Arm backend: Add ERF operator

backends/arm/_passes/insert_table_ops.py

@@ -41,6 +41,7 @@ class TableOps:
     # Targets that follow a straigtforward one-to-one mapping to their table op
     unary_table_ops: Dict[EdgeOpOverload, Callable[[torch.Tensor], torch.Tensor]] = {
         exir_ops.edge.aten.ceil.default: torch.ceil,
+        exir_ops.edge.aten.erf.default: torch.erf,
         exir_ops.edge.aten.exp.default: torch.exp,
         exir_ops.edge.aten.floor.default: torch.floor,
         exir_ops.edge.aten.log.default: torch.log,

backends/arm/operator_support/tosa_supported_operators.py

@@ -166,6 +166,7 @@ def is_node_supported(
             exir_ops.edge.aten.div.Tensor,
             exir_ops.edge.aten.eq.Tensor,
             exir_ops.edge.aten.eq.Scalar,
+            exir_ops.edge.aten.erf.default,
             exir_ops.edge.aten.exp.default,
             exir_ops.edge.aten.log.default,
             exir_ops.edge.aten.linear.default,

backends/arm/operators/__init__.py

@@ -19,6 +19,7 @@
     op_constant_pad_nd,
     op_conv2d,
     op_eq,
+    op_erf,
     op_exp,
     op_full,
     op_ge,

backends/arm/operators/op_erf.py

@@ -0,0 +1,44 @@
+# 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 typing import List
+
+import serializer.tosa_serializer as ts  # type: ignore
+import torch.fx
+from executorch.backends.arm.operators.node_visitor import (
+    NodeVisitor,
+    register_node_visitor,
+)
+from executorch.backends.arm.tosa_mapping import TosaArg
+from executorch.backends.arm.tosa_specification import TosaSpecification
+from serializer.tosa_serializer import TosaOp
+
+
+@register_node_visitor
+class ERFVisitor_080_MI(NodeVisitor):
+    target = "aten.erf.default"
+
+    # BI case handled by op_table
+    tosa_specs = [TosaSpecification.create_from_string("TOSA-0.80+MI")]
+
+    def __init__(self, *args):
+        super().__init__(*args)
+
+    def define_node(
+        self,
+        node: torch.fx.Node,
+        tosa_graph: ts.TosaSerializer,
+        inputs: List[TosaArg],
+        output: TosaArg,
+    ) -> None:
+        if not (inputs[0].dtype == output.dtype):
+            raise ValueError(
+                "All inputs and output need same dtype."
+                f"Got {inputs[0].dtype=}, {output.dtype=}"
+            )
+        if not (inputs[0].dtype == ts.DType.FP32):
+            raise ValueError("All inputs need to be FP32." f"Got {inputs[0].dtype=}")
+        # MI lowering
+        tosa_graph.addOperator(TosaOp.Op().ERF, [inputs[0].name], [output.name])

backends/arm/quantizer/quantization_annotator.py

@@ -164,6 +164,7 @@ def _match_pattern(
 _one_to_one = [
     torch.ops.aten.abs.default,
     torch.ops.aten.ceil.default,
+    torch.ops.aten.erf.default,
     torch.ops.aten.exp.default,
     torch.ops.aten.floor.default,
     torch.ops.aten.log.default,

backends/arm/test/ops/test_erf.py

@@ -0,0 +1,63 @@
+# 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,
+)
+
+aten_op = "torch.ops.aten.erf.default"
+exir_op = "executorch_exir_dialects_edge__ops_aten_erf_default"
+input_t1 = Tuple[torch.Tensor]  # Input x
+
+
+class Erf(torch.nn.Module):
+    def forward(self, x: torch.Tensor):
+        return torch.erf(x)
+
+    test_data: dict[str, input_t1] = {
+        "zeros": (torch.zeros(1, 10, 10, 10),),
+        "ones": (torch.ones(10, 10, 10),),
+        "rand": ((torch.rand(10, 10) - 0.5),),
+        "randn_pos": ((torch.randn(1, 4, 4, 4) + 10),),
+        "randn_neg": ((torch.randn(1, 4, 4, 4) - 10),),
+        "ramp": (torch.arange(-16, 16, 0.2),),
+    }
+
+
+@common.parametrize("test_data", Erf.test_data)
+def test_erf_tosa_MI(test_data: input_t1):
+    pipeline = TosaPipelineMI[input_t1](Erf(), test_data, aten_op, exir_op)
+    pipeline.run()
+
+
+@common.parametrize("test_data", Erf.test_data)
+def test_erf_tosa_BI(test_data: input_t1):
+    pipeline = TosaPipelineBI[input_t1](Erf(), test_data, aten_op, exir_op)
+    pipeline.run()
+
+
+@common.parametrize("test_data", Erf.test_data)
+@common.XfailIfNoCorstone300
+def test_erf_u55_BI(test_data: input_t1):
+    pipeline = EthosU55PipelineBI[input_t1](
+        Erf(), test_data, aten_op, exir_op, run_on_fvp=True
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", Erf.test_data)
+@common.XfailIfNoCorstone320
+def test_erf_u85_BI(test_data: input_t1):
+    pipeline = EthosU85PipelineBI[input_t1](
+        Erf(), test_data, aten_op, exir_op, run_on_fvp=True
+    )
+    pipeline.run()