Arm backend: Revert 16A8W ops test update for slice (#15088)

Summary:
This reverts the changes from D84262200 which removed xfails from tests
for 16A8W operations (Slice, Cat, Add, Mul, View, Transpose). After
landing, these tests are failing in GitHub CI.

Failed test:
https://github.com/pytorch/executorch/actions/runs/18439599594/job/52538228881
Differential Revision: D84564694




cc @freddan80 @per @zingo @oscarandersson8218 @digantdesai

Author: Ninja91

backends/arm/test/ops/test_slice.py

@@ -7,6 +7,7 @@
 
 from typing import Tuple
 
+import pytest
 import torch
 from executorch.backends.arm.quantizer.arm_quantizer import (
     get_symmetric_a16w8_quantization_config,
@@ -43,7 +44,6 @@
 
 
 class Slice(torch.nn.Module):
-
     def forward(self, x: torch.Tensor, s: list[tuple[int, int]]):
         slices = [slice(*i) for i in s]
         return x[slices]
@@ -153,6 +153,9 @@ def get_symmetric_a16w8_slice_quantizer(per_channel_quantization=False):
 
 
 @common.parametrize("test_data", test_data_suite)
+@pytest.mark.xfail(
+    reason="missing int16 slice ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13976"
+)
 def test_slice_tensor_16a8w_tosa_INT(test_data: torch.Tensor):
     """Test slice operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -178,6 +181,9 @@ def test_slice_tensor_16a8w_tosa_INT(test_data: torch.Tensor):
 
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone300
+@pytest.mark.xfail(
+    reason="Vela compilation fails with 'Invalid arguments' for int16 slice operations"
+)
 def test_slice_tensor_16a8w_u55_INT16(test_data: torch.Tensor):
     """Test slice operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -202,6 +208,9 @@ def test_slice_tensor_16a8w_u55_INT16(test_data: torch.Tensor):
 
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone320
+@pytest.mark.xfail(
+    reason="Vela compilation fails with 'Invalid arguments' for int16 slice operations"
+)
 def test_slice_tensor_16a8w_u85_INT16(test_data: torch.Tensor):
     """Test slice operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False