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Arm backend: Add TOSA support for gt.Scalar and lt.Scalar #9908

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Apr 11, 2025
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2 changes: 2 additions & 0 deletions backends/arm/_passes/match_arg_ranks_pass.py
Original file line number Diff line number Diff line change
Expand Up @@ -48,6 +48,8 @@ def __init__(self, exported_program):
exir_ops.edge.aten.bitwise_right_shift.Tensor,
exir_ops.edge.aten.bitwise_left_shift.Tensor,
exir_ops.edge.aten.eq.Tensor,
exir_ops.edge.aten.gt.Tensor,
exir_ops.edge.aten.lt.Tensor,
exir_ops.edge.aten.pow.Tensor_Tensor,
exir_ops.edge.aten.where.self,
]
Expand Down
4 changes: 4 additions & 0 deletions backends/arm/_passes/replace_scalar_with_tensor_pass.py
Original file line number Diff line number Diff line change
Expand Up @@ -26,13 +26,17 @@
exir_ops.edge.aten.__rshift__.Scalar: exir_ops.edge.aten.bitwise_right_shift.Tensor,
exir_ops.edge.aten.__lshift__.Scalar: exir_ops.edge.aten.bitwise_left_shift.Tensor,
exir_ops.edge.aten.eq.Scalar: exir_ops.edge.aten.eq.Tensor,
exir_ops.edge.aten.gt.Scalar: exir_ops.edge.aten.gt.Tensor,
exir_ops.edge.aten.lt.Scalar: exir_ops.edge.aten.lt.Tensor,
torch.ops.aten.add.Scalar: torch.ops.aten.add.Tensor,
torch.ops.aten.sub.Scalar: torch.ops.aten.sub.Tensor,
torch.ops.aten.mul.Scalar: torch.ops.aten.mul.Tensor,
torch.ops.aten.div.Scalar: torch.ops.aten.div.Tensor,
torch.ops.aten.__rshift__.Scalar: torch.ops.aten.bitwise_right_shift.Tensor,
torch.ops.aten.__lshift__.Scalar: torch.ops.aten.bitwise_left_shift.Tensor,
torch.ops.aten.eq.Scalar: torch.ops.aten.eq.Tensor,
torch.ops.aten.gt.Scalar: torch.ops.aten.gt.Tensor,
torch.ops.aten.lt.Scalar: torch.ops.aten.lt.Tensor,
}


Expand Down
2 changes: 2 additions & 0 deletions backends/arm/operator_support/ethos_u55_support.py
Original file line number Diff line number Diff line change
Expand Up @@ -135,8 +135,10 @@ class EthosU55NotSupported(OperatorSupportBase):
exir_ops.edge.aten.eq.Scalar,
exir_ops.edge.aten.ge.Tensor,
exir_ops.edge.aten.gt.Tensor,
exir_ops.edge.aten.gt.Scalar,
exir_ops.edge.aten.le.Tensor,
exir_ops.edge.aten.lt.Tensor,
exir_ops.edge.aten.lt.Scalar,
exir_ops.edge.aten.flip.default, # REVERSE
exir_ops.edge.aten.grid_sampler_2d, # GATHER
exir_ops.edge.aten.scatter.src,
Expand Down
2 changes: 2 additions & 0 deletions backends/arm/operator_support/tosa_supported_operators.py
Original file line number Diff line number Diff line change
Expand Up @@ -176,8 +176,10 @@ def is_node_supported(
exir_ops.edge.aten.full_like.default,
exir_ops.edge.aten.ge.Tensor,
exir_ops.edge.aten.gt.Tensor,
exir_ops.edge.aten.gt.Scalar,
exir_ops.edge.aten.le.Tensor,
exir_ops.edge.aten.lt.Tensor,
exir_ops.edge.aten.lt.Scalar,
exir_ops.edge.aten.mul.Tensor,
exir_ops.edge.aten.add.Scalar,
exir_ops.edge.aten.sub.Scalar,
Expand Down
35 changes: 31 additions & 4 deletions backends/arm/test/ops/test_eq.py
Original file line number Diff line number Diff line change
Expand Up @@ -96,8 +96,16 @@ def test_eq_scalar_tosa_MI(test_module):
pipeline.run()


@common.parametrize("test_module", test_data_tensor | test_data_scalar)
def test_eq_tosa_BI(test_module):
@common.parametrize("test_module", test_data_tensor)
def test_eq_tensor_tosa_BI(test_module):
pipeline = TosaPipelineBI[input_t](
test_module, test_module.get_inputs(), Equal.aten_op_Tensor, Equal.exir_op
)
pipeline.run()


@common.parametrize("test_module", test_data_scalar)
def test_eq_scalar_tosa_BI(test_module):
pipeline = TosaPipelineBI[input_t](
test_module, test_module.get_inputs(), Equal.aten_op_Tensor, Equal.exir_op
)
Expand Down Expand Up @@ -133,15 +141,34 @@ def test_eq_scalar_u55_BI(test_module):

@common.parametrize(
"test_module",
test_data_tensor | test_data_scalar,
test_data_tensor,
xfails={
"eq_tensor_rank4_randn": "MLETORCH-847: Boolean eq result unstable on U85",
},
strict=False,
)
@common.XfailIfNoCorstone320
def test_eq_tensor_u85_BI(test_module):
pipeline = EthosU85PipelineBI[input_t](
test_module,
test_module.get_inputs(),
Equal.aten_op_Tensor,
Equal.exir_op,
run_on_fvp=True,
)
pipeline.run()


@common.parametrize(
"test_module",
test_data_scalar,
xfails={
"eq_scalar_rank4_randn": "MLETORCH-847: Boolean eq result unstable on U85",
},
strict=False,
)
@common.XfailIfNoCorstone320
def test_eq_u85_BI(test_module):
def test_eq_scalar_u85_BI(test_module):
pipeline = EthosU85PipelineBI[input_t](
test_module,
test_module.get_inputs(),
Expand Down
126 changes: 82 additions & 44 deletions backends/arm/test/ops/test_gt.py
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,6 @@

from typing import Tuple

import pytest
import torch
from executorch.backends.arm.test import common

Expand All @@ -16,13 +15,15 @@
TosaPipelineMI,
)

aten_op = "torch.ops.aten.gt.Tensor"
exir_op = "executorch_exir_dialects_edge__ops_aten_gt_Tensor"

input_t = Tuple[torch.Tensor]


class Greater(torch.nn.Module):
aten_op_tensor = "torch.ops.aten.gt.Tensor"
aten_op_scalar = "torch.ops.aten.gt.Scalar"
exir_op = "executorch_exir_dialects_edge__ops_aten_gt_Tensor"

def __init__(self, input, other):
super().__init__()
self.input_ = input
Expand All @@ -31,106 +32,143 @@ def __init__(self, input, other):
def forward(
self,
input_: torch.Tensor,
other_: torch.Tensor,
other_: torch.Tensor | int | float,
):
return input_ > other_

def get_inputs(self):
return (self.input_, self.other_)


op_gt_rank1_ones = Greater(
op_gt_tensor_rank1_ones = Greater(
torch.ones(5),
torch.ones(5),
)
op_gt_rank2_rand = Greater(
op_gt_tensor_rank2_rand = Greater(
torch.rand(4, 5),
torch.rand(1, 5),
)
op_gt_rank3_randn = Greater(
op_gt_tensor_rank3_randn = Greater(
torch.randn(10, 5, 2),
torch.randn(10, 5, 2),
)
op_gt_rank4_randn = Greater(
op_gt_tensor_rank4_randn = Greater(
torch.randn(3, 2, 2, 2),
torch.randn(3, 2, 2, 2),
)

test_data_common = {
"gt_rank1_ones": op_gt_rank1_ones,
"gt_rank2_rand": op_gt_rank2_rand,
"gt_rank3_randn": op_gt_rank3_randn,
"gt_rank4_randn": op_gt_rank4_randn,
op_gt_scalar_rank1_ones = Greater(torch.ones(5), 1.0)
op_gt_scalar_rank2_rand = Greater(torch.rand(4, 5), 0.2)
op_gt_scalar_rank3_randn = Greater(torch.randn(10, 5, 2), -0.1)
op_gt_scalar_rank4_randn = Greater(torch.randn(3, 2, 2, 2), 0.3)

test_data_tensor = {
"gt_tensor_rank1_ones": op_gt_tensor_rank1_ones,
"gt_tensor_rank2_rand": op_gt_tensor_rank2_rand,
"gt_tensor_rank3_randn": op_gt_tensor_rank3_randn,
"gt_tensor_rank4_randn": op_gt_tensor_rank4_randn,
}

test_data_scalar = {
"gt_scalar_rank1_ones": op_gt_scalar_rank1_ones,
"gt_scalar_rank2_rand": op_gt_scalar_rank2_rand,
"gt_scalar_rank3_randn": op_gt_scalar_rank3_randn,
"gt_scalar_rank4_randn": op_gt_scalar_rank4_randn,
}


@common.parametrize("test_module", test_data_common)
def test_gt_tosa_MI(test_module):
@common.parametrize("test_module", test_data_tensor)
def test_gt_tensor_tosa_MI(test_module):
pipeline = TosaPipelineMI[input_t](
test_module, test_module.get_inputs(), Greater.aten_op_tensor, Greater.exir_op
)
pipeline.run()


@common.parametrize("test_module", test_data_scalar)
def test_gt_scalar_tosa_MI(test_module):
pipeline = TosaPipelineMI[input_t](
test_module, test_module.get_inputs(), aten_op, exir_op
test_module, test_module.get_inputs(), Greater.aten_op_scalar, Greater.exir_op
)
pipeline.run()


@common.parametrize("test_module", test_data_tensor)
def test_gt_tensor_tosa_BI(test_module):
pipeline = TosaPipelineBI[input_t](
test_module, test_module.get_inputs(), Greater.aten_op_tensor, Greater.exir_op
)
pipeline.run()


@common.parametrize("test_module", test_data_common)
def test_gt_tosa_BI(test_module):
@common.parametrize("test_module", test_data_scalar)
def test_gt_scalar_tosa_BI(test_module):
pipeline = TosaPipelineBI[input_t](
test_module, test_module.get_inputs(), aten_op, exir_op
test_module, test_module.get_inputs(), Greater.aten_op_tensor, Greater.exir_op
)
pipeline.run()


@common.parametrize("test_module", test_data_common)
def test_gt_u55_BI(test_module):
# GREATER is not supported on U55.
@common.parametrize("test_module", test_data_tensor)
@common.XfailIfNoCorstone300
def test_gt_tensor_u55_BI(test_module):
# Greater is not supported on U55.
pipeline = OpNotSupportedPipeline[input_t](
test_module,
test_module.get_inputs(),
"TOSA-0.80+BI+u55",
{exir_op: 1},
{Greater.exir_op: 1},
)
pipeline.run()


@common.parametrize("test_module", test_data_common)
def test_gt_u85_BI(test_module):
pipeline = EthosU85PipelineBI[input_t](
@common.parametrize("test_module", test_data_scalar)
@common.XfailIfNoCorstone300
def test_gt_scalar_u55_BI(test_module):
# Greater is not supported on U55.
pipeline = OpNotSupportedPipeline[input_t](
test_module,
test_module.get_inputs(),
aten_op,
exir_op,
run_on_fvp=False,
use_to_edge_transform_and_lower=True,
"TOSA-0.80+BI+u55",
{Greater.exir_op: 1},
n_expected_delegates=1,
)
pipeline.run()


@common.parametrize("test_module", test_data_common)
@pytest.mark.skip(reason="The same as test_gt_u55_BI")
def test_gt_u55_BI_on_fvp(test_module):
# GREATER is not supported on U55.
pipeline = OpNotSupportedPipeline[input_t](
@common.parametrize(
"test_module",
test_data_tensor,
xfails={
"gt_tensor_rank4_randn": "MLETORCH-847: Boolean eq result unstable on U85",
},
)
@common.XfailIfNoCorstone320
def test_gt_tensor_u85_BI(test_module):
pipeline = EthosU85PipelineBI[input_t](
test_module,
test_module.get_inputs(),
"TOSA-0.80+BI+u55",
{exir_op: 1},
Greater.aten_op_tensor,
Greater.exir_op,
run_on_fvp=True,
)
pipeline.run()


@common.parametrize(
"test_module",
test_data_common,
xfails={"gt_rank4_randn": "4D fails because boolean Tensors can't be subtracted"},
test_data_scalar,
xfails={
"gt_scalar_rank4_randn": "MLETORCH-847: Boolean eq result unstable on U85",
},
)
@common.SkipIfNoCorstone320
def test_gt_u85_BI_on_fvp(test_module):
@common.XfailIfNoCorstone320
def test_gt_scalar_u85_BI(test_module):
pipeline = EthosU85PipelineBI[input_t](
test_module,
test_module.get_inputs(),
aten_op,
exir_op,
Greater.aten_op_tensor,
Greater.exir_op,
run_on_fvp=True,
use_to_edge_transform_and_lower=True,
)
pipeline.run()
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