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maddun01maddun01
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Arm backend: Add CEIL Operator (#9267)
Arm backend: support for CEIL op - Update unary operator factory with CEIL op - Rename and refactor test_floor to handle similar ops Signed-off-by: Madeleine Dunn <[email protected]>
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-82
lines changed

6 files changed

+157
-82
lines changed

‎backends/arm/_passes/insert_table_ops.py

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@@ -41,6 +41,7 @@ class InsertTableOpsPass(ExportPass):
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"""
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table_ops: Dict[EdgeOpOverload, Callable[[torch.Tensor], torch.Tensor]] = {
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exir_ops.edge.aten.ceil.default: torch.ceil,
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exir_ops.edge.aten.exp.default: torch.exp,
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exir_ops.edge.aten.floor.default: torch.floor,
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exir_ops.edge.aten.log.default: torch.log,

‎backends/arm/operator_support/tosa_supported_operators.py

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@@ -147,6 +147,7 @@ def is_node_supported(
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exir_ops.edge.aten.bitwise_xor.Tensor,
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exir_ops.edge.aten.expand_copy.default,
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exir_ops.edge.aten.cat.default,
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exir_ops.edge.aten.ceil.default,
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exir_ops.edge.aten.clamp.default,
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exir_ops.edge.aten.bmm.default,
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exir_ops.edge.aten.permute_copy.default,

‎backends/arm/operators/ops_unary.py

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

‎backends/arm/quantizer/quantization_annotator.py

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

‎backends/arm/test/ops/test_floor.py

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This file was deleted.

‎backends/arm/test/ops/test_unary.py

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# Copyright 2025 Arm Limited and/or its affiliates.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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from typing import Tuple
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import torch
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from executorch.backends.arm.test import common
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from executorch.backends.arm.test.tester.test_pipeline import (
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EthosU55PipelineBI,
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EthosU85PipelineBI,
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TosaPipelineBI,
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TosaPipelineMI,
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)
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input_t1 = Tuple[torch.Tensor] # Input x
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class Ceil(torch.nn.Module):
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def forward(self, x: torch.Tensor):
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return torch.ceil(x)
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op_name = "ceil"
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aten_op = "torch.ops.aten.ceil.default"
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exir_op = "executorch_exir_dialects_edge__ops_aten_ceil_default"
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class Floor(torch.nn.Module):
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def forward(self, x: torch.Tensor):
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return torch.floor(x)
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op_name = "floor"
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aten_op = "torch.ops.aten.floor.default"
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exir_op = "executorch_exir_dialects_edge__ops_aten_floor_default"
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zeros = torch.zeros(1, 10, 10, 10)
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ones = torch.ones(10, 10, 10)
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rand = torch.rand(10, 10) - 0.5
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randn_pos = torch.randn(1, 4, 4, 4) + 10
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randn_neg = torch.randn(1, 4, 4, 4) - 10
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ramp = torch.arange(-16, 16, 0.2)
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test_data = {
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"ceil_zeros": (
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Ceil(),
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zeros,
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),
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"floor_zeros": (
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Floor(),
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zeros,
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),
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"ceil_ones": (
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Ceil(),
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ones,
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),
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"floor_ones": (
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Floor(),
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ones,
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),
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"ceil_rand": (
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Ceil(),
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rand,
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),
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"floor_rand": (
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Floor(),
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rand,
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),
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"ceil_randn_pos": (
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Ceil(),
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randn_pos,
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),
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"floor_randn_pos": (
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Floor(),
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randn_pos,
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),
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"ceil_randn_neg": (
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Ceil(),
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randn_neg,
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),
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"floor_randn_neg": (
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Floor(),
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randn_neg,
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),
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"ceil_ramp": (
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Ceil(),
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ramp,
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),
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"floor_ramp": (
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Floor(),
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ramp,
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),
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}
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@common.parametrize("test_data", test_data)
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def test_unary_tosa_MI(test_data: input_t1):
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module = test_data[0]
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pipeline = TosaPipelineMI[input_t1](
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module, (test_data[1],), module.aten_op, module.exir_op
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)
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pipeline.run()
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@common.parametrize("test_data", test_data)
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def test_unary_tosa_BI(test_data: input_t1):
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module = test_data[0]
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pipeline = TosaPipelineBI[input_t1](
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module, (test_data[1],), module.aten_op, module.exir_op
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)
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pipeline.run()
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@common.parametrize("test_data", test_data)
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def test_unary_u55_BI(test_data: input_t1):
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module = test_data[0]
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pipeline = EthosU55PipelineBI[input_t1](
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module, (test_data[1],), module.aten_op, module.exir_op, run_on_fvp=False
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)
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pipeline.run()
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@common.parametrize("test_data", test_data)
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def test_unary_u85_BI(test_data: input_t1):
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module = test_data[0]
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pipeline = EthosU85PipelineBI[input_t1](
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module, (test_data[1],), module.aten_op, module.exir_op, run_on_fvp=False
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)
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pipeline.run()
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@common.parametrize("test_data", test_data)
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@common.SkipIfNoCorstone300
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def test_unary_u55_BI_on_fvp(test_data: input_t1):
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module = test_data[0]
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pipeline = EthosU55PipelineBI[input_t1](
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module, (test_data[1],), module.aten_op, module.exir_op, run_on_fvp=True
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)
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pipeline.run()
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@common.parametrize("test_data", test_data)
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@common.SkipIfNoCorstone320
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def test_unary_u85_BI_on_fvp(test_data: input_t1):
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module = test_data[0]
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pipeline = EthosU85PipelineBI[input_t1](
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module, (test_data[1],), module.aten_op, module.exir_op, run_on_fvp=True
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)
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pipeline.run()

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