Add hardswish operator to Arm backend (#8136)

Signed-off-by: Tom Allsop <tom.allsop@arm.com>

Author: tom-arm

backends/arm/_passes/insert_table_ops.py

@@ -31,7 +31,7 @@ class InsertTableOpsPass(ExportPass):
     """
     For ops in self.table_ops they need to be serialized as a TOSA TABLE. This pass replaces these
     edge ops with a tosa._table(input: Tensor, target_str: str) where target_str == str(node.target).
-    When loweringthe _table node target_str will be used to find the corresponding torch operator
+    When lowering the _table node target_str will be used to find the corresponding torch operator
     which will be used to produce the table values in operators/op_table.py.
     """
 
@@ -43,6 +43,7 @@ class InsertTableOpsPass(ExportPass):
         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,
+        exir_ops.edge.aten.hardswish.default: torch.nn.functional.hardswish,
     }
 
     def __init__(self, exported_program: ExportedProgram) -> None:

backends/arm/arm_partitioner.py

@@ -115,6 +115,7 @@ def ops_to_not_decompose(
     ) -> Tuple[List[torch._ops.OpOverload], Optional[Callable[[torch.fx.Node], bool]]]:
         ops_to_not_decompose_if_quant_op = [
             torch.ops.aten.hardsigmoid.default,
+            torch.ops.aten.hardswish.default,
         ]
 
         def filter_fn(node: torch.fx.Node) -> bool:

backends/arm/operator_support/tosa_supported_operators.py

@@ -81,6 +81,7 @@ def is_node_supported(self, submodules, node: fx.Node) -> bool:
             exir_ops.edge.aten.permute_copy.default,
             exir_ops.edge.aten.hardsigmoid.default,
             exir_ops.edge.aten.hardtanh.default,
+            exir_ops.edge.aten.hardswish.default,
             exir_ops.edge.aten.convolution.default,
             exir_ops.edge.aten.div.Tensor,
             exir_ops.edge.aten.eq.Tensor,

backends/arm/quantizer/quantization_annotator.py

@@ -133,6 +133,7 @@ def _match_pattern(
     torch.ops.aten.tanh.default,
     torch.ops.aten.sum.dim_IntList,
     torch.ops.aten.hardsigmoid.default,
+    torch.ops.aten.hardswish.default,
 ]
 
 _one_to_one_shared_input_qspec = [

backends/arm/test/ops/test_hardswish.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 TestHardswish(unittest.TestCase):
+    class Hardswish(torch.nn.Module):
+        def __init__(self):
+            super().__init__()
+            self.hardswish = torch.nn.Hardswish()
+
+        def forward(self, x):
+            return self.hardswish(x)
+
+    def _test_hardswish_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.hardswish.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_hardswish_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.hardswish.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_hardswish_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.hardswish.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_hardswish_tosa_MI(
+        self,
+        test_name: str,
+        test_data: torch.Tensor,
+    ):
+        self._test_hardswish_tosa_MI_pipeline(self.Hardswish(), (test_data,))
+
+    @parameterized.expand(test_data_suite)
+    def test_hardswish_tosa_BI(self, test_name: str, test_data: torch.Tensor):
+        self._test_hardswish_tosa_BI_pipeline(self.Hardswish(), (test_data,))
+
+    @parameterized.expand(test_data_suite)
+    @pytest.mark.corstone_fvp
+    def test_hardswish_tosa_u55_BI(self, test_name: str, test_data: torch.Tensor):
+        self._test_hardswish_tosa_ethos_BI_pipeline(
+            common.get_u55_compile_spec(), self.Hardswish(), (test_data,)
+        )
+
+    @parameterized.expand(test_data_suite)
+    @pytest.mark.corstone_fvp
+    def test_hardswish_tosa_u85_BI(self, test_name: str, test_data: torch.Tensor):
+        self._test_hardswish_tosa_ethos_BI_pipeline(
+            common.get_u85_compile_spec(), self.Hardswish(), (test_data,)
+        )