From 72660bec364696c23394482e08055cf84991e982 Mon Sep 17 00:00:00 2001 From: Nitin Jain Date: Mon, 13 Oct 2025 20:40:24 -0700 Subject: [PATCH] Revert D84262200: Updating tests for 16A8W ops which are supported (#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 --- backends/arm/test/ops/test_slice.py | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) diff --git a/backends/arm/test/ops/test_slice.py b/backends/arm/test/ops/test_slice.py index 7e71a51899a..bdf5ccda770 100644 --- a/backends/arm/test/ops/test_slice.py +++ b/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