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Arm backend: Fix Arm tester issue for inplace ops #14625

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Merged
merged 1 commit into from
Oct 6, 2025
Merged

Arm backend: Fix Arm tester issue for inplace ops #14625

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5 changes: 0 additions & 5 deletions backends/arm/test/ops/test_silu.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,6 @@

from typing import Optional, Tuple

import pytest
import torch
from executorch.backends.arm.test import common
from executorch.backends.arm.test.tester.test_pipeline import (
Expand Down Expand Up @@ -117,7 +116,6 @@ def test_silu_u85_INT_inplace(test_data: input_t):

@common.parametrize("test_data", Silu.test_data)
@common.SkipIfNoModelConverter
@pytest.mark.xfail(reason="MLETORCH-1387: Output differs")
def test_silu_vgf_FP(test_data: input_t):
silu_data = (test_data(), False)
pipeline = VgfPipeline[input_t](
Expand All @@ -128,7 +126,6 @@ def test_silu_vgf_FP(test_data: input_t):

@common.parametrize("test_data", Silu.test_data)
@common.SkipIfNoModelConverter
@pytest.mark.xfail(reason="MLETORCH-1387: Output differs")
def test_silu_vgf_FP_inplace(test_data: input_t):
silu_data = (test_data(), True)
pipeline = VgfPipeline[input_t](
Expand All @@ -139,7 +136,6 @@ def test_silu_vgf_FP_inplace(test_data: input_t):

@common.parametrize("test_data", Silu.test_data)
@common.SkipIfNoModelConverter
@pytest.mark.xfail(reason="MLETORCH-1387: Output differs")
def test_silu_vgf_INT(test_data: input_t):
silu_data = (test_data(), False)
pipeline = VgfPipeline[input_t](
Expand All @@ -153,7 +149,6 @@ def test_silu_vgf_INT(test_data: input_t):

@common.parametrize("test_data", Silu.test_data)
@common.SkipIfNoModelConverter
@pytest.mark.xfail(reason="MLETORCH-1387: Output differs")
def test_silu_vgf_INT_inplace(test_data: input_t):
silu_data = (test_data(), True)
pipeline = VgfPipeline[input_t](
Expand Down
10 changes: 7 additions & 3 deletions backends/arm/test/tester/arm_tester.py
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Original file line number Diff line number Diff line change
Expand Up @@ -463,6 +463,10 @@ def run_method_and_compare_outputs(
for run_iteration in range(num_runs):
reference_input = inputs if inputs else next(self.generate_random_inputs())

# Avoid issues with inplace operators
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Interesting. I am sure we will run this in other places, but I see just Silu, which is good. :)

test_input = copy.deepcopy(reference_input)
original_input = copy.deepcopy(reference_input)

input_shapes = [
generated_input.shape if hasattr(generated_input, "shape") else (1,)
for generated_input in reference_input
Expand All @@ -477,16 +481,16 @@ def run_method_and_compare_outputs(
# Run exported module directly
test_outputs, _ = pytree.tree_flatten(
self._calculate_reference_output(
exported_program.module(), reference_input
exported_program.module(), test_input
)
)
else:
# Run lowered model with target
test_outputs, _ = pytree.tree_flatten(
test_stage.run_artifact(reference_input)
test_stage.run_artifact(test_input)
)

logger.info(f"\n Input: {reference_input}")
logger.info(f"\n Input: {original_input}")
logger.info(f"\n Ref output: {reference_outputs}")
logger.info(f"\nTest output: {test_outputs}")

Expand Down
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