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Update on "ET_HAS_EXCEPTIONS: require defined(_MSC_VER) to conclude _HAS_EXCEPTIONS implies exceptions are on"
_HAS_EXCEPTIONS might get defined on some other platform by coincidence; require it to be actual MSVC for us to conclude exceptions are on. Differential Revision: [D76857541](https://our.internmc.facebook.com/intern/diff/D76857541/) [ghstack-poisoned]
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‎.ci/scripts/test_model.sh

Lines changed: 27 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -188,6 +188,14 @@ test_model_with_qnn() {
188188
EXPORT_SCRIPT=edsr
189189
# Additional deps for edsr
190190
pip install piq
191+
elif [[ "${MODEL_NAME}" == "albert" ]]; then
192+
EXPORT_SCRIPT=albert
193+
elif [[ "${MODEL_NAME}" == "bert" ]]; then
194+
EXPORT_SCRIPT=bert
195+
elif [[ "${MODEL_NAME}" == "distilbert" ]]; then
196+
EXPORT_SCRIPT=distilbert
197+
elif [[ "${MODEL_NAME}" == "eurobert" ]]; then
198+
EXPORT_SCRIPT=eurobert
191199
else
192200
echo "Unsupported model $MODEL_NAME"
193201
exit 1
@@ -197,7 +205,25 @@ test_model_with_qnn() {
197205
# TODO(guangyang): Make QNN chipset matches the target device
198206
QNN_CHIPSET=SM8450
199207

200-
"${PYTHON_EXECUTABLE}" -m examples.qualcomm.scripts.${EXPORT_SCRIPT} -b ${CMAKE_OUTPUT_DIR} -m ${QNN_CHIPSET} --ci --compile_only $EXTRA_FLAGS
208+
SCRIPT_FOLDER=""
209+
case "${MODEL_NAME}" in
210+
"dl3"|"mv3"|"mv2"|"ic4"|"ic3"|"vit"|"mb"|"w2l")
211+
SCRIPT_FOLDER=scripts
212+
;;
213+
"albert"|"bert"|"distilbert")
214+
pip install evaluate
215+
SCRIPT_FOLDER=oss_scripts
216+
# Bert models running in 16bit will encounter op validation fail on some operations,
217+
# which requires CHIPSET >= SM8550.
218+
QNN_CHIPSET=SM8550
219+
;;
220+
*)
221+
echo "Unsupported model $MODEL_NAME"
222+
exit 1
223+
;;
224+
esac
225+
226+
"${PYTHON_EXECUTABLE}" -m examples.qualcomm.${SCRIPT_FOLDER}.${EXPORT_SCRIPT} -b ${CMAKE_OUTPUT_DIR} -m ${QNN_CHIPSET} --ci --compile_only $EXTRA_FLAGS
201227
EXPORTED_MODEL=$(find "./${EXPORT_SCRIPT}" -type f -name "${MODEL_NAME}*.pte" -print -quit)
202228
}
203229

‎.github/workflows/trunk.yml

Lines changed: 26 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -480,6 +480,32 @@ jobs:
480480
PYTHON_EXECUTABLE=python bash .ci/scripts/build-qnn-sdk.sh
481481
PYTHON_EXECUTABLE=python bash .ci/scripts/test_model.sh ${{ matrix.model }} "cmake" "qnn"
482482
483+
test-qnn-optimum-model:
484+
name: test-qnn-optimum-model
485+
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
486+
permissions:
487+
id-token: write
488+
contents: read
489+
strategy:
490+
matrix:
491+
dtype: [fp32]
492+
model: [albert, bert, distilbert] # eurobert requires transfomer >= 4.48.0, skip for now
493+
fail-fast: false
494+
with:
495+
runner: linux.2xlarge
496+
docker-image: executorch-ubuntu-22.04-qnn-sdk
497+
submodules: 'recursive'
498+
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
499+
timeout: 900
500+
script: |
501+
# The generic Linux job chooses to use base env, not the one setup by the image
502+
CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
503+
conda activate "${CONDA_ENV}"
504+
PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh --build-tool cmake
505+
PYTHON_EXECUTABLE=python bash .ci/scripts/setup-qnn-deps.sh
506+
PYTHON_EXECUTABLE=python bash .ci/scripts/build-qnn-sdk.sh
507+
PYTHON_EXECUTABLE=python bash .ci/scripts/test_model.sh ${{ matrix.model }} "cmake" "qnn"
508+
483509
test-apple-model:
484510
name: test-apple-model
485511
uses: pytorch/test-infra/.github/workflows/macos_job.yml@main

‎.gitignore

Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -42,6 +42,9 @@ xcuserdata/
4242
*.xcworkspace/
4343
*.xcframework/
4444

45+
# clangd
46+
.cache/
47+
4548
# misc
4649
/.vscode/
4750
*.so

‎backends/__init__.py

Whitespace-only changes.

‎backends/arm/test/misc/test_lifted_tensor.py

Lines changed: 3 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -12,7 +12,7 @@
1212
TosaPipelineBI,
1313
TosaPipelineMI,
1414
)
15-
from executorch.backends.xnnpack.test.tester import ToEdge
15+
from executorch.backends.test.harness.stages import StageType
1616

1717

1818
input_t1 = Tuple[torch.Tensor]
@@ -72,9 +72,8 @@ def test_partition_lifted_tensor_tosa_MI(test_data: input_t1):
7272
use_to_edge_transform_and_lower=False,
7373
)
7474
pipeline.run()
75-
to_edge_stage_name = pipeline.tester.stage_name(ToEdge)
7675
signature = (
77-
pipeline.tester.stages[to_edge_stage_name]
76+
pipeline.tester.stages[StageType.TO_EDGE]
7877
.artifact.exported_program()
7978
.graph_signature
8079
)
@@ -94,9 +93,8 @@ def test_partition_lifted_tensor_tosa_BI(test_data: input_t1):
9493
use_to_edge_transform_and_lower=False,
9594
)
9695
pipeline.run()
97-
to_edge_stage_name = pipeline.tester.stage_name(ToEdge)
9896
signature = (
99-
pipeline.tester.stages[to_edge_stage_name]
97+
pipeline.tester.stages[StageType.TO_EDGE]
10098
.artifact.exported_program()
10199
.graph_signature
102100
)

‎backends/arm/test/passes/test_cast_int64_pass.py

Lines changed: 5 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -11,6 +11,8 @@
1111
from executorch.backends.arm.test import common
1212
from executorch.backends.arm.test.tester.test_pipeline import PassPipeline
1313

14+
from executorch.backends.test.harness.stages import StageType
15+
1416
input_t = Tuple[torch.Tensor] # Input x
1517

1618

@@ -40,6 +42,8 @@ def test_int64_model(test_data: input_t):
4042
)
4143
pipeline.run()
4244

43-
exported_program = pipeline.tester.get_artifact("RunPasses").exported_program()
45+
exported_program = pipeline.tester.get_artifact(
46+
StageType.RUN_PASSES
47+
).exported_program()
4448
for state in exported_program.state_dict:
4549
assert exported_program.state_dict[state].dtype == torch.int32

‎backends/arm/test/quantizer/test_generic_annotater.py

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -9,6 +9,7 @@
99
import torch
1010
from executorch.backends.arm.quantizer import is_annotated
1111
from executorch.backends.arm.test.tester.test_pipeline import TosaPipelineBI
12+
from executorch.backends.test.harness.stages import StageType
1213

1314
from torch.fx.passes.utils.source_matcher_utils import get_source_partitions
1415

@@ -36,7 +37,7 @@ def check_annotation(model):
3637
pipeline.pop_stage("run_method_and_compare_outputs")
3738
pipeline.run()
3839

39-
artifact = pipeline.tester.get_artifact("Quantize")
40+
artifact = pipeline.tester.get_artifact(StageType.QUANTIZE)
4041

4142
partitions = get_source_partitions(artifact.graph, [model.op])
4243
partitions = list(itertools.chain.from_iterable(partitions.values()))

‎backends/arm/test/tester/analyze_output_utils.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -14,7 +14,7 @@
1414
get_output_quantization_params,
1515
)
1616

17-
from executorch.backends.xnnpack.test.tester.tester import Export, Quantize
17+
from executorch.backends.test.harness.stages import StageType
1818

1919
logger = logging.getLogger(__name__)
2020

@@ -238,8 +238,8 @@ def dump_error_output(
238238
if path_to_tosa_files is None:
239239
path_to_tosa_files = tempfile.mkdtemp(prefix="executorch_result_dump_")
240240

241-
export_stage = tester.stages.get(tester.stage_name(Export), None)
242-
quantize_stage = tester.stages.get(tester.stage_name(Quantize), None)
241+
export_stage = tester.stages.get(StageType.EXPORT, None)
242+
quantize_stage = tester.stages.get(StageType.QUANTIZE, None)
243243
if export_stage is not None and quantize_stage is not None:
244244
output_nodes = get_output_nodes(export_stage.artifact)
245245
qp_input = get_input_quantization_params(export_stage.artifact)

‎backends/arm/test/tester/arm_tester.py

Lines changed: 26 additions & 28 deletions
Original file line numberDiff line numberDiff line change
@@ -61,6 +61,7 @@
6161
from executorch.backends.arm.tosa_partitioner import TOSAPartitioner
6262
from executorch.backends.arm.tosa_specification import TosaSpecification
6363

64+
from executorch.backends.test.harness.stages import Stage, StageType
6465
from executorch.backends.xnnpack.test.tester import Tester
6566
from executorch.devtools.backend_debug import get_delegation_info
6667

@@ -259,10 +260,13 @@ def wrapped_ep_pass(ep: ExportedProgram) -> ExportedProgram:
259260
super().run(artifact, inputs)
260261

261262

262-
class InitialModel(tester.Stage):
263+
class InitialModel(Stage):
263264
def __init__(self, model: torch.nn.Module):
264265
self.model = model
265266

267+
def stage_type(self) -> StageType:
268+
return StageType.INITIAL_MODEL
269+
266270
def run(self, artifact, inputs=None) -> None:
267271
pass
268272

@@ -305,13 +309,13 @@ def __init__(
305309
self.constant_methods = constant_methods
306310
self.compile_spec = compile_spec
307311
super().__init__(model, example_inputs, dynamic_shapes)
308-
self.pipeline[self.stage_name(InitialModel)] = [
309-
self.stage_name(tester.Quantize),
310-
self.stage_name(tester.Export),
312+
self.pipeline[StageType.INITIAL_MODEL] = [
313+
StageType.QUANTIZE,
314+
StageType.EXPORT,
311315
]
312316

313317
# Initial model needs to be set as a *possible* but not yet added Stage, therefore add None entry.
314-
self.stages[self.stage_name(InitialModel)] = None
318+
self.stages[StageType.INITIAL_MODEL] = None
315319
self._run_stage(InitialModel(self.original_module))
316320

317321
def quantize(
@@ -413,7 +417,7 @@ def serialize(
413417
return super().serialize(serialize_stage)
414418

415419
def is_quantized(self) -> bool:
416-
return self.stages[self.stage_name(tester.Quantize)] is not None
420+
return self.stages[StageType.QUANTIZE] is not None
417421

418422
def run_method_and_compare_outputs(
419423
self,
@@ -442,18 +446,16 @@ def run_method_and_compare_outputs(
442446
"""
443447

444448
if not run_eager_mode:
445-
edge_stage = self.stages[self.stage_name(tester.ToEdge)]
449+
edge_stage = self.stages[StageType.TO_EDGE]
446450
if edge_stage is None:
447-
edge_stage = self.stages[
448-
self.stage_name(tester.ToEdgeTransformAndLower)
449-
]
451+
edge_stage = self.stages[StageType.TO_EDGE_TRANSFORM_AND_LOWER]
450452
assert (
451453
edge_stage is not None
452454
), "To compare outputs, at least the ToEdge or ToEdgeTransformAndLower stage needs to be run."
453455
else:
454456
# Run models in eager mode. We do this when we want to check that the passes
455457
# are numerically accurate and the exported graph is correct.
456-
export_stage = self.stages[self.stage_name(tester.Export)]
458+
export_stage = self.stages[StageType.EXPORT]
457459
assert (
458460
export_stage is not None
459461
), "To compare outputs in eager mode, the model must be at Export stage"
@@ -463,11 +465,11 @@ def run_method_and_compare_outputs(
463465
is_quantized = self.is_quantized()
464466

465467
if is_quantized:
466-
reference_stage = self.stages[self.stage_name(tester.Quantize)]
468+
reference_stage = self.stages[StageType.QUANTIZE]
467469
else:
468-
reference_stage = self.stages[self.stage_name(InitialModel)]
470+
reference_stage = self.stages[StageType.INITIAL_MODEL]
469471

470-
exported_program = self.stages[self.stage_name(tester.Export)].artifact
472+
exported_program = self.stages[StageType.EXPORT].artifact
471473
output_nodes = get_output_nodes(exported_program)
472474

473475
output_qparams = get_output_quantization_params(output_nodes)
@@ -477,7 +479,7 @@ def run_method_and_compare_outputs(
477479
quantization_scales.append(getattr(output_qparams[node], "scale", None))
478480

479481
logger.info(
480-
f"Comparing Stage '{self.stage_name(test_stage)}' with Stage '{self.stage_name(reference_stage)}'"
482+
f"Comparing Stage '{test_stage.stage_type()}' with Stage '{reference_stage.stage_type()}'"
481483
)
482484

483485
# Loop inputs and compare reference stage with the compared stage.
@@ -528,14 +530,12 @@ def get_graph(self, stage: str | None = None) -> Graph:
528530
stage = self.cur
529531
artifact = self.get_artifact(stage)
530532
if (
531-
self.cur == self.stage_name(tester.ToEdge)
532-
or self.cur == self.stage_name(Partition)
533-
or self.cur == self.stage_name(ToEdgeTransformAndLower)
533+
self.cur == StageType.TO_EDGE
534+
or self.cur == StageType.PARTITION
535+
or self.cur == StageType.TO_EDGE_TRANSFORM_AND_LOWER
534536
):
535537
graph = artifact.exported_program().graph
536-
elif self.cur == self.stage_name(tester.Export) or self.cur == self.stage_name(
537-
tester.Quantize
538-
):
538+
elif self.cur == StageType.EXPORT or self.cur == StageType.QUANTIZE:
539539
graph = artifact.graph
540540
else:
541541
raise RuntimeError(
@@ -556,13 +556,13 @@ def dump_operator_distribution(
556556
Returns self for daisy-chaining.
557557
"""
558558
line = "#" * 10
559-
to_print = f"{line} {self.cur.capitalize()} Operator Distribution {line}\n"
559+
to_print = f"{line} {self.cur} Operator Distribution {line}\n"
560560

561561
if (
562562
self.cur
563563
in (
564-
self.stage_name(tester.Partition),
565-
self.stage_name(ToEdgeTransformAndLower),
564+
StageType.PARTITION,
565+
StageType.TO_EDGE_TRANSFORM_AND_LOWER,
566566
)
567567
and print_table
568568
):
@@ -602,9 +602,7 @@ def dump_dtype_distribution(
602602
"""
603603

604604
line = "#" * 10
605-
to_print = (
606-
f"{line} {self.cur.capitalize()} Placeholder Dtype Distribution {line}\n"
607-
)
605+
to_print = f"{line} {self.cur} Placeholder Dtype Distribution {line}\n"
608606

609607
graph = self.get_graph(self.cur)
610608
tosa_spec = get_tosa_spec(self.compile_spec)
@@ -653,7 +651,7 @@ def run_transform_for_annotation_pipeline(
653651
stage = self.cur
654652
# We need to clone the artifact in order to ensure that the state_dict is preserved after passes are run.
655653
artifact = self.get_artifact(stage)
656-
if self.cur == self.stage_name(tester.Export):
654+
if self.cur == StageType.EXPORT:
657655
new_gm = ArmPassManager(get_tosa_spec(self.compile_spec)).transform_for_annotation_pipeline( # type: ignore[arg-type]
658656
graph_module=artifact.graph_module
659657
)

‎backends/qualcomm/_passes/__init__.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -8,7 +8,6 @@
88
from .annotate_quant_attrs import AnnotateQuantAttrs
99
from .annotate_stack import AnnotateStack
1010
from .annotate_unbind import AnnotateUnbind
11-
from .convert_bmm_to_matmul import ConvertBmmToMatmul
1211
from .convert_conv1d_to_conv2d import ConvertConv1dToConv2d
1312
from .convert_square_to_pow import ConvertSquareToPow
1413
from .decompose_any import DecomposeAny
@@ -19,6 +18,7 @@
1918
from .decompose_linalg_vector_norm import DecomposeLinalgVectorNorm
2019
from .decompose_roll import DecomposeRoll
2120
from .decompose_silu import DecomposeSilu
21+
from .decompose_wrap_with_autocast import DecomposeWrapWithAutocast
2222
from .expand_broadcast_tensor_shape import ExpandBroadcastTensorShape
2323
from .fixed_linear_keep_dim import FixedLinearKeepDim
2424
from .fold_qdq import FoldQDQ
@@ -45,7 +45,6 @@
4545
AnnotateQuantAttrs,
4646
AnnotateStack,
4747
AnnotateUnbind,
48-
ConvertBmmToMatmul,
4948
ConvertConv1dToConv2d,
5049
ConvertSquareToPow,
5150
DecomposeAny,
@@ -56,6 +55,7 @@
5655
DecomposeLinalgVectorNorm,
5756
DecomposeRoll,
5857
DecomposeSilu,
58+
DecomposeWrapWithAutocast,
5959
ExpandBroadcastTensorShape,
6060
FixedLinearKeepDim,
6161
FoldQDQ,

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