Arm backend: Add 16A8W support and test for slice operation (#14215)

This PR was created by the merge bot to help merge the original PR into
the main branch.
ghstack PR number: #13798 by
@Ninja91
^ Please use this as the source of truth for the PR details, comments,
and reviews
ghstack PR base:
https://github.com/pytorch/executorch/tree/gh/Ninja91/11/base
ghstack PR head:
https://github.com/pytorch/executorch/tree/gh/Ninja91/11/head
Merge bot PR base:
https://github.com/pytorch/executorch/tree/gh/Ninja91/10/orig
Merge bot PR head:
https://github.com/pytorch/executorch/tree/gh/Ninja91/11/orig
@diff-train-skip-merge

---------

Co-authored-by: Nitin Jain <[email protected]>

Author: pytorchbot

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,
         )
 

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 +126,105 @@ 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)
+@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
+
+    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()