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Arm backend: Fix tensor_div_mode decomp for scalar input #14114

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Merged
merged 1 commit into from
Sep 9, 2025
+35 −33
Merged

Arm backend: Fix tensor_div_mode decomp for scalar input #14114

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4 changes: 2 additions & 2 deletions backends/arm/_passes/arm_pass_manager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -197,6 +197,7 @@ def _tosa_FP_pipeline(self, exported_program: ExportedProgram) -> GraphModule:
self.add_pass(CastBoolToInt8Pass())
self.add_pass(DecomposeSinhPass())
self.add_pass(DecomposeSignPass())
self.add_pass(DecomposeDivTensorModePass())
self.add_pass(ReplaceScalarWithTensorArgPassTOSAMI())
self.add_pass(DecomposeEmbeddingPass())
self.add_pass(FuseQuantizedActivationPass())
Expand All @@ -215,7 +216,6 @@ def _tosa_FP_pipeline(self, exported_program: ExportedProgram) -> GraphModule:
DecomposeMeanDimPass(exported_program.graph_module, self.tosa_spec)
)
self.add_pass(DecomposeNotEqualPass())
self.add_pass(DecomposeDivTensorModePass())
self.add_pass(DecomposeDivPass())
self.add_pass(DecomposeSoftmaxPass())
self.add_pass(DecomposeGeluPass())
Expand Down Expand Up @@ -285,6 +285,7 @@ def transform_for_annotation_pipeline(self, graph_module: GraphModule):
self.add_pass(CastBoolToInt8Pass())
self.add_pass(DecomposeSignPass())
self.add_pass(DecomposeAddmmPass())
self.add_pass(DecomposeDivTensorModePass())
self.add_pass(ReplaceScalarWithTensorArgPassTOSABI())
self.add_pass(ScalarsToAttributePass())
self.add_pass(DecomposeGroupNormPass())
Expand All @@ -294,7 +295,6 @@ def transform_for_annotation_pipeline(self, graph_module: GraphModule):
self.add_pass(DecomposeNotEqualPass())
self.add_pass(DecomposeCosineSimilarityPass())
self.add_pass(DecomposeGluPass())
self.add_pass(DecomposeDivTensorModePass())
self.add_pass(DecomposeDivPass())
self.add_pass(DecomposeLeakyReLUPass())
self.add_pass(DecomposeLinearVectorNormPass())
Expand Down
64 changes: 33 additions & 31 deletions backends/arm/test/ops/test_div_tensor_mode.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,6 @@

from typing import Tuple

import pytest
import torch

from executorch.backends.arm.test import common
Expand All @@ -19,13 +18,6 @@
input_tt = Tuple[torch.Tensor, torch.Tensor]


def make_float_div_inputs(B: int = 4, T: int = 64) -> input_tt:
x = torch.randn(B, T)
# guard against zero in denominator
y = torch.randn(B, T).abs() + 1e-3
return x, y


class DivTensorModeFloat(torch.nn.Module):
"""
torch.div(x, y, rounding_mode=mode) with
Expand All @@ -44,11 +36,24 @@ def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
return torch.div(x, y, rounding_mode=self.mode)


@pytest.mark.parametrize("mode", [None, "floor", "trunc"])
def test_div_tensor_mode_tosa_FP(mode):
test_data = {
"mode_none": lambda: (None, (torch.randn(4, 8), torch.randn(4, 8).abs() + 1e-3)),
"mode_floor": lambda: (
"floor",
(torch.randn(4, 8), torch.randn(4, 8).abs() + 1e-3),
),
"mode_trunc": lambda: (
"trunc",
(torch.randn(4, 8), torch.randn(4, 8).abs() + 1e-3),
),
"int_denominator": lambda: (None, (torch.randn(4, 8), 2)),
}


@common.parametrize("data", test_data)
def test_div_tensor_mode_tosa_FP(data):
mode, inputs = data()
model = DivTensorModeFloat(mode)
inputs = make_float_div_inputs()

pipeline = TosaPipelineFP[input_tt](
model,
Expand All @@ -61,11 +66,10 @@ def test_div_tensor_mode_tosa_FP(mode):
pipeline.run()


@pytest.mark.parametrize("mode", [None, "floor", "trunc"])
def test_div_tensor_mode_tosa_INT(mode):

@common.parametrize("data", test_data)
def test_div_tensor_mode_tosa_INT(data):
mode, inputs = data()
model = DivTensorModeFloat(mode)
inputs = make_float_div_inputs()

pipeline = TosaPipelineINT[input_tt](
model,
Expand All @@ -79,11 +83,12 @@ def test_div_tensor_mode_tosa_INT(mode):


@common.XfailIfNoCorstone300
@pytest.mark.parametrize("mode", [None, "floor"])
def test_div_tensor_mode_u55_INT(mode):

@common.parametrize(
"data", test_data, xfails={"mode_trunc": "CPU op missing in unittests"}
)
def test_div_tensor_mode_u55_INT(data):
mode, inputs = data()
model = DivTensorModeFloat(mode)
inputs = make_float_div_inputs()

pipeline = EthosU55PipelineINT[input_tt](
model,
Expand All @@ -97,11 +102,10 @@ def test_div_tensor_mode_u55_INT(mode):


@common.XfailIfNoCorstone320
@pytest.mark.parametrize("mode", [None, "floor", "trunc"])
def test_div_tensor_mode_u85_INT(mode):

@common.parametrize("data", test_data)
def test_div_tensor_mode_u85_INT(data):
mode, inputs = data()
model = DivTensorModeFloat(mode)
inputs = make_float_div_inputs()

pipeline = EthosU85PipelineINT[input_tt](
model,
Expand All @@ -115,11 +119,10 @@ def test_div_tensor_mode_u85_INT(mode):


@common.SkipIfNoModelConverter
@pytest.mark.parametrize("mode", [None, "floor", "trunc"])
def test_div_tensor_mode_vgf_INT(mode):

@common.parametrize("data", test_data)
def test_div_tensor_mode_vgf_INT(data):
mode, inputs = data()
model = DivTensorModeFloat(mode)
inputs = make_float_div_inputs()

pipeline = VgfPipeline[input_tt](
model,
Expand All @@ -134,11 +137,10 @@ def test_div_tensor_mode_vgf_INT(mode):


@common.SkipIfNoModelConverter
@pytest.mark.parametrize("mode", [None, "floor", "trunc"])
def test_div_tensor_mode_vgf_FP(mode):

@common.parametrize("data", test_data)
def test_div_tensor_mode_vgf_FP(data):
mode, inputs = data()
model = DivTensorModeFloat(mode)
inputs = make_float_div_inputs()

pipeline = VgfPipeline[input_tt](
model,
Expand Down
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