Arm backend: Add CEIL Operator

backends/arm/_passes/insert_table_ops.py

@@ -38,6 +38,7 @@ class InsertTableOpsPass(ExportPass):
     """
 
     table_ops: Dict[EdgeOpOverload, Callable[[torch.Tensor], torch.Tensor]] = {
+        exir_ops.edge.aten.ceil.default: torch.ceil,
         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

@@ -126,6 +126,7 @@ def is_node_supported(
             exir_ops.edge.aten.bitwise_xor.Tensor,
             exir_ops.edge.aten.expand_copy.default,
             exir_ops.edge.aten.cat.default,
+            exir_ops.edge.aten.ceil.default,
             exir_ops.edge.aten.clamp.default,
             exir_ops.edge.aten.bmm.default,
             exir_ops.edge.aten.permute_copy.default,

backends/arm/operators/ops_unary.py

@@ -53,5 +53,6 @@ def define_node(
     register_node_visitor(UnaryOperator)
 
 
+unary_operator_factory("aten.ceil.default", TosaOp.Op().CEIL)
 unary_operator_factory("aten.floor.default", TosaOp.Op().FLOOR)
 unary_operator_factory("aten.logical_not.default", TosaOp.Op().LOGICAL_NOT)

backends/arm/quantizer/quantization_annotator.py

@@ -126,6 +126,7 @@ def _match_pattern(
 
 _one_to_one = [
     torch.ops.aten.abs.default,
+    torch.ops.aten.ceil.default,
     torch.ops.aten.exp.default,
     torch.ops.aten.floor.default,
     torch.ops.aten.log.default,

backends/arm/test/ops/test_unary.py

@@ -0,0 +1,153 @@
+# 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_t1 = Tuple[torch.Tensor]  # Input x
+
+
+class Ceil(torch.nn.Module):
+    def forward(self, x: torch.Tensor):
+        return torch.ceil(x)
+
+    op_name = "ceil"
+    aten_op = "torch.ops.aten.ceil.default"
+    exir_op = "executorch_exir_dialects_edge__ops_aten_ceil_default"
+
+
+class Floor(torch.nn.Module):
+    def forward(self, x: torch.Tensor):
+        return torch.floor(x)
+
+    op_name = "floor"
+    aten_op = "torch.ops.aten.floor.default"
+    exir_op = "executorch_exir_dialects_edge__ops_aten_floor_default"
+
+
+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)
+
+
+test_data = {
+    "ceil_zeros": (
+        Ceil(),
+        zeros,
+    ),
+    "floor_zeros": (
+        Floor(),
+        zeros,
+    ),
+    "ceil_ones": (
+        Ceil(),
+        ones,
+    ),
+    "floor_ones": (
+        Floor(),
+        ones,
+    ),
+    "ceil_rand": (
+        Ceil(),
+        rand,
+    ),
+    "floor_rand": (
+        Floor(),
+        rand,
+    ),
+    "ceil_randn_pos": (
+        Ceil(),
+        randn_pos,
+    ),
+    "floor_randn_pos": (
+        Floor(),
+        randn_pos,
+    ),
+    "ceil_randn_neg": (
+        Ceil(),
+        randn_neg,
+    ),
+    "floor_randn_neg": (
+        Floor(),
+        randn_neg,
+    ),
+    "ceil_ramp": (
+        Ceil(),
+        ramp,
+    ),
+    "floor_ramp": (
+        Floor(),
+        ramp,
+    ),
+}
+
+
+@common.parametrize("test_data", test_data)
+def test_unary_tosa_MI(test_data: input_t1):
+    module = test_data[0]
+    pipeline = TosaPipelineMI[input_t1](
+        module, (test_data[1],), module.aten_op, module.exir_op
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data)
+def test_unary_tosa_BI(test_data: input_t1):
+    module = test_data[0]
+    pipeline = TosaPipelineBI[input_t1](
+        module, (test_data[1],), module.aten_op, module.exir_op
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data)
+def test_unary_u55_BI(test_data: input_t1):
+    module = test_data[0]
+    pipeline = EthosU55PipelineBI[input_t1](
+        module, (test_data[1],), module.aten_op, module.exir_op, run_on_fvp=False
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data)
+def test_unary_u85_BI(test_data: input_t1):
+    module = test_data[0]
+    pipeline = EthosU85PipelineBI[input_t1](
+        module, (test_data[1],), module.aten_op, module.exir_op, run_on_fvp=False
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data)
+@common.SkipIfNoCorstone300
+def test_unary_u55_BI_on_fvp(test_data: input_t1):
+    module = test_data[0]
+    pipeline = EthosU55PipelineBI[input_t1](
+        module, (test_data[1],), module.aten_op, module.exir_op, run_on_fvp=True
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data)
+@common.SkipIfNoCorstone320
+def test_unary_u85_BI_on_fvp(test_data: input_t1):
+    module = test_data[0]
+    pipeline = EthosU85PipelineBI[input_t1](
+        module, (test_data[1],), module.aten_op, module.exir_op, run_on_fvp=True
+    )
+    pipeline.run()