[Fix] fix slice negative axis (PaddlePaddle#59272)

python/paddle/tensor/manipulation.py

@@ -313,28 +313,26 @@ def slice(input, axes, starts, ends):
             >>> sliced_2 = paddle.slice(input, axes=axes, starts=[minus_3, 0, 2], ends=ends)
             >>> # sliced_2 is input[1:3, 0:2, 2:4].
     """
+    if isinstance(axes, (list, tuple)):
+        axes = list(axes)
+        if len(axes) == 0:
+            raise ValueError("Input axes should not be an empty list/tuple.")
+        for i in range(len(axes)):
+            if axes[i] < 0:
+                axes[i] = max(0, axes[i] + len(input.shape))
+            else:
+                axes[i] = min(len(input.shape) - 1, axes[i])
+
+    else:
+        raise ValueError(
+            f"Input axes must be a python list or tuple, but reveived {type(axes)}"
+        )
+
     if in_dynamic_mode():
         attrs = ()
         starts_tensor = None
         ends_tensor = None
 
-        if isinstance(axes, (list, tuple)):
-            axes = list(axes)
-            if len(axes) == 0:
-                raise ValueError(
-                    "Input axes should not be an empty list/tuple."
-                )
-            for i in range(len(axes)):
-                if axes[i] < 0:
-                    axes[i] = max(0, axes[i] + len(input.shape))
-                else:
-                    axes[i] = min(len(input.shape) - 1, axes[i])
-
-        else:
-            raise ValueError(
-                f"Input axes must be a python list or tuple, but reveived {type(axes)}"
-            )
-
         infer_flags = [1 for i in range(len(axes))]
 
         if isinstance(starts, (list, tuple)):

test/legacy_test/test_slice_op.py

@@ -734,6 +734,73 @@ def test_pir(self):
             np.testing.assert_array_equal(res_6, input[-3:3, 0:100, :, 2:-1])
             # np.testing.assert_array_equal(res_7, input[-1, 0:100, :, 2:-1])
 
+    # Test negative axis
+    def test_negative_axis_dygraph(self):
+        with paddle.base.dygraph.guard():
+            input = np.random.random([3, 4, 5, 6]).astype("float64")
+
+            res = paddle.slice(
+                paddle.to_tensor(input), axes=[-2], starts=[2], ends=[3]
+            )
+            np.testing.assert_array_equal(res, input[:, :, 2:3, :])
+
+    def test_negative_axis_static(self):
+        with paddle_static_guard(), paddle.static.program_guard(
+            paddle.static.Program()
+        ):
+            input = np.random.random([3, 4, 5, 6]).astype("float64")
+            x = paddle.static.data(
+                name="x",
+                shape=[3, 4, 5, 6],
+                dtype="float64",
+            )
+
+            out = paddle.slice(
+                x,
+                axes=[-2],
+                starts=[2],
+                ends=[3],
+            )
+
+            exe = base.Executor(place=base.CPUPlace())
+            res = exe.run(
+                feed={
+                    "x": input,
+                },
+                fetch_list=[out],
+            )[0]
+
+            np.testing.assert_array_equal(res, input[:, :, 2:3, :])
+
+    def test_negative_axis_pir(self):
+        with paddle.pir_utils.IrGuard(), paddle.static.program_guard(
+            paddle.static.Program()
+        ):
+            input = np.random.random([3, 4, 5, 6]).astype("float64")
+            x = paddle.static.data(
+                name="x",
+                shape=[3, 4, 5, 6],
+                dtype="float64",
+            )
+
+            out = paddle.slice(
+                x,
+                axes=[-2],
+                starts=[2],
+                ends=[3],
+            )
+
+            exe = base.Executor(place=base.CPUPlace())
+            res = exe.run(
+                paddle.static.default_main_program(),
+                feed={
+                    "x": input,
+                },
+                fetch_list=[out],
+            )[0]
+
+            np.testing.assert_array_equal(res, input[:, :, 2:3, :])
+
 
 class TestSliceApiWithTensor(unittest.TestCase):
     def test_starts_ends_is_tensor(self):