Clean

Author: daniil-lyakhov

backends/openvino/scripts/openvino_build.sh

@@ -26,14 +26,11 @@ main() {
         cmake -DCMAKE_INSTALL_PREFIX="${build_dir}" \
               -DCMAKE_BUILD_TYPE=Release \
               -DEXECUTORCH_BUILD_OPENVINO=ON \
-              -DEXECUTORCH_BUILD_XNNPACK=ON \
               -DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
               -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \
               -DEXECUTORCH_BUILD_EXTENSION_RUNNER_UTIL=ON \
               -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
               -DEXECUTORCH_BUILD_OPENVINO_EXECUTOR_RUNNER=ON \
-              -DPYTHON_EXECUTABLE=python \
-              -DEXECUTORCH_LOG_LEVEL=Debug \
               -B"${build_dir}"
 
 
@@ -51,14 +48,13 @@ main() {
         # Set parameters to configure the project with CMake
         # Note: Add any additional configuration options you need here
         export CMAKE_ARGS="-DEXECUTORCH_BUILD_OPENVINO=ON \
-                           -DEXECUTORCH_BUILD_XNNPACK=ON \
                            -DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
                            -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \
                            -DEXECUTORCH_BUILD_EXTENSION_RUNNER_UTIL=ON \
                            -DEXECUTORCH_ENABLE_LOGGING=ON \
                            -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
                            -DEXECUTORCH_BUILD_PYBIND=ON"
-        export CMAKE_BUILD_ARGS="--target openvino_backend xnnpack_backend"
+        export CMAKE_BUILD_ARGS="--target openvino_backend"
 
         # Build the package
         pip install . --no-build-isolation

examples/models/yolo12/CMakeLists.txt

@@ -2,7 +2,7 @@ cmake_minimum_required(VERSION 3.5)
 
 project(Yolo12DetectionDemo VERSION 0.1)
 
-option(USE_OPENVINO_BACKEND "Build the tutorial with the XNNPACK backend" ON)
+option(USE_OPENVINO_BACKEND "Build the tutorial with the OPENVINO backend" ON)
 option(USE_XNNPACK_BACKEND "Build the tutorial with the XNNPACK backend" OFF)
 
 set(CMAKE_INCLUDE_CURRENT_DIR ON)

examples/models/yolo12/README.md

@@ -2,11 +2,11 @@
 
 <p align="center">
       <br>
-      <img src="./yolo12s_demo.gif" width=300>
+      <img src="./yolo12s_demo.gif">
       <br>
 </p>
 
-This example demonstrates how to perform inference of Ultralytics YOLO12 family detection models in C++ leveraging the Executorch backends:
+This example demonstrates how to perform inference of [Ultralytics YOLO12 family](https://docs.ultralytics.com/models/yolo12/) detection models in C++ leveraging the Executorch backends:
 - [OpenVINO](../../../backends/openvino/README.md)
 - [XNNPACK](../../../backends/xnnpack/README.md)
 
@@ -86,5 +86,7 @@ To get a full parameters description please use the following command:
 
 
 # Credits:
+
 Ultralytics examples: https://github.com/ultralytics/ultralytics/tree/main/examples
+
 Sample video: https://www.pexels.com/@shanu-1040189/

examples/models/yolo12/build.sh

@@ -15,9 +15,6 @@
 import executorch
 import numpy as np
 import torch
-from executorch.backends.openvino.partitioner import OpenvinoPartitioner
-from executorch.backends.openvino.quantizer import OpenVINOQuantizer
-from executorch.backends.openvino.quantizer.quantizer import QuantizationMode
 from executorch.backends.xnnpack.partition.xnnpack_partitioner import XnnpackPartitioner
 from executorch.backends.xnnpack.quantizer.xnnpack_quantizer import (
     get_symmetric_quantization_config,
@@ -80,7 +77,11 @@ def lower_to_openvino(
     subset_size: int,
     quantize: bool,
 ) -> ExecutorchProgramManager:
+    # Import openvino locally to avoid nncf side-effects
     import nncf.torch
+    from executorch.backends.openvino.partitioner import OpenvinoPartitioner
+    from executorch.backends.openvino.quantizer import OpenVINOQuantizer
+    from executorch.backends.openvino.quantizer.quantizer import QuantizationMode
     from nncf.experimental.torch.fx import quantize_pt2e
 
     with nncf.torch.disable_patching():

examples/models/yolo12/export_and_quantize.py

@@ -57,12 +57,12 @@ int main(int argc, char** argv) {
 
   ET_CHECK_MSG(
       error == Error::Ok,
-      "Loading of the model failed with status 0x%",
+      "Loading of the model failed with status 0x%" PRIx32,
       (uint32_t)error);
   error = yolo_module.load_forward();
   ET_CHECK_MSG(
       error == Error::Ok,
-      "Loading of the forward method failed with status 0x%",
+      "Loading of the forward method failed with status 0x%" PRIx32,
       (uint32_t)error);
 
   const auto model_input_shape =