Arm backend: Add hardsigmoid operator (#8091)

* Add filter_fn to ops_to_not_decompose, to filter out quantized candidate ops
* Added aten.hardsigmoid as a table op for the BI case

Signed-off-by: Tom Allsop <[email protected]>

Author: tom-arm

backends/arm/_passes/insert_table_ops.py

@@ -42,6 +42,7 @@ class InsertTableOpsPass(ExportPass):
         exir_ops.edge.aten.rsqrt.default: torch.rsqrt,
         exir_ops.edge.aten.sigmoid.default: torch.sigmoid,
         exir_ops.edge.aten.tanh.default: torch.tanh,
+        exir_ops.edge.aten.hardsigmoid.default: torch.nn.functional.hardsigmoid,
     }
 
     def __init__(self, exported_program: ExportedProgram) -> None:

backends/arm/arm_partitioner.py

@@ -113,8 +113,40 @@ def ops_to_not_decompose(
         self,
         ep: ExportedProgram,
     ) -> Tuple[List[torch._ops.OpOverload], Optional[Callable[[torch.fx.Node], bool]]]:
+        ops_to_not_decompose_if_quant_op = [
+            torch.ops.aten.hardsigmoid.default,
+        ]
+
+        def filter_fn(node: torch.fx.Node) -> bool:
+            # This function filters for operators to not decompose where:
+            #   - It's target is in ops_to_not_decompose_if_quant_op list.
+            #   - All it's inputs/outputs are quantize operators.
+            dq = torch.ops.quantized_decomposed.dequantize_per_tensor.default
+            q = torch.ops.quantized_decomposed.quantize_per_tensor.default
+
+            if node.target in ops_to_not_decompose_if_quant_op:
+                # Assume we should not decompose the operator (it is quantized)
+                should_not_decompose = True
+
+                input_nodes = node.all_input_nodes
+                ouput_nodes = node.users
+
+                for inp in input_nodes:
+                    if inp.target != dq:
+                        should_not_decompose = False
+
+                for out in ouput_nodes:
+                    if out.target != q:
+                        should_not_decompose = False
+
+                return should_not_decompose
+
+            # Be default, do not decompose the operator
+            return True
+
         ops_to_not_decompose = [
             torch.ops.aten.linear.default,
             torch.ops.aten.upsample_nearest2d.vec,
-        ]
-        return (ops_to_not_decompose, None)
+        ] + ops_to_not_decompose_if_quant_op
+
+        return (ops_to_not_decompose, filter_fn)

backends/arm/operator_support/tosa_supported_operators.py

@@ -79,6 +79,7 @@ def is_node_supported(self, submodules, node: fx.Node) -> bool:
             exir_ops.edge.aten.clamp.default,
             exir_ops.edge.aten.bmm.default,
             exir_ops.edge.aten.permute_copy.default,
+            exir_ops.edge.aten.hardsigmoid.default,
             exir_ops.edge.aten.hardtanh.default,
             exir_ops.edge.aten.convolution.default,
             exir_ops.edge.aten.div.Tensor,

backends/arm/quantizer/quantization_annotator.py

@@ -132,6 +132,7 @@ def _match_pattern(
     torch.ops.aten.sigmoid.default,
     torch.ops.aten.tanh.default,
     torch.ops.aten.sum.dim_IntList,
+    torch.ops.aten.hardsigmoid.default,
 ]
 
 _one_to_one_shared_input_qspec = [

backends/arm/test/ops/test_hardsigmoid.py

@@ -0,0 +1,128 @@
+# Copyright 2025 Arm Limited and/or its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+import unittest
+
+from typing import Tuple
+
+import pytest
+import torch
+
+from executorch.backends.arm.test import common, conftest
+from executorch.backends.arm.test.tester.arm_tester import ArmTester
+from executorch.exir.backend.compile_spec_schema import CompileSpec
+from parameterized import parameterized
+
+
+test_data_suite = [
+    # (test_name, test_data)
+    ("zeros", torch.zeros(1, 10, 10, 10)),
+    ("ones", torch.ones(10, 10, 10)),
+    ("rand", torch.rand(10, 10) - 0.5),
+    ("randn_pos", torch.randn(10) + 10),
+    ("randn_neg", torch.randn(10) - 10),
+    ("ramp", torch.arange(-16, 16, 0.2)),
+]
+
+
+class TestHardsigmoid(unittest.TestCase):
+    class Hardsigmoid(torch.nn.Module):
+        def __init__(self):
+            super().__init__()
+            self.hardsigmoid = torch.nn.Hardsigmoid()
+
+        def forward(self, x):
+            return self.hardsigmoid(x)
+
+    def _test_hardsigmoid_tosa_MI_pipeline(
+        self, module: torch.nn.Module, test_data: Tuple[torch.tensor]
+    ):
+        (
+            ArmTester(
+                module,
+                example_inputs=test_data,
+                compile_spec=common.get_tosa_compile_spec("TOSA-0.80+MI"),
+            )
+            .export()
+            .check(["torch.ops.aten.hardsigmoid.default"])
+            .check_not(["torch.ops.quantized_decomposed"])
+            .to_edge_transform_and_lower()
+            .check_not(["executorch_exir_dialects_edge__ops_aten_clamp_default"])
+            .check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
+            .to_executorch()
+            .run_method_and_compare_outputs(inputs=test_data)
+        )
+
+    def _test_hardsigmoid_tosa_BI_pipeline(
+        self, module: torch.nn.Module, test_data: Tuple
+    ):
+        (
+            ArmTester(
+                module,
+                example_inputs=test_data,
+                compile_spec=common.get_tosa_compile_spec("TOSA-0.80+BI"),
+            )
+            .quantize()
+            .export()
+            .check(["torch.ops.aten.hardsigmoid.default"])
+            .check(["torch.ops.quantized_decomposed"])
+            .to_edge_transform_and_lower()
+            .check_not(["executorch_exir_dialects_edge__ops_aten_clamp_default"])
+            .check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
+            .to_executorch()
+            .run_method_and_compare_outputs(inputs=test_data)
+        )
+
+    def _test_hardsigmoid_tosa_ethos_BI_pipeline(
+        self,
+        compile_spec: list[CompileSpec],
+        module: torch.nn.Module,
+        test_data: Tuple[torch.tensor],
+    ):
+        tester = (
+            ArmTester(
+                module,
+                example_inputs=test_data,
+                compile_spec=compile_spec,
+            )
+            .quantize()
+            .export()
+            .check_count({"torch.ops.aten.hardsigmoid.default": 1})
+            .check(["torch.ops.quantized_decomposed"])
+            .to_edge_transform_and_lower()
+            .check_not(["executorch_exir_dialects_edge__ops_aten_clamp_default"])
+            .check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
+            .to_executorch()
+            .serialize()
+        )
+        if conftest.is_option_enabled("corstone_fvp"):
+            tester.run_method_and_compare_outputs(qtol=1, inputs=test_data)
+
+    @parameterized.expand(test_data_suite)
+    def test_hardsigmoid_tosa_MI(
+        self,
+        test_name: str,
+        test_data: torch.Tensor,
+    ):
+        self._test_hardsigmoid_tosa_MI_pipeline(self.Hardsigmoid(), (test_data,))
+
+    @parameterized.expand(test_data_suite)
+    def test_hardsigmoid_tosa_BI(self, test_name: str, test_data: torch.Tensor):
+        self._test_hardsigmoid_tosa_BI_pipeline(self.Hardsigmoid(), (test_data,))
+
+    @parameterized.expand(test_data_suite)
+    @pytest.mark.corstone_fvp
+    def test_hardsigmoid_tosa_u55_BI(self, test_name: str, test_data: torch.Tensor):
+        self._test_hardsigmoid_tosa_ethos_BI_pipeline(
+            common.get_u55_compile_spec(), self.Hardsigmoid(), (test_data,)
+        )
+
+    @parameterized.expand(test_data_suite)
+    @pytest.mark.corstone_fvp
+    def test_hardsigmoid_tosa_u85_BI(self, test_name: str, test_data: torch.Tensor):
+        self._test_hardsigmoid_tosa_ethos_BI_pipeline(
+            common.get_u85_compile_spec(), self.Hardsigmoid(), (test_data,)
+        )