Arm backend: Add asinh decomposition pass and test (#13035)

Add decomposition pass and tests for asinh.

Signed-off-by: Emma Kujala <[email protected]>

Author: emmakujala

backends/arm/_passes/__init__.py

@@ -26,6 +26,7 @@
 from .decompose_adaptive_avg_pool2d_pass import DecomposeAdaptiveAvgPool2dPass  # noqa
 from .decompose_addmm_pass import DecomposeAddmmPass  # noqa
 from .decompose_asin_pass import DecomposeAsinPass  # noqa
+from .decompose_asinh_pass import DecomposeAsinhPass  # noqa
 from .decompose_atan_pass import DecomposeAtanPass  # noqa
 from .decompose_atanh_pass import DecomposeAtanhPass  # noqa
 from .decompose_avg_pool2d import DecomposeAvgPool2d  # noqa

backends/arm/_passes/arm_pass_manager.py

@@ -30,6 +30,7 @@
     DecomposeAcoshPass,
     DecomposeAdaptiveAvgPool2dPass,
     DecomposeAddmmPass,
+    DecomposeAsinhPass,
     DecomposeAsinPass,
     DecomposeAtanhPass,
     DecomposeAtanPass,
@@ -114,7 +115,6 @@ def _tosa_080_BI_pipeline(self, exported_program: ExportedProgram) -> GraphModul
         self.add_pass(
             DecomposeMeanDimPass(exported_program.graph_module, self.tosa_spec)
         )
-
         self.add_pass(ConvertFullLikeToFullPass())
         self.add_pass(ConvertToClampPass())
         self.add_pass(ConvertMinMaxPass())
@@ -148,7 +148,6 @@ def _tosa_080_BI_pipeline(self, exported_program: ExportedProgram) -> GraphModul
         self.add_pass(DecomposeMaxPool2DPass())
         self.add_pass(SizeAdjustInputPass())
         self.add_pass(DecomposeSelectPass())
-
         self.add_pass(ConvertSqueezesToViewPass())
 
         self.add_pass(FuseViewCopyTransform())
@@ -167,6 +166,7 @@ def _tosa_080_MI_pipeline(self, exported_program: ExportedProgram) -> GraphModul
         self.add_pass(DecomposeRoundPass())
         self.add_pass(DecomposeAcoshPass())
         self.add_pass(DecomposeAsinPass())
+        self.add_pass(DecomposeAsinhPass())
         self.add_pass(DecomposeSqrtPass())
         self.add_pass(DecomposeAtanPass())
         self.add_pass(DecomposeAtanhPass())

backends/arm/_passes/decompose_asinh_pass.py

@@ -0,0 +1,50 @@
+# Copyright 2025 Arm Limited and/or its affiliates.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe
+
+
+from executorch.backends.arm._passes import ArmPass
+from executorch.exir.dialects._ops import ops as exir_ops
+
+# For MI case
+edge_asinh_op = (exir_ops.edge.aten.asinh.default,)
+
+
+class DecomposeAsinhPass(ArmPass):
+    """
+    Decomposes asinh to supported TOSA-operations.
+    This decomposition is based on the mathematical identity:
+        asinh(x) = log(x + sqrt(x^2 + 1))
+    """
+
+    def call_operator(self, op, args, kwargs, meta):
+        if op not in edge_asinh_op:
+            return super().call_operator(op, args, kwargs, meta)
+
+        log_op, sqrt_op, mul_op, add_op_scalar, add_op = (
+            exir_ops.edge.aten.log.default,
+            exir_ops.edge.aten.sqrt.default,
+            exir_ops.edge.aten.mul.Tensor,
+            exir_ops.edge.aten.add.Scalar,
+            exir_ops.edge.aten.add.Tensor,
+        )
+
+        x = args[0]
+
+        # calculate t1 = x^2 + 1
+        x2 = super().call_operator(mul_op, (x, x), {}, meta, True)
+        t1 = super().call_operator(add_op_scalar, (x2, 1.0), {}, meta, True)
+
+        # t2 = sqrt(t1)
+        t2 = super().call_operator(sqrt_op, (t1,), {}, meta, True)
+
+        # t3 = x + t2
+        t3 = super().call_operator(add_op, (x, t2), {}, meta, True)
+
+        # out = ln(t3)
+        out = super().call_operator(log_op, (t3,), {}, meta, True)
+
+        return out

backends/arm/_passes/insert_table_ops.py

@@ -58,6 +58,7 @@ class TableOps:
         exir_ops.edge.aten.sinh.default: torch.sinh,
         exir_ops.edge.aten.acosh.default: torch.acosh,
         exir_ops.edge.aten.asin.default: torch.asin,
+        exir_ops.edge.aten.asinh.default: torch.asinh,
     }
 
     # Targets that must be treated explicitly

backends/arm/operator_support/tosa_supported_operators.py

@@ -258,6 +258,7 @@ def is_node_supported(
             exir_ops.edge.aten.atanh.default,
             exir_ops.edge.aten.addmm.default,
             exir_ops.edge.aten.masked_fill.Scalar,
+            exir_ops.edge.aten.asinh.default,
         ]
 
         return supported

backends/arm/quantizer/quantization_annotator.py

@@ -219,6 +219,7 @@ def _match_pattern(
     torch.ops.aten.sign.default,
     torch.ops.aten.asin.default,
     torch.ops.aten.atanh.default,
+    torch.ops.aten.asinh.default,
 ]
 
 _one_to_one_shared_input_qspec = [

backends/arm/test/ops/test_asinh.py

@@ -0,0 +1,79 @@
+# Copyright 2025 Arm Limited and/or its affiliates.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+from typing import Tuple
+
+import torch
+
+from executorch.backends.arm.test import common
+from executorch.backends.arm.test.tester.test_pipeline import (
+    EthosU55PipelineBI,
+    EthosU85PipelineBI,
+    TosaPipelineBI,
+    TosaPipelineMI,
+)
+
+input_t = Tuple[torch.Tensor]  # Input x
+aten_op = "torch.ops.aten.asinh.default"
+
+test_data_suite = {
+    "zeros": lambda: torch.zeros(1, 5, 3, 2),
+    "ones": lambda: torch.ones(10, 10, 10),
+    "neg_ones": lambda: -torch.ones(10, 10, 10),
+    "rand": lambda: (torch.rand(10, 10) - 0.5) * 20,
+    "ramp": lambda: torch.linspace(-10.0, 10.0, steps=160),
+    "near_zero": lambda: torch.tensor([-1e-6, 0.0, 1e-6]),
+    "large": lambda: torch.tensor([-100.0, -10.0, 0.0, 10.0, 100.0]),
+    "rand_4d": lambda: torch.randn(1, 3, 4, 5),
+}
+
+
+class Asinh(torch.nn.Module):
+    def forward(self, x):
+        return torch.asinh(x)
+
+
+@common.parametrize("test_data", test_data_suite)
+def test_asin_tosa_MI(test_data: Tuple):
+    pipeline = TosaPipelineMI[input_t](
+        Asinh(),
+        (test_data(),),
+        aten_op,
+        exir_op=[],
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data_suite)
+def test_asin_tosa_BI(test_data: Tuple):
+    pipeline = TosaPipelineBI[input_t](
+        Asinh(),
+        (test_data(),),
+        aten_op=[],
+        exir_op=[],
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data_suite)
+@common.XfailIfNoCorstone300
+def test_asin_u55_BI(test_data: Tuple):
+    pipeline = EthosU55PipelineBI[input_t](
+        Asinh(),
+        (test_data(),),
+        aten_ops=[],
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data_suite)
+@common.XfailIfNoCorstone320
+def test_asin_u85_BI(test_data: Tuple):
+    pipeline = EthosU85PipelineBI[input_t](
+        Asinh(),
+        (test_data(),),
+        aten_ops=[],
+    )
+    pipeline.run()