Consolidate cudf object handling in as_column

python/cudf/cudf/core/column/column.py

@@ -1873,6 +1873,7 @@ def as_column(
         If None (default), treats NaN values in arbitrary as null if there is
         no mask passed along with it. If True, combines the mask and NaNs to
         form a new validity mask. If False, leaves NaN values as is.
+        Only applies when arbitrary is not a cudf object (Index, Series, Column).
     dtype : optional
         Optionally typecast the constructed Column to the given
         dtype.
@@ -1909,22 +1910,17 @@ def as_column(
                 f'i{cudf.get_option("default_integer_bitwidth")//8}'
             )
         if dtype is not None:
-            column = column.astype(dtype)
+            return column.astype(dtype)
         return column
-    elif isinstance(arbitrary, ColumnBase):
+    elif isinstance(arbitrary, (ColumnBase, cudf.Series, cudf.BaseIndex)):
+        # Ignoring nan_as_null per the docstring
+        if isinstance(arbitrary, cudf.Series):
+            arbitrary = arbitrary._column
+        elif isinstance(arbitrary, cudf.BaseIndex):
+            arbitrary = arbitrary._values
         if dtype is not None:
             return arbitrary.astype(dtype)
-        else:
-            return arbitrary
-    elif isinstance(arbitrary, cudf.Series):
-        data = arbitrary._column
-        if dtype is not None:
-            data = data.astype(dtype)
-    elif isinstance(arbitrary, cudf.BaseIndex):
-        data = arbitrary._values
-        if dtype is not None:
-            data = data.astype(dtype)
-
+        return arbitrary
     elif hasattr(arbitrary, "__cuda_array_interface__"):
         desc = arbitrary.__cuda_array_interface__
         shape = desc["shape"]