fixing test errors for numpy 1.22

tests/test_spec_elementwise_functions.py

@@ -20,6 +20,7 @@
 import ragged
 
 has_complex_dtype = True
+numpy_has_array_api = False
 
 # if np.lib.NumpyVersion(np.__version__) < "2.0.0b1":
 #     with warnings.catch_warnings():
@@ -30,11 +31,13 @@
 # else:
 #     xp = np
 devices = ["cpu"]
+
 try:
     with warnings.catch_warnings():
         warnings.simplefilter("ignore")
         import numpy.array_api as xp
 
+        numpy_has_array_api = True
         has_complex_dtype = np.dtype("complex128") in xp._dtypes._all_dtypes
 except ModuleNotFoundError:
     import numpy as xp  # noqa: ICN001
@@ -403,8 +406,23 @@ def test_ceil(device, x):
     assert xp.ceil(first(x)).dtype == result.dtype
 
 
+@pytest.mark.skipif(
+    not numpy_has_array_api, reason=f"testing in numpy version {np.__version__}"
+)
+@pytest.mark.parametrize("device", devices)
+def test_ceil_int_1(device, x_int):
+    result = ragged.ceil(x_int.to_device(device))
+    assert type(result) is type(x_int)
+    assert result.shape == x_int.shape
+    assert xp.ceil(first(x_int)) == np.array(first(result)).astype(first(result).dtype)
+    assert xp.ceil(first(x_int)).dtype == result.dtype
+
+
+@pytest.mark.skipif(
+    numpy_has_array_api, reason=f"testing in numpy version {np.__version__}"
+)
 @pytest.mark.parametrize("device", devices)
-def test_ceil_int(device, x_int):
+def test_ceil_int_2(device, x_int):
     result = ragged.ceil(x_int.to_device(device))
     assert type(result) is type(x_int)
     assert result.shape == x_int.shape
@@ -516,12 +534,31 @@ def test_floor(device, x):
     assert xp.floor(first(x)).dtype == result.dtype
 
 
+@pytest.mark.skipif(
+    not numpy_has_array_api, reason=f"testing in numpy version {np.__version__}"
+)
 @pytest.mark.parametrize("device", devices)
-def test_floor_int(device, x_int):
+def test_floor_int_1(device, x_int):
     result = ragged.floor(x_int.to_device(device))
     assert type(result) is type(x_int)
     assert result.shape == x_int.shape
-    assert xp.floor(first(x_int)) == first(result).astype(_wrapper(first(result).dtype))
+    assert xp.floor(first(x_int)) == np.asarray(first(result)).astype(
+        first(result).dtype
+    )
+    assert xp.floor(first(x_int)).dtype == result.dtype
+
+
+@pytest.mark.skipif(
+    numpy_has_array_api, reason=f"testing in numpy version {np.__version__}"
+)
+@pytest.mark.parametrize("device", devices)
+def test_floor_int_2(device, x_int):
+    result = ragged.floor(x_int.to_device(device))
+    assert type(result) is type(x_int)
+    assert result.shape == x_int.shape
+    assert xp.floor(first(x_int)) == np.asarray(first(result)).astype(
+        _wrapper(first(result).dtype)
+    )
     assert xp.floor(first(x_int)).dtype == _wrapper(result.dtype)