Fix cumsum with dtype specified

ndonnx/_core/_numericimpl.py

@@ -568,18 +568,17 @@ def cumulative_sum(
             else:
                 raise ValueError("axis must be specified for multi-dimensional arrays")
 
-        if dtype is None:
-            if isinstance(x.dtype, (dtypes.Unsigned, dtypes.NullableUnsigned)):
-                if ndx.iinfo(x.dtype).bits < 64:
-                    out = x.astype(dtypes.int64)
-                else:
-                    raise ndx.UnsupportedOperationError(
-                        f"Cannot perform `cumulative_sum` using {x.dtype}"
-                    )
+        if isinstance(x.dtype, (dtypes.Unsigned, dtypes.NullableUnsigned)):
+            if ndx.iinfo(x.dtype).bits < 64:
+                out = x.astype(dtypes.int64)
             else:
-                out = x.astype(_determine_reduce_op_dtype(x, dtype, dtypes.int64))
+                return NotImplemented
+        elif dtype == dtypes.uint64 or dtype == dtypes.nuint64:
+            raise ndx.UnsupportedOperationError(
+                f"Unsupported dtype parameter for cumulative_sum {dtype} due to missing kernel support"
+            )
         else:
-            out = out.astype(dtype)
+            out = x.astype(_determine_reduce_op_dtype(x, None, dtypes.int64))
 
         out = from_corearray(
             opx.cumsum(
@@ -589,10 +588,13 @@ def cumulative_sum(
             )
         )
 
-        if isinstance(x.dtype, dtypes.Unsigned):
-            out = out.astype(ndx.uint64)
-        elif isinstance(x.dtype, dtypes.NullableUnsigned):
-            out = out.astype(ndx.nuint64)
+        if dtype is None:
+            if isinstance(x.dtype, dtypes.Unsigned):
+                out = out.astype(ndx.uint64)
+            elif isinstance(x.dtype, dtypes.NullableUnsigned):
+                out = out.astype(ndx.nuint64)
+        else:
+            out = out.astype(dtype)
 
         # Exclude axis and create zeros of that shape
         if include_initial:

ndonnx/_data_types/coretype.py

@@ -69,7 +69,11 @@ def _parse_input(self, data: np.ndarray) -> dict[str, np.ndarray]:
 
     def _cast_from(self, array: Array) -> Array:
         if isinstance(array.dtype, CoreType):
-            return ndx.Array._from_fields(self, data=opx.cast(array._core(), to=self))
+            return (
+                ndx.Array._from_fields(self, data=opx.cast(array._core(), to=self))
+                if array.dtype != self
+                else array.copy()
+            )
         else:
             raise CastError(f"Cannot cast from {array.dtype} to {self}")
 

tests/test_core.py

@@ -933,13 +933,14 @@ def test_dynamic_reshape_has_no_static_shape(x, shape):
 )
 @pytest.mark.parametrize("include_initial", [True, False])
 @pytest.mark.parametrize(
-    "dtype",
+    "array_dtype",
     [ndx.int32, ndx.int64, ndx.float32, ndx.float64, ndx.uint8, ndx.uint16, ndx.uint32],
 )
 @pytest.mark.parametrize(
     "array, axis",
     [
         ([1, 2, 3], None),
+        ([100, 100], None),
         ([1, 2, 3], 0),
         ([[1, 2], [3, 4]], 0),
         ([[1, 2], [3, 4]], 1),
@@ -948,21 +949,36 @@ def test_dynamic_reshape_has_no_static_shape(x, shape):
         ([[[[1]]], [[[3]]]], 1),
     ],
 )
-def test_cumulative_sum(array, axis, include_initial, dtype):
-    a = ndx.asarray(array, dtype=dtype)
+@pytest.mark.parametrize(
+    "cumsum_dtype",
+    [None, ndx.int32, ndx.float32, ndx.float64, ndx.uint8, ndx.int8],
+)
+def test_cumulative_sum(array, axis, include_initial, array_dtype, cumsum_dtype):
+    a = ndx.asarray(array, dtype=array_dtype)
     assert_array_equal(
-        ndx.cumulative_sum(a, include_initial=include_initial, axis=axis).to_numpy(),
+        ndx.cumulative_sum(
+            a, include_initial=include_initial, axis=axis, dtype=cumsum_dtype
+        ).to_numpy(),
         np.cumulative_sum(
             np.asarray(array, a.dtype.to_numpy_dtype()),
             include_initial=include_initial,
             axis=axis,
+            dtype=cumsum_dtype.to_numpy_dtype() if cumsum_dtype is not None else None,
         ),
     )
 
 
 def test_no_unsafe_cumulative_sum_cast():
     with pytest.raises(
-        ndx.UnsupportedOperationError, match="Cannot perform `cumulative_sum`"
+        ndx.UnsupportedOperationError,
+        match="Unsupported operand type for cumulative_sum",
     ):
         a = ndx.asarray([1, 2, 3], ndx.uint64)
         ndx.cumulative_sum(a)
+
+    with pytest.raises(
+        ndx.UnsupportedOperationError,
+        match="Unsupported dtype parameter for cumulative_sum",
+    ):
+        a = ndx.asarray([1, 2, 3], ndx.int32)
+        ndx.cumulative_sum(a, dtype=ndx.uint64)