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Nov 13, 2025
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[Executorch][QNN] Improve qualcomm examples #15477

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39 changes: 24 additions & 15 deletions examples/qualcomm/oss_scripts/albert.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,9 @@


def main(args):
if args.compile_only and args.pre_gen_pte:
raise RuntimeError("Cannot set both compile_only and pre_gen_pte as true")

skip_node_id_set, skip_node_op_set = parse_skip_delegation_node(args)

os.makedirs(args.artifact, exist_ok=True)
Expand Down Expand Up @@ -60,26 +63,32 @@ def main(args):
module = AutoModelForMaskedLM.from_pretrained(model_name, config=config).eval()
pte_filename = "albert_qnn_q16"

# lower to QNN
passes_job = get_capture_program_passes()
build_executorch_binary(
module,
inputs[0],
args.model,
f"{args.artifact}/{pte_filename}",
dataset=inputs,
skip_node_id_set=skip_node_id_set,
skip_node_op_set=skip_node_op_set,
quant_dtype=QuantDtype.use_16a16w,
passes_job=passes_job,
shared_buffer=args.shared_buffer,
)
# Skip lowering/compilation if using pre-generated PTE
if not args.pre_gen_pte:
# lower to QNN
passes_job = get_capture_program_passes()
build_executorch_binary(
module,
inputs[0],
args.model,
f"{args.artifact}/{pte_filename}",
dataset=inputs,
skip_node_id_set=skip_node_id_set,
skip_node_op_set=skip_node_op_set,
quant_dtype=QuantDtype.use_16a16w,
passes_job=passes_job,
shared_buffer=args.shared_buffer,
)

if args.compile_only:
return

workspace = f"/data/local/tmp/{getpass.getuser()}/executorch/{pte_filename}"
pte_path = f"{args.artifact}/{pte_filename}.pte"
pte_path = (
f"{args.pre_gen_pte}/{pte_filename}.pte"
if args.pre_gen_pte
else f"{args.artifact}/{pte_filename}.pte"
)

adb = SimpleADB(
qnn_sdk=os.getenv("QNN_SDK_ROOT"),
Expand Down
39 changes: 24 additions & 15 deletions examples/qualcomm/oss_scripts/bert.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,9 @@


def main(args):
if args.compile_only and args.pre_gen_pte:
raise RuntimeError("Cannot set both compile_only and pre_gen_pte as true")

skip_node_id_set, skip_node_op_set = parse_skip_delegation_node(args)

os.makedirs(args.artifact, exist_ok=True)
Expand Down Expand Up @@ -57,26 +60,32 @@ def main(args):
).eval()
pte_filename = "bert_qnn_q16"

# lower to QNN
passes_job = get_capture_program_passes()
build_executorch_binary(
module,
inputs[0],
args.model,
f"{args.artifact}/{pte_filename}",
dataset=inputs,
skip_node_id_set=skip_node_id_set,
skip_node_op_set=skip_node_op_set,
quant_dtype=QuantDtype.use_16a8w,
passes_job=passes_job,
shared_buffer=args.shared_buffer,
)
# Skip lowering/compilation if using pre-generated PTE
if not args.pre_gen_pte:
# lower to QNN
passes_job = get_capture_program_passes()
build_executorch_binary(
module,
inputs[0],
args.model,
f"{args.artifact}/{pte_filename}",
dataset=inputs,
skip_node_id_set=skip_node_id_set,
skip_node_op_set=skip_node_op_set,
quant_dtype=QuantDtype.use_16a8w,
passes_job=passes_job,
shared_buffer=args.shared_buffer,
)

if args.compile_only:
return

workspace = f"/data/local/tmp/{getpass.getuser()}/executorch/{pte_filename}"
pte_path = f"{args.artifact}/{pte_filename}.pte"
pte_path = (
f"{args.pre_gen_pte}/{pte_filename}.pte"
if args.pre_gen_pte
else f"{args.artifact}/{pte_filename}.pte"
)

adb = SimpleADB(
qnn_sdk=os.getenv("QNN_SDK_ROOT"),
Expand Down
39 changes: 24 additions & 15 deletions examples/qualcomm/oss_scripts/distilbert.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,9 @@


def main(args):
if args.compile_only and args.pre_gen_pte:
raise RuntimeError("Cannot set both compile_only and pre_gen_pte as true")

skip_node_id_set, skip_node_op_set = parse_skip_delegation_node(args)

os.makedirs(args.artifact, exist_ok=True)
Expand Down Expand Up @@ -58,26 +61,32 @@ def main(args):
).eval()
pte_filename = "distilbert_qnn_q16"

# lower to QNN
passes_job = get_capture_program_passes()
build_executorch_binary(
module,
inputs[0],
args.model,
f"{args.artifact}/{pte_filename}",
dataset=inputs,
skip_node_id_set=skip_node_id_set,
skip_node_op_set=skip_node_op_set,
quant_dtype=QuantDtype.use_16a8w,
passes_job=passes_job,
shared_buffer=args.shared_buffer,
)
# Skip lowering/compilation if using pre-generated PTE
if not args.pre_gen_pte:
# lower to QNN
passes_job = get_capture_program_passes()
build_executorch_binary(
module,
inputs[0],
args.model,
f"{args.artifact}/{pte_filename}",
dataset=inputs,
skip_node_id_set=skip_node_id_set,
skip_node_op_set=skip_node_op_set,
quant_dtype=QuantDtype.use_16a8w,
passes_job=passes_job,
shared_buffer=args.shared_buffer,
)

if args.compile_only:
return

workspace = f"/data/local/tmp/{getpass.getuser()}/executorch/{pte_filename}"
pte_path = f"{args.artifact}/{pte_filename}.pte"
pte_path = (
f"{args.pre_gen_pte}/{pte_filename}.pte"
if args.pre_gen_pte
else f"{args.artifact}/{pte_filename}.pte"
)

adb = SimpleADB(
qnn_sdk=os.getenv("QNN_SDK_ROOT"),
Expand Down
48 changes: 29 additions & 19 deletions examples/qualcomm/oss_scripts/eurobert.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,9 @@


def main(args):
if args.compile_only and args.pre_gen_pte:
raise RuntimeError("Cannot set both compile_only and pre_gen_pte as true")

assert (
transformers.__version__ >= TRANSFORMERS_VERSION
), f"Please ensure transformers version >= {TRANSFORMERS_VERSION}, current version is {transformers.__version__}"
Expand Down Expand Up @@ -88,33 +91,40 @@ def replace_rms_norm_with_native_rms_norm(module: torch.nn.Module):

pte_filename = "eurobert_qnn_q16"

# lower to QNN
passes_job = get_capture_program_passes()
quantizer = make_quantizer(
quant_dtype=QuantDtype.use_16a16w,
)
quantizer.add_custom_quant_annotations((annotate_eurobert,))
with torch.no_grad():
build_executorch_binary(
model,
inputs[0],
args.model,
f"{args.artifact}/{pte_filename}",
dataset=inputs,
skip_node_id_set=skip_node_id_set,
skip_node_op_set=skip_node_op_set,
custom_quantizer=quantizer,
passes_job=passes_job,
shared_buffer=args.shared_buffer,
# Skip lowering/compilation if using pre-generated PTE
if not args.pre_gen_pte:
# lower to QNN
passes_job = get_capture_program_passes()
quantizer = make_quantizer(
quant_dtype=QuantDtype.use_16a16w,
)
quantizer.add_custom_quant_annotations((annotate_eurobert,))
with torch.no_grad():
build_executorch_binary(
model,
inputs[0],
args.model,
f"{args.artifact}/{pte_filename}",
dataset=inputs,
skip_node_id_set=skip_node_id_set,
skip_node_op_set=skip_node_op_set,
custom_quantizer=quantizer,
passes_job=passes_job,
shared_buffer=args.shared_buffer,
)

if args.compile_only:
return

pte_path = (
f"{args.pre_gen_pte}/{pte_filename}.pte"
if args.pre_gen_pte
else f"{args.artifact}/{pte_filename}.pte"
)
adb = SimpleADB(
qnn_sdk=os.getenv("QNN_SDK_ROOT"),
build_path=f"{args.build_folder}",
pte_path=f"{args.artifact}/{pte_filename}.pte",
pte_path=pte_path,
workspace=f"/data/local/tmp/executorch/{pte_filename}",
device_id=args.device,
host_id=args.host,
Expand Down
3 changes: 2 additions & 1 deletion examples/qualcomm/oss_scripts/llama/llama.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1023,7 +1023,8 @@ def post_process():
runner=f"examples/qualcomm/oss_scripts/llama/qnn_llama_runner",
)
# No pregen inputs, input_list is not required
adb.push(inputs=[], files=[runtime_tokenizer_path])
if not args.skip_push:
adb.push(inputs=[], files=[runtime_tokenizer_path])
adb.execute(custom_runner_cmd=runner_cmd)
adb.pull(output_path=args.artifact, callback=post_process)

Expand Down
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