Construct NumPy arrays correctly from 0D deferred arrays backed by re…

…gion fields (nv-legate#551)

* Handle inline allocations from 0D stores correctly (spoiler: they are not 0D)

* Add a test case for 0D region-backed stores

cunumeric/deferred.py

@@ -286,7 +286,10 @@ def construct_ndarray(
                 initializer = _CuNumericNDarray(
                     shape, self.dtype, address, strides, False
                 )
-                return np.asarray(initializer)
+                result = np.asarray(initializer)
+                if self.shape == ():
+                    result = result.reshape(())
+                return result
 
             result = cast("npt.NDArray[Any]", alloc.consume(construct_ndarray))
 

tests/integration/test_slicing.py

@@ -68,6 +68,18 @@ def test_3d():
     assert np.array_equal(firstslice, firstslicegold)
 
 
+def test_0d():
+    in_np = np.array([1, 2])
+    in_num = num.array([1, 2])
+
+    sl_np = in_np[1:].reshape(())
+    sl_num = in_num[1:].reshape(())
+
+    # Test inline mapping for a 0-d array
+    print(sl_num)
+    assert np.array_equal(sl_np, sl_num)
+
+
 # TODO: Legate needs 4-D arrays for this to work correctly
 @pytest.mark.skip
 def test_4d():