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Revert "Revert "Add qnn backend to pip packages (#13794)"" (#14220)
Reverts #14212
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‎.ci/scripts/test_wheel_package_qnn.sh‎

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#!/bin/bash
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# === CI Wheel Build & Test Script ===
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# Exit immediately on error, print each command, and capture all output to build.log
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set -e
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set -x
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exec > >(tee -i build.log) 2>&1
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# Save repo root
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REPO_ROOT=$(pwd)
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# ----------------------------
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# Dynamically create script_qnn_wheel_test.py
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# ----------------------------
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cat > "/tmp/script_qnn_wheel_test.py" << 'EOF'
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# pyre-ignore-all-errors
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import argparse
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import torch
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from executorch.backends.qualcomm.quantizer.quantizer import QnnQuantizer
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from executorch.backends.qualcomm.utils.utils import (
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generate_htp_compiler_spec,
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generate_qnn_executorch_compiler_spec,
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get_soc_to_chipset_map,
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to_edge_transform_and_lower_to_qnn,
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)
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from executorch.exir.backend.utils import format_delegated_graph
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from executorch.examples.models.model_factory import EagerModelFactory
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from executorch.exir.capture._config import ExecutorchBackendConfig
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from executorch.extension.export_util.utils import save_pte_program
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from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e, prepare_qat_pt2e
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def main() -> None:
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parser = argparse.ArgumentParser()
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parser.add_argument("-f", "--output_folder", type=str, default="", help="The folder to store the exported program")
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parser.add_argument("--soc", type=str, default="SM8650", help="Specify the SoC model.")
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parser.add_argument("-q", "--quantization", choices=["ptq", "qat"], help="Run post-traininig quantization.")
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args = parser.parse_args()
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class LinearModule(torch.nn.Module):
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def __init__(self):
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super().__init__()
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self.linear = torch.nn.Linear(3, 3)
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def forward(self, arg):
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return self.linear(arg)
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def get_example_inputs(self):
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return (torch.randn(3, 3),)
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model = LinearModule()
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example_inputs = model.get_example_inputs()
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if args.quantization:
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quantizer = QnnQuantizer()
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m = torch.export.export(model.eval(), example_inputs, strict=True).module()
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if args.quantization == "qat":
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m = prepare_qat_pt2e(m, quantizer)
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m(*example_inputs)
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elif args.quantization == "ptq":
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m = prepare_pt2e(m, quantizer)
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m(*example_inputs)
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m = convert_pt2e(m)
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else:
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m = model
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use_fp16 = True if args.quantization is None else False
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backend_options = generate_htp_compiler_spec(use_fp16=use_fp16)
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compile_spec = generate_qnn_executorch_compiler_spec(
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soc_model=get_soc_to_chipset_map()[args.soc],
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backend_options=backend_options,
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)
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delegated_program = to_edge_transform_and_lower_to_qnn(m, example_inputs, compile_spec)
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output_graph = format_delegated_graph(delegated_program.exported_program().graph_module)
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# Ensure QnnBackend is in the output graph
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assert "QnnBackend" in output_graph
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executorch_program = delegated_program.to_executorch(
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config=ExecutorchBackendConfig(extract_delegate_segments=False)
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)
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save_pte_program(executorch_program, "linear", args.output_folder)
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if __name__ == "__main__":
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main()
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EOF
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# ----------------------------
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# Wheel build and .so checks
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# ----------------------------
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echo "=== Building Wheel Package ==="
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source .ci/scripts/utils.sh
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install_executorch
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EXECUTORCH_BUILDING_WHEEL=1 python setup.py bdist_wheel
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unset EXECUTORCH_BUILDING_WHEEL
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WHEEL_FILE=$(ls dist/*.whl | head -n 1)
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echo "Found wheel: $WHEEL_FILE"
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PYTHON_VERSION=$1
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# ----------------------------
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# Check wheel does NOT contain qualcomm/sdk
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# ----------------------------
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echo "Checking wheel does not contain qualcomm/sdk..."
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SDK_FILES=$(unzip -l "$WHEEL_FILE" | awk '{print $4}' | grep "executorch/backends/qualcomm/sdk" || true)
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if [ -n "$SDK_FILES" ]; then
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echo "ERROR: Wheel package contains unexpected qualcomm/sdk files:"
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echo "$SDK_FILES"
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exit 1
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else
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echo "OK: No qualcomm/sdk files found in wheel"
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fi
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# ----------------------------
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# Check .so files in the wheel
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# ----------------------------
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echo "Checking for .so files inside the wheel..."
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WHEEL_SO_FILES=$(unzip -l "$WHEEL_FILE" | awk '{print $4}' | grep "executorch/backends/qualcomm/python" || true)
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if [ -z "$WHEEL_SO_FILES" ]; then
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echo "ERROR: No .so files found in wheel under executorch/backends/qualcomm/python"
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exit 1
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else
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echo "Wheel contains the following .so files:"
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echo "$WHEEL_SO_FILES"
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fi
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# ----------------------------
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# Helpers
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# ----------------------------
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get_site_packages_dir () {
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local PYBIN="$1"
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"$PYBIN" - <<'PY'
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import sysconfig, sys
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print(sysconfig.get_paths().get("purelib") or sysconfig.get_paths().get("platlib"))
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PY
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}
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run_core_tests () {
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local PYBIN="$1" # path to python
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local PIPBIN="$2" # path to pip
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local LABEL="$3" # label to print (conda/venv)
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echo "=== [$LABEL] Installing wheel & deps ==="
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"$PIPBIN" install --upgrade pip
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"$PIPBIN" install "$WHEEL_FILE"
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"$PIPBIN" install torch=="2.9.0.dev20250906" --index-url "https://download.pytorch.org/whl/nightly/cpu"
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"$PIPBIN" install --pre torchao --index-url "https://download.pytorch.org/whl/nightly/cpu"
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echo "=== [$LABEL] Import smoke tests ==="
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"$PYBIN" -c "import executorch; print('executorch imported successfully')"
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"$PYBIN" -c "import executorch.backends.qualcomm; print('executorch.backends.qualcomm imported successfully')"
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echo "=== [$LABEL] List installed executorch/backends/qualcomm/python ==="
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local SITE_DIR
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SITE_DIR="$(get_site_packages_dir "$PYBIN")"
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local SO_DIR="$SITE_DIR/executorch/backends/qualcomm/python"
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ls -l "$SO_DIR" || echo "Folder does not exist!"
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echo "=== [$LABEL] Run export script to generate linear.pte ==="
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(cd "$REPO_ROOT" && "$PYBIN" "/tmp/script_qnn_wheel_test.py")
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if [ -f "$REPO_ROOT/linear.pte" ]; then
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echo "[$LABEL] Model file linear.pte successfully created"
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else
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echo "ERROR: [$LABEL] Model file linear.pte was not created"
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exit 1
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fi
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}
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# ----------------------------
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# Conda environment setup & tests
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# ----------------------------
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echo "=== Testing in Conda env ==="
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TEMP_ENV_DIR=$(mktemp -d)
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echo "Using temporary directory for conda: $TEMP_ENV_DIR"
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conda create -y -p "$TEMP_ENV_DIR/env" python=$PYTHON_VERSION
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# derive python/pip paths inside the conda env
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CONDA_PY="$TEMP_ENV_DIR/env/bin/python"
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CONDA_PIP="$TEMP_ENV_DIR/env/bin/pip"
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# Some images require conda run; keep pip/python direct to simplify path math
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run_core_tests "$CONDA_PY" "$CONDA_PIP" "conda"
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# Cleanup conda env
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conda env remove -p "$TEMP_ENV_DIR/env" -y || true
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rm -rf "$TEMP_ENV_DIR"
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# ----------------------------
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# Python venv setup & tests
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# ----------------------------
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echo "=== Testing in Python venv ==="
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TEMP_VENV_DIR=$(mktemp -d)
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echo "Using temporary directory for venv: $TEMP_VENV_DIR"
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python3 -m venv "$TEMP_VENV_DIR/venv"
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VENV_PY="$TEMP_VENV_DIR/venv/bin/python"
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VENV_PIP="$TEMP_VENV_DIR/venv/bin/pip"
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# Ensure venv has wheel/build basics if needed
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"$VENV_PIP" install --upgrade pip
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run_core_tests "$VENV_PY" "$VENV_PIP" "venv"
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# Cleanup venv
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rm -rf "$TEMP_VENV_DIR"
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echo "=== All tests completed! ==="

‎.github/workflows/pull.yml‎

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cancel-in-progress: true
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jobs:
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test-qnn-wheel-packages-linux:
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name: test-qnn-wheel-packages-linux
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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strategy:
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fail-fast: false
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matrix:
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python-version: [ "3.10", "3.11", "3.12" ]
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with:
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runner: linux.2xlarge
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docker-image: ci-image:executorch-ubuntu-22.04-qnn-sdk
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submodules: 'recursive'
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ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
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timeout: 180
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script: |
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# The generic Linux job chooses to use base env, not the one setup by the image
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CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
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conda activate "${CONDA_ENV}"
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# Create a clean env for each python version
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conda create -y -n test_env_${{ matrix.python-version }} python=${{ matrix.python-version }}
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conda activate test_env_${{ matrix.python-version }}
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PYTHON_EXECUTABLE=python bash .ci/scripts/test_wheel_package_qnn.sh "${{ matrix.python-version }}"
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test-setup-linux-gcc:
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name: test-setup-linux-gcc
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main

‎.gitignore‎

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cmake-ios-out/
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cmake-out*
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cmake-out-android/
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build-android/
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build-x86/
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dist/
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ethos-u-scratch/
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executorch.egg-info

‎backends/qualcomm/__init__.py‎

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import os
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from .scripts.download_qnn_sdk import (
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check_glibc_exist_and_validate,
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install_qnn_sdk,
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is_linux_x86,
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)
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env_flag = os.getenv("EXECUTORCH_BUILDING_WHEEL", "0").lower()
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# If users have preinstalled QNN_SDK_ROOT, we will use it.
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qnn_sdk_root_flag = os.getenv("QNN_SDK_ROOT", None)
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if (
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env_flag not in ("1", "true", "yes")
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and not qnn_sdk_root_flag
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and is_linux_x86()
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and check_glibc_exist_and_validate()
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):
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ok = install_qnn_sdk()
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if not ok:
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raise RuntimeError("Failed to install QNN SDK. Please check the logs above.")

‎backends/qualcomm/runtime/backends/QnnImplementation.cpp‎

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* LICENSE file in the root directory of this source tree.
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*/
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#include <executorch/backends/qualcomm/runtime/backends/QnnImplementation.h>
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#include "QnnInterface.h"
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namespace executorch {
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namespace backends {
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const QnnSaver_Config_t** saver_config) {
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Qnn_ErrorHandle_t error = QNN_SUCCESS;
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void* lib_handle = nullptr;
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lib_handle = dlopen(lib_path.c_str(), RTLD_NOW | RTLD_GLOBAL);
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// If the library is already loaded, return the handle.
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lib_handle = dlopen(lib_path.c_str(), RTLD_NOW | RTLD_NOLOAD);
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if (!lib_handle) {
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lib_handle = dlopen(lib_path.c_str(), RTLD_NOW | RTLD_GLOBAL);
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}
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if (lib_handle == nullptr) {
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QNN_EXECUTORCH_LOG_ERROR(
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"Cannot Open QNN library %s, with error: %s",

‎backends/qualcomm/scripts/build.sh‎

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#!/usr/bin/env bash
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# Copyright (c) Qualcomm Innovation Center, Inc.
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# All rights reserved
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#

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