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Refactor Arm backend pass unittests #8368

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Merged
zingo merged 1 commit into from
Feb 11, 2025
Merged

Refactor Arm backend pass unittests #8368

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48 changes: 24 additions & 24 deletions backends/arm/test/passes/test_cast_int64_pass.py
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@@ -1,44 +1,44 @@
# 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 torch
from executorch.backends.arm._passes.cast_int64_pass import CastInt64ToInt32Pass

from executorch.backends.arm.test import common
from executorch.backends.arm.test.tester.test_pipeline import TestPassPipeline

from executorch.backends.arm.test.tester.arm_tester import ArmTester, RunPasses
input_t = Tuple[torch.Tensor] # Input x


class Int64Model(torch.nn.Module):

def forward(self, x: torch.Tensor):
return x + 3

def get_inputs(self):
def get_inputs(self) -> input_t:
return (torch.rand(4),)


class TestCastInt64Pass(unittest.TestCase):

def test_int64_model(self):
module = Int64Model()
test_pass_stage = RunPasses(passes_with_exported_program=[CastInt64ToInt32Pass])
tester = (
ArmTester(
module,
example_inputs=module.get_inputs(),
compile_spec=common.get_tosa_compile_spec("TOSA-0.80+BI"),
)
.export()
.to_edge()
.run_passes(test_pass_stage)
.run_method_and_compare_outputs()
)
exported_program = tester.get_artifact("RunPasses").exported_program()
for state in exported_program.state_dict:
assert exported_program.state_dict[state].dtype != torch.int64
def test_int64_model_tosa_BI():
module = Int64Model()
op_checks = {
"executorch_exir_dialects_edge__ops_dim_order_ops__to_dim_order_copy_default": 1,
"executorch_exir_dialects_edge__ops_aten_add_Tensor": 1,
}
pipeline = TestPassPipeline[input_t](
module,
module.get_inputs(),
tosa_version="TOSA-0.80+BI",
ops_before_pass=op_checks,
ops_after_pass=op_checks,
passes_with_exported_program=[CastInt64ToInt32Pass],
)
pipeline.pop_stage("quantize")
pipeline.run()

exported_program = pipeline.tester.get_artifact("RunPasses").exported_program()
for state in exported_program.state_dict:
assert exported_program.state_dict[state].dtype == torch.int32
63 changes: 25 additions & 38 deletions backends/arm/test/passes/test_fold_qdq_pass.py
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@@ -1,63 +1,50 @@
# Copyright 2024-2025 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 torch
from executorch.backends.arm._passes.fold_qdq_with_annotated_qparams_pass import (
FoldAndAnnotateQParamsPass,
)
from executorch.backends.arm.test.tester.test_pipeline import TestPassPipeline

from executorch.backends.arm.test import common
from executorch.backends.arm.test.tester.arm_tester import ArmTester

from executorch.backends.xnnpack.test.tester.tester import RunPasses
input_t = Tuple[torch.Tensor, torch.Tensor] # Input x, y


class SimpleQuantizeModel(torch.nn.Module):
def forward(self, x, y):
return x + torch.max((x + x), (y + y))

def get_inputs(self):
def get_inputs(self) -> input_t:
return (torch.rand(1, 1280, 7, 7), torch.rand(1, 1280, 7, 7))


class TestFoldAndAnnotateQParamsPass(unittest.TestCase):
def test_fold_qdq_pass_tosa_BI():
"""
Tests the FoldAndAnnotateQParamsPass which folds dq/q nodes into
the node and stores the quantization parameters in meta.
"""

def test_fold_qdq_pass(self):
"""
Check that the pass runs for add operation and that one q node and one dq node
is removed from the representation.
"""
module = SimpleQuantizeModel()
test_pass_stage = RunPasses([FoldAndAnnotateQParamsPass])
(
ArmTester(
module,
example_inputs=module.get_inputs(),
compile_spec=common.get_tosa_compile_spec("TOSA-0.80+BI"),
)
.quantize()
.export()
.to_edge()
.check_count(
{
"executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 7,
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 6,
}
)
.run_passes(test_pass_stage)
.check_count(
{
"executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 1,
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 2,
}
)
)
Check that the pass runs for add operation and that one q node and one dq node
is removed from the representation.
"""
module = SimpleQuantizeModel()
pipeline = TestPassPipeline[input_t](
module,
module.get_inputs(),
tosa_version="TOSA-0.80+BI",
ops_before_pass={
"executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 7,
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 6,
},
ops_after_pass={
"executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 1,
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 2,
},
pass_list=[FoldAndAnnotateQParamsPass],
)
pipeline.pop_stage(-1) # Do not compare output
pipeline.run()
65 changes: 28 additions & 37 deletions backends/arm/test/passes/test_fuse_batchnorm_pass.py
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# 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 torch
from executorch.backends.arm._passes.fuse_batchnorm2d_pass import FuseBatchnorm2DPass
from executorch.backends.arm.test import common
from executorch.backends.arm.test.tester.arm_tester import ArmTester, RunPasses
from parameterized import parameterized
from executorch.backends.arm.test.tester.test_pipeline import TestPassPipeline

input_t = Tuple[torch.Tensor] # Input x


class MergeOneOfTwoBN(torch.nn.Module):
Expand All @@ -35,7 +36,7 @@ def __init__(self, affine: bool):
self.batch_norm2d.bias = torch.nn.Parameter(torch.rand(3))
self.relu6 = torch.nn.ReLU6()

def get_inputs(self) -> tuple[torch.Tensor]:
def get_inputs(self) -> input_t:
return (torch.randn(1, 3, 256, 256),)

def forward(self, x):
Expand Down Expand Up @@ -72,7 +73,7 @@ def __init__(self, affine: bool):
self.batch_norm2d.bias = torch.nn.Parameter(torch.rand(3))
self.relu6 = torch.nn.ReLU6()

def get_inputs(self) -> tuple[torch.Tensor]:
def get_inputs(self) -> input_t:
return (torch.randn(1, 3, 256, 256),)

def forward(self, x):
Expand Down Expand Up @@ -110,7 +111,7 @@ def __init__(self, affine: bool):
self.batch_norm2d.bias = torch.nn.Parameter(torch.rand(3))
self.relu6 = torch.nn.ReLU6()

def get_inputs(self) -> tuple[torch.Tensor]:
def get_inputs(self) -> input_t:
return (torch.randn(1, 3, 256, 256),)

def forward(self, x):
Expand All @@ -126,33 +127,23 @@ def forward(self, x):
return z, a


modules = [
MergeOneOfTwoBN(True),
MergeOneOfTwoBN(False),
MergeTwosOfTwoBN(True),
MergeNoBN(True),
]


class TestFuseBatchnormPass(unittest.TestCase):

@parameterized.expand(modules)
def test_fuse_batchnorm_tosa_MI(self, module):
"""Test various cases where the batchnorm should and shouldn't be fused."""
inputs = module.get_inputs()
test_pass_stage = RunPasses(passes_with_exported_program=[FuseBatchnorm2DPass])
(
(
ArmTester(
module,
example_inputs=inputs,
compile_spec=common.get_tosa_compile_spec("TOSA-0.80+MI"),
)
.export()
.to_edge()
.check_count(module.ops_before_pass)
.run_passes(test_pass_stage)
.check_count(module.ops_after_pass)
.run_method_and_compare_outputs()
)
)
modules = {
"merge_one_of_two_bn_affine": MergeOneOfTwoBN(True),
"merge_one_of_two_bn": MergeOneOfTwoBN(False),
"merge_two_of_two_bn_affine": MergeTwosOfTwoBN(True),
"merge_no_bn_affine": MergeNoBN(True),
}


@common.parametrize("module", modules)
def test_fuse_batchnorm_tosa_MI(module):
"""Test various cases where the batchnorm should and shouldn't be fused."""
pipeline = TestPassPipeline[input_t](
module,
module.get_inputs(),
tosa_version="TOSA-0.80+MI",
ops_before_pass=module.ops_before_pass,
ops_after_pass=module.ops_after_pass,
passes_with_exported_program=[FuseBatchnorm2DPass],
)
pipeline.run()
57 changes: 24 additions & 33 deletions backends/arm/test/passes/test_insert_table_ops_pass.py
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@@ -1,55 +1,46 @@
# 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 torch
from executorch.backends.arm._passes.fold_qdq_with_annotated_qparams_pass import (
FoldAndAnnotateQParamsPass,
)
from executorch.backends.arm._passes.insert_table_ops import InsertTableOpsPass
from executorch.backends.arm.test.tester.test_pipeline import TestPassPipeline

from executorch.backends.arm.test import common

from executorch.backends.arm.test.tester.arm_tester import ArmTester, RunPasses
input_t = Tuple[torch.Tensor] # Input x


class Sigmoid(torch.nn.Module):

def forward(self, x: torch.Tensor):
return x.sigmoid()

def get_inputs(self):
def get_inputs(self) -> input_t:
return (torch.rand(4),)


class TestInsertTablePass(unittest.TestCase):

def test_insert_table_tosa_BI(self):
module = Sigmoid()
test_pass_stage = RunPasses(
[FoldAndAnnotateQParamsPass],
passes_with_exported_program=[InsertTableOpsPass],
)
(
ArmTester(
module,
example_inputs=module.get_inputs(),
compile_spec=common.get_tosa_compile_spec("TOSA-0.80+BI"),
)
.quantize()
.export()
.to_edge()
.run_passes(test_pass_stage)
.check("tosa._table")
.check_count(
{
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 1,
"executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 1,
}
)
.check_not(["aten_sigmoid_default"])
)
def test_insert_table_tosa_BI():
module = Sigmoid()
pipeline = TestPassPipeline[input_t](
module,
module.get_inputs(),
tosa_version="TOSA-0.80+BI",
ops_before_pass={},
ops_after_pass={
"executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default": 1,
"executorch_exir_dialects_edge__ops_quantized_decomposed_dequantize_per_tensor_default": 1,
"tosa._table": 1,
},
ops_not_after_pass=["aten_sigmoid_default"],
pass_list=[FoldAndAnnotateQParamsPass],
passes_with_exported_program=[InsertTableOpsPass],
)
pipeline.pop_stage(-1) # Do not compare output

pipeline.run()
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