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Arm backend: Increase tolerance on Tanh int16 test #16094

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Merged
zingo merged 1 commit into from
Dec 6, 2025
Merged

Arm backend: Increase tolerance on Tanh int16 test #16094

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60 changes: 9 additions & 51 deletions backends/arm/test/ops/test_tanh.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,21 +8,15 @@

import pytest
import torch
from executorch.backends.arm.quantizer.arm_quantizer import (
get_symmetric_a16w8_quantization_config,
TOSAQuantizer,
)

from executorch.backends.arm.test import common, conftest
from executorch.backends.arm.test import common
from executorch.backends.arm.test.tester.test_pipeline import (
EthosU55PipelineINT,
EthosU85PipelineINT,
TosaPipelineFP,
TosaPipelineINT,
VgfPipeline,
)
from executorch.backends.arm.tosa.specification import TosaSpecification
from executorch.backends.xnnpack.test.tester import Quantize

aten_op = "torch.ops.aten.tanh.default"
input_t1 = Tuple[torch.Tensor] # Input x
Expand Down Expand Up @@ -114,29 +108,6 @@ def test_tanh_vgf_INT(test_data: Tuple):
pipeline.run()


def get_symmetric_a16w8_tanh_quantizer(per_channel_quantization=False):
tosa_version = conftest.get_option("tosa_version")
tosa_profiles = {
"1.0": TosaSpecification.create_from_string("TOSA-1.0+INT+int16"),
}

quantizer = TOSAQuantizer(tosa_profiles[tosa_version])

# Use a smaller episilon value to not greatly inflate [qmin, qmax]
quantizer.set_global(
get_symmetric_a16w8_quantization_config(
is_per_channel=per_channel_quantization, epsilon=2**-16
)
)

return Quantize(
quantizer,
get_symmetric_a16w8_quantization_config(
is_per_channel=per_channel_quantization, epsilon=2**-16
),
)


@common.parametrize("test_data", test_data_suite)
def test_tanh_16a8w_tosa_INT(test_data: torch.Tensor):
"""Test tanh operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
Expand All @@ -150,13 +121,8 @@ def test_tanh_16a8w_tosa_INT(test_data: torch.Tensor):
per_channel_quantization=per_channel_quantization,
use_to_edge_transform_and_lower=True,
tosa_extensions=["int16"],
)

pipeline.change_args(
"quantize",
get_symmetric_a16w8_tanh_quantizer(
per_channel_quantization=per_channel_quantization
),
epsilon=2**-16,
rtol=2e-03,
)
pipeline.run()

Expand All @@ -177,13 +143,9 @@ def test_tanh_16a8w_u55_INT16(test_data: torch.Tensor):
exir_ops=[],
per_channel_quantization=per_channel_quantization,
use_to_edge_transform_and_lower=True,
)

pipeline.change_args(
"quantize",
get_symmetric_a16w8_tanh_quantizer(
per_channel_quantization=per_channel_quantization
),
a16w8_quantization=True,
epsilon=2**-16,
rtol=2e-03,
)
pipeline.run()

Expand All @@ -201,12 +163,8 @@ def test_tanh_16a8w_u85_INT16(test_data: torch.Tensor):
exir_ops=[],
per_channel_quantization=per_channel_quantization,
use_to_edge_transform_and_lower=True,
)

pipeline.change_args(
"quantize",
get_symmetric_a16w8_tanh_quantizer(
per_channel_quantization=per_channel_quantization
),
a16w8_quantization=True,
epsilon=2**-16,
rtol=2e-03,
)
pipeline.run()
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