(m)