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Merged
Sebastian-Larsson merged 2 commits into from
Aug 4, 2025
Merged

Arm backend: Add VGF unit tests to operators (Part 2) #13033

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5dd17bf
Arm backend: Add VGF unit tests to operators (Part 2)
YufengShi-dudu Jul 9, 2025
3f819b7
Merge branch 'main' into add-vgf-ops-tests-part2
YufengShi-dudu Aug 1, 2025
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53 changes: 53 additions & 0 deletions backends/arm/test/ops/test_ge.py
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Expand Up @@ -13,6 +13,7 @@
OpNotSupportedPipeline,
TosaPipelineFP,
TosaPipelineINT,
VgfPipeline,
)

input_t = Tuple[torch.Tensor]
Expand Down Expand Up @@ -181,3 +182,55 @@ def test_ge_scalar_u85_INT(test_module):
run_on_fvp=True,
)
pipeline.run()


@common.parametrize("test_module", test_data_tensor)
@common.SkipIfNoModelConverter
def test_ge_tensor_vgf_FP(test_module):
pipeline = VgfPipeline[input_t](
test_module(),
test_module().get_inputs(),
GreaterEqual.aten_op_tensor,
GreaterEqual.exir_op,
tosa_version="TOSA-1.0+FP",
)
pipeline.run()


@common.parametrize("test_module", test_data_tensor)
@common.SkipIfNoModelConverter
def test_ge_tensor_vgf_INT(test_module):
pipeline = VgfPipeline[input_t](
test_module(),
test_module().get_inputs(),
GreaterEqual.aten_op_tensor,
GreaterEqual.exir_op,
tosa_version="TOSA-1.0+INT",
)
pipeline.run()


@common.parametrize("test_module", test_data_scalar)
@common.SkipIfNoModelConverter
def test_ge_scalar_vgf_FP(test_module):
pipeline = VgfPipeline[input_t](
test_module(),
test_module().get_inputs(),
GreaterEqual.aten_op_scalar,
GreaterEqual.exir_op,
tosa_version="TOSA-1.0+FP",
)
pipeline.run()


@common.parametrize("test_module", test_data_scalar)
@common.SkipIfNoModelConverter
def test_ge_scalar_vgf_INT(test_module):
pipeline = VgfPipeline[input_t](
test_module(),
test_module().get_inputs(),
GreaterEqual.aten_op_tensor,
GreaterEqual.exir_op,
tosa_version="TOSA-1.0+INT",
)
pipeline.run()
29 changes: 29 additions & 0 deletions backends/arm/test/ops/test_gelu.py
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Expand Up @@ -12,6 +12,7 @@
EthosU85PipelineINT,
TosaPipelineFP,
TosaPipelineINT,
VgfPipeline,
)

input_t1 = Tuple[torch.Tensor]
Expand Down Expand Up @@ -125,3 +126,31 @@ def test_gelu_u85_INT(test_data: input_t1):
Gelu.aten_op,
Gelu.exir_op,
).run()


@common.parametrize("test_data", Gelu.test_data)
@common.SkipIfNoModelConverter
def test_gelu_vgf_FP(test_data: input_t1):
approximate, data = test_data()
pipeline = VgfPipeline[input_t1](
Gelu(approximate),
(data,),
Gelu.aten_op,
Gelu.exir_op,
tosa_version="TOSA-1.0+FP",
)
pipeline.run()


@common.parametrize("test_data", Gelu.test_data)
@common.SkipIfNoModelConverter
def test_gelu_vgf_INT(test_data: input_t1):
approximate, data = test_data()
pipeline = VgfPipeline[input_t1](
Gelu(approximate),
(data,),
Gelu.aten_op,
Gelu.exir_op,
tosa_version="TOSA-1.0+INT",
)
pipeline.run()
54 changes: 54 additions & 0 deletions backends/arm/test/ops/test_group_norm.py
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Expand Up @@ -10,6 +10,7 @@
EthosU85PipelineINT,
TosaPipelineFP,
TosaPipelineINT,
VgfPipeline,
)


Expand Down Expand Up @@ -143,3 +144,56 @@ def test_native_group_norm_u85_INT(test_data):
)
pipeline.change_args("run_method_and_compare_outputs", atol=1, qtol=1)
pipeline.run()


@common.parametrize(
"test_data",
test_data_suite,
xfails={
"randn_1_12_8_6_groups_12": "MLETORCH-925: Fix numerical issue",
"rand_6_8_10_12_groups_1": "MLETORCH-925: Fix numerical issue",
"rand_6_8_10_12_groups_4_no_affine": "MLETORCH-925: Fix numerical issue",
"rand_6_8_10_12_groups_8": "MLETORCH-925: Fix numerical issue",
},
strict=False,
)
@common.SkipIfNoModelConverter
def test_native_group_norm_vgf_FP(test_data):
aten_op = "torch.ops.aten.group_norm.default"
exir_op = "executorch_exir_dialects_edge__ops_aten_native_group_norm_default"
model, inp = test_data
pipeline = VgfPipeline[input_t](
inp,
model,
aten_op=aten_op,
exir_op=exir_op,
tosa_version="TOSA-1.0+FP",
)
pipeline.run()


@common.parametrize(
"test_data",
test_data_suite,
xfails={
"randn_1_12_8_6_groups_12": "MLETORCH-925: Fix numerical issue",
"rand_6_8_10_12_groups_1": "MLETORCH-925: Fix numerical issue",
"rand_6_8_10_12_groups_4_no_affine": "MLETORCH-925: Fix numerical issue",
"rand_6_8_10_12_groups_8": "MLETORCH-925: Fix numerical issue",
},
strict=False,
)
@common.SkipIfNoModelConverter
def test_native_group_norm_vgf_INT(test_data):
aten_op = "torch.ops.aten.sub.Tensor"
exir_op = "executorch_exir_dialects_edge__ops_aten_native_group_norm_default"
model, inp = test_data
pipeline = VgfPipeline[input_t](
inp,
model,
aten_op=aten_op,
exir_op=exir_op,
tosa_version="TOSA-1.0+INT",
atol=0.1, # TODO: "MLETORCH-925: Fix numerical issue for aten.native_group_norm"
)
pipeline.run()
53 changes: 53 additions & 0 deletions backends/arm/test/ops/test_gt.py
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Expand Up @@ -13,6 +13,7 @@
OpNotSupportedPipeline,
TosaPipelineFP,
TosaPipelineINT,
VgfPipeline,
)


Expand Down Expand Up @@ -186,3 +187,55 @@ def test_gt_scalar_u85_INT(test_module):
run_on_fvp=True,
)
pipeline.run()


@common.parametrize("test_module", test_data_tensor)
@common.SkipIfNoModelConverter
def test_gt_tensor_vgf_FP(test_module):
pipeline = VgfPipeline[input_t](
test_module(),
test_module().get_inputs(),
Greater.aten_op_tensor,
Greater.exir_op,
tosa_version="TOSA-1.0+FP",
)
pipeline.run()


@common.parametrize("test_module", test_data_scalar)
@common.SkipIfNoModelConverter
def test_gt_scalar_vgf_FP(test_module):
pipeline = VgfPipeline[input_t](
test_module(),
test_module().get_inputs(),
Greater.aten_op_scalar,
Greater.exir_op,
tosa_version="TOSA-1.0+FP",
)
pipeline.run()


@common.parametrize("test_module", test_data_tensor)
@common.SkipIfNoModelConverter
def test_gt_tensor_vgf_INT(test_module):
pipeline = VgfPipeline[input_t](
test_module(),
test_module().get_inputs(),
Greater.aten_op_tensor,
Greater.exir_op,
tosa_version="TOSA-1.0+INT",
)
pipeline.run()


@common.parametrize("test_module", test_data_scalar)
@common.SkipIfNoModelConverter
def test_gt_scalar_vgf_INT(test_module):
pipeline = VgfPipeline[input_t](
test_module(),
test_module().get_inputs(),
Greater.aten_op_tensor,
Greater.exir_op,
tosa_version="TOSA-1.0+INT",
)
pipeline.run()
23 changes: 23 additions & 0 deletions backends/arm/test/ops/test_hardsigmoid.py
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Expand Up @@ -14,6 +14,7 @@
EthosU85PipelineINT,
TosaPipelineFP,
TosaPipelineINT,
VgfPipeline,
)

aten_op = "torch.ops.aten.hardsigmoid.default"
Expand Down Expand Up @@ -87,3 +88,25 @@ def test_hardsigmoid_u85_INT(test_data: torch.Tensor):
use_to_edge_transform_and_lower=True,
)
pipeline.run()


@common.parametrize("test_data", test_data_suite)
@common.SkipIfNoModelConverter
def test_hardsigmoid_vgf_FP(test_data: torch.Tensor):
pipeline = VgfPipeline[input_t1](
Hardsigmoid(), (test_data(),), aten_op, exir_op=[], tosa_version="TOSA-1.0+FP"
)
pipeline.run()


@common.parametrize("test_data", test_data_suite)
@common.SkipIfNoModelConverter
def test_hardsigmoid_vgf_INT(test_data: torch.Tensor):
pipeline = VgfPipeline[input_t1](
Hardsigmoid(),
(test_data(),),
aten_op,
exir_op=[],
tosa_version="TOSA-1.0+INT",
)
pipeline.run()
23 changes: 23 additions & 0 deletions backends/arm/test/ops/test_hardswish.py
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Expand Up @@ -14,6 +14,7 @@
EthosU85PipelineINT,
TosaPipelineFP,
TosaPipelineINT,
VgfPipeline,
)

aten_op = "torch.ops.aten.hardswish.default"
Expand Down Expand Up @@ -77,3 +78,25 @@ def test_hardswish_u85_INT(test_data):
run_on_fvp=True,
use_to_edge_transform_and_lower=True,
).run()


@common.parametrize("test_data", test_data_suite)
@common.SkipIfNoModelConverter
def test_hardswish_vgf_FP(test_data):
pipeline = VgfPipeline[input_t1](
Hardswish(), (test_data(),), aten_op, exir_op, tosa_version="TOSA-1.0+FP"
)
pipeline.run()


@common.parametrize("test_data", test_data_suite)
@common.SkipIfNoModelConverter
def test_hardswish_vgf_INT(test_data):
pipeline = VgfPipeline[input_t1](
Hardswish(),
(test_data(),),
aten_op,
exir_op,
tosa_version="TOSA-1.0+INT",
)
pipeline.run()
23 changes: 23 additions & 0 deletions backends/arm/test/ops/test_hardtanh.py
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Expand Up @@ -16,6 +16,7 @@
EthosU85PipelineINT,
TosaPipelineFP,
TosaPipelineINT,
VgfPipeline,
)

test_data_suite = {
Expand Down Expand Up @@ -86,3 +87,25 @@ def test_hardtanh_u85_INT(test_data: torch.Tensor):
run_on_fvp=True,
)
pipeline.run()


@common.parametrize("test_data", test_data_suite)
@common.SkipIfNoModelConverter
def test_hardtanh_vgf_FP(test_data: torch.Tensor):
pipeline = VgfPipeline[input_t](
HardTanh(), (test_data(),), aten_op, exir_op, tosa_version="TOSA-1.0+FP"
)
pipeline.run()


@common.parametrize("test_data", test_data_suite)
@common.SkipIfNoModelConverter
def test_hardtanh_vgf_INT(test_data: torch.Tensor):
pipeline = VgfPipeline[input_t](
HardTanh(),
(test_data(),),
aten_op,
exir_op,
tosa_version="TOSA-1.0+INT",
)
pipeline.run()
49 changes: 49 additions & 0 deletions backends/arm/test/ops/test_index_select.py
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Expand Up @@ -9,9 +9,12 @@
import pytest

import torch

from executorch.backends.arm.test import common
from executorch.backends.arm.test.tester.test_pipeline import (
TosaPipelineFP,
TosaPipelineINT,
VgfPipeline,
)


Expand Down Expand Up @@ -115,3 +118,49 @@ def test_index_select_tosa_INT_rand(test_data: input_params):
"run_method_and_compare_outputs", inputs=test_input, atol=0.9, rtol=0.2, qtol=1
)
pipeline.run()


@pytest.mark.parametrize("test_data", list(test_data.values()))
@common.SkipIfNoModelConverter
def test_index_select_vgf_FP(test_data: input_params):
op, inp = test_data
pipeline = VgfPipeline[input_params](
op,
inp,
op.aten_op,
op.exir_op,
tosa_version="TOSA-1.0+FP",
)
pipeline.run()


@pytest.mark.parametrize("test_data", list(test_data.values())[:-1])
@common.SkipIfNoModelConverter
def test_index_select_vgf_INT(test_data: input_params):
op, inp = test_data
pipeline = VgfPipeline[input_params](
op,
inp,
op.aten_op,
op.exir_op,
tosa_version="TOSA-1.0+INT",
)
pipeline.run()


@pytest.mark.parametrize("test_data", list(test_data.values())[-1:])
@common.SkipIfNoModelConverter
def test_index_select_vgf_INT_rand(test_data: input_params):
op, inp = test_data
pipeline = VgfPipeline[input_params](
op,
inp,
op.aten_op,
op.exir_op,
tosa_version="TOSA-1.0+INT",
)
# TODO: MLETORCH-1136 Change args of run_method_and_compare_outputs of the vgf tests
# pipeline.change_args(
# "run_method_and_compare_outputs", inputs=test_input, atol=0.9, rtol=0.2, qtol=1
# )
pipeline.run()
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