Revert ndonnx device support

Author: crusaderky

array_api_compat/common/_helpers.py

@@ -645,7 +645,7 @@ def device(x: Array, /) -> Device:
     to_device : Move array data to a different device.
 
     """
-    if is_numpy_array(x) or is_ndonnx_array(x):
+    if is_numpy_array(x):
         return "cpu"
     elif is_dask_array(x):
         # Peek at the metadata of the Dask array to determine type

tests/_helpers.py

@@ -21,3 +21,14 @@ def import_(library, wrapper=False):
             library = 'array_api_compat.' + library
 
     return import_module(library)
+
+
+def xfail(request: pytest.FixtureRequest, reason: str) -> None:
+    """
+    XFAIL the currently running test.
+
+    Unlike ``pytest.xfail``, allow rest of test to execute instead of immediately
+    halting it, so that it may result in a XPASS.
+    xref https://github.com/pandas-dev/pandas/issues/38902
+    """
+    request.node.add_marker(pytest.mark.xfail(reason=reason))

tests/test_common.py

@@ -17,7 +17,8 @@
 from array_api_compat import (
     device, is_array_api_obj, is_lazy_array, is_writeable_array, size, to_device
 )
-from ._helpers import import_, wrapped_libraries, all_libraries
+from ._helpers import all_libraries, import_, wrapped_libraries, xfail
+
 
 is_array_functions = {
     'numpy': 'is_numpy_array',
@@ -188,7 +189,10 @@ class C:
 
 
 @pytest.mark.parametrize("library", all_libraries)
-def test_device(library):
+def test_device(library, request):
+    if library == "ndonnx":
+        xfail(request, reason="Needs ndonnx >=0.9.4")
+
     xp = import_(library, wrapper=True)
 
     # We can't test much for device() and to_device() other than that
@@ -226,24 +230,19 @@ def test_to_device_host(library):
 @pytest.mark.parametrize("target_library", is_array_functions.keys())
 @pytest.mark.parametrize("source_library", is_array_functions.keys())
 def test_asarray_cross_library(source_library, target_library, request):
-    def _xfail(reason: str) -> None:
-        # Allow rest of test to execute instead of immediately xfailing
-        # xref https://github.com/pandas-dev/pandas/issues/38902
-        request.node.add_marker(pytest.mark.xfail(reason=reason))
-
     if source_library == "dask.array" and target_library == "torch":
         # TODO: remove xfail once
         # https://github.com/dask/dask/issues/8260 is resolved
-        _xfail(reason="Bug in dask raising error on conversion")
+        xfail(request, reason="Bug in dask raising error on conversion")
     elif (
         source_library == "ndonnx" 
         and target_library not in ("array_api_strict", "ndonnx", "numpy")
     ):
-        _xfail(reason="The truth value of lazy Array Array(dtype=Boolean) is unknown")
+        xfail(request, reason="The truth value of lazy Array Array(dtype=Boolean) is unknown")
     elif source_library == "ndonnx" and target_library == "numpy":
-        _xfail(reason="produces numpy array of ndonnx scalar arrays")
+        xfail(request, reason="produces numpy array of ndonnx scalar arrays")
     elif source_library == "jax.numpy" and target_library == "torch":
-        _xfail(reason="casts int to float")
+        xfail(request, reason="casts int to float")
     elif source_library == "cupy" and target_library != "cupy":
         # cupy explicitly disallows implicit conversions to CPU
         pytest.skip(reason="cupy does not support implicit conversion to CPU")