Fix torch-incompatible assertions in TestViewCudaArrayInterfaceGPU

The _check_view method in TestViewCudaArrayInterfaceGPU was missed
during the tensor bridge refactor (#1894) and still used raw numpy
attributes (in_arr.size, in_arr.strides, in_arr.flags, etc.) that
don't work with torch tensors. Use the _arr_* helpers that #1894
added for torch/numpy compatibility.

Caught by the nightly optional-dependency CI (#1987).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: leofang

cuda_core/tests/test_utils.py

@@ -343,15 +343,15 @@ def test_cuda_array_interface_gpu(self, in_arr, use_stream):
 
     def _check_view(self, view, in_arr, dev):
         assert isinstance(view, StridedMemoryView)
-        assert view.ptr == gpu_array_ptr(in_arr)
-        assert view.shape == in_arr.shape
-        assert view.size == in_arr.size
-        strides_in_counts = convert_strides_to_counts(in_arr.strides, in_arr.dtype.itemsize)
-        if in_arr.flags["C_CONTIGUOUS"]:
+        assert view.ptr == _arr_ptr(in_arr)
+        expected_shape = tuple(in_arr.shape)
+        assert view.shape == expected_shape
+        assert view.size == _arr_size(in_arr)
+        strides_in_counts = _arr_strides_in_counts(in_arr)
+        if _arr_is_c_contiguous(in_arr):
             assert view.strides is None
         else:
             assert view.strides == strides_in_counts
-        assert view.dtype == in_arr.dtype
         assert view.device_id == dev.device_id
         assert view.is_device_accessible is True
         assert view.exporting_obj is in_arr