Tweak test_asarray_cross_library

Author: crusaderky

tests/test_common.py

@@ -138,24 +138,24 @@ 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):
-    if source_library == "dask.array" and target_library == "torch":
+    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
-        request.node.add_marker(
-            pytest.mark.xfail(reason="Bug in dask raising error on conversion")
-        )
+        _xfail(reason="Bug in dask raising error on conversion")
     elif (
         source_library == "ndonnx" 
         and target_library not in ("array_api_strict", "ndonnx", "numpy")
     ):
-        request.node.add_marker(
-            pytest.mark.xfail(
-                reason="The truth value of lazy Array Array(dtype=Boolean) is unknown"
-            )
-        )        
+        _xfail(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")
+    elif source_library == "jax.numpy" and target_library == "torch":
+        _xfail(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")
@@ -166,10 +166,12 @@ def test_asarray_cross_library(source_library, target_library, request):
     tgt_lib = import_(target_library, wrapper=True)
     is_tgt_type = globals()[is_array_functions[target_library]]
 
-    a = src_lib.asarray([1, 2, 3])
+    a = src_lib.asarray([1, 2, 3], dtype=src_lib.int32)
     b = tgt_lib.asarray(a)
 
     assert is_tgt_type(b), f"Expected {b} to be a {tgt_lib.ndarray}, but was {type(b)}"
+    assert b.dtype == tgt_lib.int32
+
 
 @pytest.mark.parametrize("library", wrapped_libraries)
 def test_asarray_copy(library):