openvino/openvino-onnx-ml-defines.patch

Index: openvino-2024.0.0/thirdparty/dependencies.cmake
===================================================================
--- openvino-2024.0.0.orig/thirdparty/dependencies.cmake
+++ openvino-2024.0.0/thirdparty/dependencies.cmake
@@ -482,6 +482,7 @@ if(ENABLE_OV_ONNX_FRONTEND)
 
     if(ONNX_FOUND)
         # conan and vcpkg create imported targets 'onnx' and 'onnx_proto'
+        add_compile_definitions(ONNX_ML=1)
     else()
         add_subdirectory(thirdparty/onnx)
     endif()
- openvino-onnx-ml-defines.patch and openvino-remove-npu-compile-tool.patchhas been removed as it is no longer needed in this version. - Update to 2024.4.0 - Summary of major features and improvements   * OpenVINO 2024.6 release includes updates for enhanced stability and improved LLM performance. * Introduced support for Intel® Arc™ B-Series Graphics (formerly known as Battlemage). * Implemented optimizations to improve the inference time and LLM performance on NPUs. * Improved LLM performance with GenAI API optimizations and bug fixes. - Support Change and Deprecation Notices * Using deprecated features and components is not advised. They are available to enable a smooth transition to new solutions and will be discontinued in the future. To keep using discontinued features, you will have to revert to the last LTS OpenVINO version supporting them. For more details, refer to the OpenVINO Legacy Features and Components page. * Discontinued in 2024.0: + Runtime components: - Intel® Gaussian & Neural Accelerator (Intel® GNA).. Consider using the Neural Processing Unit (NPU) for low-powered systems like Intel® Core™ Ultra or 14th generation and beyond. - OpenVINO C++/C/Python 1.0 APIs (see 2023.3 API transition guide for reference). - All ONNX Frontend legacy API (known as ONNX_IMPORTER_API) - 'PerfomanceMode.UNDEFINED' property as part of the OpenVINO Python API + Tools: - Deployment Manager. See installation and deployment guides for current distribution options. - Accuracy Checker. - Post-Training Optimization Tool (POT). Neural Network Compression Framework (NNCF) should be used instead. - A Git patch for NNCF integration with  huggingface/transformers. The recommended approach is to use huggingface/optimum-intel for applying NNCF optimization on top of models from Hugging Face. - Support for Apache MXNet, Caffe, and Kaldi model formats. Conversion to ONNX may be used as a solution. * Deprecated and to be removed in the future: + The macOS x86_64 debug bins will no longer be provided with the OpenVINO toolkit, starting with OpenVINO 2024.5. + Python 3.8 is no longer supported, starting with OpenVINO 2024.5. + As MxNet doesn’t support Python version higher than 3.8, according to the MxNet PyPI project, it is no longer supported by OpenVINO, either. + Discrete Keem Bay support is no longer supported, starting with OpenVINO 2024.5. + Support for discrete devices (formerly codenamed Raptor Lake) is no longer available for NPU. OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/openvino?expand=0&rev=23 2025-01-07 18:14:03 +01:00			`Index: openvino-2024.0.0/thirdparty/dependencies.cmake`
			`===================================================================`
			`--- openvino-2024.0.0.orig/thirdparty/dependencies.cmake`
			`+++ openvino-2024.0.0/thirdparty/dependencies.cmake`
			`@@ -482,6 +482,7 @@ if(ENABLE_OV_ONNX_FRONTEND)`

			`if(ONNX_FOUND)`
			`# conan and vcpkg create imported targets 'onnx' and 'onnx_proto'`
			`+ add_compile_definitions(ONNX_ML=1)`
			`else()`
			`add_subdirectory(thirdparty/onnx)`
			`endif()`