TST: unxfail tests of out and dtype as positional args

Author: ev-br

torch_np/tests/numpy_tests/core/test_multiarray.py

@@ -3743,7 +3743,6 @@ def test_ret_is_out(self, ndim, method):
         ret = arg_method(axis=0, out=out)
         assert ret is out
 
-    @pytest.mark.xfail(reason='FIXME: out w/ positional args?')
     @pytest.mark.parametrize('arr_method, np_method',
         [('argmax', np.argmax),
          ('argmin', np.argmin)])

torch_np/tests/numpy_tests/core/test_numeric.py

@@ -2486,7 +2486,6 @@ def test_mode(self):
 
 class TestDtypePositional:
 
-    @pytest.mark.xfail(reason='TODO: restore dtypes as positional args')
     def test_dtype_positional(self):
         np.empty((2,), bool)
 

torch_np/tests/numpy_tests/lib/test_shape_base_.py

@@ -719,7 +719,7 @@ def test_kroncompare(self):
         for s in shape:
             b = randint(0, 10, size=s)
             for r in reps:
-                a = np.ones(r, dtype=b.dtype)   # TODO: restore dtype positional arg
+                a = np.ones(r, b.dtype)
                 large = tile(b, r)
                 klarge = kron(a, b)
                 assert_equal(large, klarge)

torch_np/tests/test_ndarray_methods.py

@@ -323,7 +323,6 @@ def test_np_vs_ndarray(self, arr_method, np_method):
         assert_equal(arg_method(out=out1, axis=0), np_method(a, out=out2, axis=0))
         assert_equal(out1, out2)
 
-    @pytest.mark.xfail(reason="out=... as a positional arg")
     @pytest.mark.parametrize(
         "arr_method, np_method", [("argmax", np.argmax), ("argmin", np.argmin)]
     )