From 82818693e267f5e857400f96b264f96e18cc8191 Mon Sep 17 00:00:00 2001
From: Nitin Jain <jainnitin@meta.com>
Date: Thu, 28 Aug 2025 23:42:52 -0700
Subject: [PATCH] Add 16A8W support and test for slice operation

Add 16A8W quantization support and test for the slice operation in ExecutorTorch ARM backend.

This follows the pattern established for linear, mul, sigmoid, and tanh operations, extending int16 support to slice operations.

Changes:
- Add INT16 dtype validation support in op_slice.py
- Add test_slice_tensor_16a8w_tosa_INT test function
- Enable test_slice.py in test targets configuration

The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency.

Differential Revision: [D80511095](https://our.internmc.facebook.com/intern/diff/D80511095/)

[ghstack-poisoned]
---
 backends/arm/operators/op_slice.py  |   2 +-
 backends/arm/test/ops/test_slice.py | 108 +++++++++++++++++++++++++++-
 2 files changed, 108 insertions(+), 2 deletions(-)

diff --git a/backends/arm/operators/op_slice.py b/backends/arm/operators/op_slice.py
index 56115073ce1..2e1e3236b09 100644
--- a/backends/arm/operators/op_slice.py
+++ b/backends/arm/operators/op_slice.py
@@ -57,7 +57,7 @@ def define_node(
         validate_valid_dtype(
             self.target,
             [inputs[0], output],
-            [ts.DType.INT8, ts.DType.INT32, ts.DType.FP32],
+            [ts.DType.INT8, ts.DType.INT16, ts.DType.INT32, ts.DType.FP32],
             output.tosa_spec,
         )
 
diff --git a/backends/arm/test/ops/test_slice.py b/backends/arm/test/ops/test_slice.py
index 915aec2e522..81563413c1f 100644
--- a/backends/arm/test/ops/test_slice.py
+++ b/backends/arm/test/ops/test_slice.py
@@ -7,9 +7,14 @@
 
 from typing import Tuple
 
+import pytest
 import torch
+from executorch.backends.arm.quantizer.arm_quantizer import (
+    get_symmetric_a16w8_quantization_config,
+    TOSAQuantizer,
+)
 
-from executorch.backends.arm.test import common
+from executorch.backends.arm.test import common, conftest
 
 from executorch.backends.arm.test.tester.test_pipeline import (
     EthosU55PipelineINT,
@@ -18,6 +23,8 @@
     TosaPipelineINT,
     VgfPipeline,
 )
+from executorch.backends.arm.tosa_specification import TosaSpecification
+from executorch.backends.xnnpack.test.tester import Quantize
 
 aten_op = "torch.ops.aten.slice.Tensor"
 exir_op = "executorch_exir_dialects_edge__ops_aten_slice_copy"
@@ -119,3 +126,102 @@ def test_slice_tensor_vgf_INT(test_data: torch.Tensor):
         tosa_version="TOSA-1.0+INT",
     )
     pipeline.run()
+
+
+def get_symmetric_a16w8_slice_quantizer(per_channel_quantization=False):
+    tosa_version = conftest.get_option("tosa_version")
+    tosa_profiles = {
+        "1.0": TosaSpecification.create_from_string("TOSA-1.0+INT+int16"),
+    }
+
+    quantizer = TOSAQuantizer(tosa_profiles[tosa_version])
+    quantizer.set_global(
+        get_symmetric_a16w8_quantization_config(is_per_channel=per_channel_quantization)
+    )
+
+    return Quantize(
+        quantizer,
+        get_symmetric_a16w8_quantization_config(
+            is_per_channel=per_channel_quantization
+        ),
+    )
+
+
+@common.parametrize("test_data", test_data_suite)
+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
+
+    pipeline = TosaPipelineINT[input_t1](
+        Slice(),
+        test_data(),
+        aten_op,
+        exir_op=[],
+        per_channel_quantization=per_channel_quantization,
+        use_to_edge_transform_and_lower=True,
+        tosa_extensions=["int16"],
+    )
+
+    pipeline.change_args(
+        "quantize",
+        get_symmetric_a16w8_slice_quantizer(
+            per_channel_quantization=per_channel_quantization
+        ),
+    )
+    pipeline.run()
+
+
+@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
+
+    pipeline = EthosU55PipelineINT[input_t1](
+        Slice(),
+        test_data(),
+        aten_ops=[],
+        exir_ops=[],
+        per_channel_quantization=per_channel_quantization,
+        use_to_edge_transform_and_lower=True,
+        run_on_fvp=True,
+    )
+
+    pipeline.change_args(
+        "quantize",
+        get_symmetric_a16w8_slice_quantizer(
+            per_channel_quantization=per_channel_quantization
+        ),
+    )
+    pipeline.run()
+
+
+@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
+
+    pipeline = EthosU85PipelineINT[input_t1](
+        Slice(),
+        test_data(),
+        aten_ops=[],
+        exir_ops=[],
+        per_channel_quantization=per_channel_quantization,
+        use_to_edge_transform_and_lower=True,
+        run_on_fvp=True,
+    )
+
+    pipeline.change_args(
+        "quantize",
+        get_symmetric_a16w8_slice_quantizer(
+            per_channel_quantization=per_channel_quantization
+        ),
+    )
+    pipeline.run()