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Arm backend: Refactor gt, ge, lt, le and eq tests to pipeline #8828

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Feb 28, 2025
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Arm backend: Refactor gt, ge, lt, le and eq tests to pipeline #8828

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5 changes: 5 additions & 0 deletions backends/arm/operator_support/tosa_supported_operators.py
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Original file line number Diff line number Diff line change
Expand Up @@ -195,6 +195,11 @@ def is_node_supported(
exir_ops.edge.aten.bitwise_xor.Tensor,
exir_ops.edge.aten.amax.default,
exir_ops.edge.aten.amin.default,
exir_ops.edge.aten.eq.Tensor,
exir_ops.edge.aten.ge.Tensor,
exir_ops.edge.aten.gt.Tensor,
exir_ops.edge.aten.le.Tensor,
exir_ops.edge.aten.lt.Tensor,
]

if node.target in unsupported_ops:
Expand Down
255 changes: 123 additions & 132 deletions backends/arm/test/ops/test_eq.py
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Original file line number Diff line number Diff line change
@@ -1,145 +1,136 @@
# Copyright 2025 Arm Limited and/or its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.

import unittest
from typing import Tuple

import pytest
import torch
from executorch.backends.arm.test import common
from executorch.backends.arm.test.tester.arm_tester import ArmTester
from executorch.exir.backend.compile_spec_schema import CompileSpec
from parameterized import parameterized

test_data_suite = [
# (test_name, input, other,) See torch.eq() for info
(
"op_eq_rank1_ones",
torch.ones(5),
torch.ones(5),
),
(
"op_eq_rank2_rand",
torch.rand(4, 5),
torch.rand(1, 5),
),
(
"op_eq_rank3_randn",
torch.randn(10, 5, 2),
torch.randn(10, 5, 2),
),
(
"op_eq_rank4_randn",
torch.randn(3, 2, 2, 2),
torch.randn(3, 2, 2, 2),
),
]


class TestEqual(unittest.TestCase):
class Equal(torch.nn.Module):
def forward(
self,
input_: torch.Tensor,
other_: torch.Tensor,
):
return input_ == other_

def _test_eq_tosa_MI_pipeline(
self,
compile_spec: list[CompileSpec],
module: torch.nn.Module,
test_data: tuple[torch.Tensor, torch.Tensor],
):
(
ArmTester(
module,
example_inputs=test_data,
compile_spec=compile_spec,
)
.export()
.check_count({"torch.ops.aten.eq.Tensor": 1})
.to_edge()
.partition()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.to_executorch()
.run_method_and_compare_outputs(inputs=test_data)
)

def _test_eq_tosa_BI_pipeline(
self,
compile_spec: list[CompileSpec],
module: torch.nn.Module,
test_data: tuple[torch.Tensor, torch.Tensor],
):
(
ArmTester(
module,
example_inputs=test_data,
compile_spec=compile_spec,
)
.quantize()
.export()
.check_count({"torch.ops.aten.eq.Tensor": 1})
.check(["torch.ops.quantized_decomposed"])
.to_edge()
.partition()
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.to_executorch()
.run_method_and_compare_outputs(inputs=test_data)
)

@parameterized.expand(test_data_suite)
def test_eq_tosa_MI(
self,
test_name: str,
input_: torch.Tensor,
other_: torch.Tensor,
):
test_data = (input_, other_)
self._test_eq_tosa_MI_pipeline(
common.get_tosa_compile_spec("TOSA-0.80+MI"), self.Equal(), test_data
)

@parameterized.expand(test_data_suite)
def test_eq_tosa_BI(
self,
test_name: str,
input_: torch.Tensor,
other_: torch.Tensor,
):
test_data = (input_, other_)
self._test_eq_tosa_BI_pipeline(
common.get_tosa_compile_spec("TOSA-0.80+BI"), self.Equal(), test_data
)

@parameterized.expand(test_data_suite)
@unittest.skip
def test_eq_u55_BI(
self,
test_name: str,
input_: torch.Tensor,
other_: torch.Tensor,
):
test_data = (input_, other_)
self._test_eq_tosa_BI_pipeline(
common.get_u55_compile_spec(permute_memory_to_nhwc=True),
self.Equal(),
test_data,
)

@parameterized.expand(test_data_suite)
@unittest.skip
def test_eq_u85_BI(
from executorch.backends.arm.test.tester.test_pipeline import (
EthosU85PipelineBI,
OpNotSupportedPipeline,
TosaPipelineBI,
TosaPipelineMI,
)

aten_op = "torch.ops.aten.eq.Tensor"
exir_op = "executorch_exir_dialects_edge__ops_aten_eq_Tensor"

input_t = Tuple[torch.Tensor]


class Equal(torch.nn.Module):
def __init__(self, input, other):
super().__init__()
self.input_ = input
self.other_ = other

def forward(
self,
test_name: str,
input_: torch.Tensor,
other_: torch.Tensor,
):
test_data = (input_, other_)
self._test_eq_tosa_BI_pipeline(
common.get_u85_compile_spec(permute_memory_to_nhwc=True),
self.Equal(),
test_data,
)
return input_ == other_

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


op_eq_rank1_ones = Equal(
torch.ones(5),
torch.ones(5),
)
op_eq_rank2_rand = Equal(
torch.rand(4, 5),
torch.rand(1, 5),
)
op_eq_rank3_randn = Equal(
torch.randn(10, 5, 2),
torch.randn(10, 5, 2),
)
op_eq_rank4_randn = Equal(
torch.randn(3, 2, 2, 2),
torch.randn(3, 2, 2, 2),
)

test_data_common = {
"eq_rank1_ones": op_eq_rank1_ones,
"eq_rank2_rand": op_eq_rank2_rand,
"eq_rank3_randn": op_eq_rank3_randn,
"eq_rank4_randn": op_eq_rank4_randn,
}


@common.parametrize("test_module", test_data_common)
def test_eq_tosa_MI(test_module):
pipeline = TosaPipelineMI[input_t](
test_module, test_module.get_inputs(), aten_op, exir_op
)
pipeline.run()


@common.parametrize("test_module", test_data_common)
def test_eq_tosa_BI(test_module):
pipeline = TosaPipelineBI[input_t](
test_module, test_module.get_inputs(), aten_op, exir_op
)
pipeline.run()


@common.parametrize("test_module", test_data_common)
def test_eq_u55_BI(test_module):
# EQUAL is not supported on U55.
pipeline = OpNotSupportedPipeline[input_t](
test_module,
test_module.get_inputs(),
"TOSA-0.80+BI+u55",
{exir_op: 1},
)
pipeline.run()


@common.parametrize("test_module", test_data_common)
def test_eq_u85_BI(test_module):
pipeline = EthosU85PipelineBI[input_t](
test_module,
test_module.get_inputs(),
aten_op,
exir_op,
run_on_fvp=False,
use_to_edge_transform_and_lower=True,
)
pipeline.run()


@common.parametrize("test_module", test_data_common)
@pytest.mark.skip(reason="The same as test_eq_u55_BI")
def test_eq_u55_BI_on_fvp(test_module):
# EQUAL is not supported on U55.
pipeline = OpNotSupportedPipeline[input_t](
test_module,
test_module.get_inputs(),
"TOSA-0.80+BI+u55",
{exir_op: 1},
)
pipeline.run()


@common.parametrize(
"test_module",
test_data_common,
xfails={"eq_rank4_randn": "4D fails because boolean Tensors can't be subtracted"},
)
@common.SkipIfNoCorstone320
def test_eq_u85_BI_on_fvp(test_module):
pipeline = EthosU85PipelineBI[input_t](
test_module,
test_module.get_inputs(),
aten_op,
exir_op,
run_on_fvp=True,
use_to_edge_transform_and_lower=True,
)
pipeline.run()
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