Files
openvino/openvino-fix-build-sample-path.patch
Alessandro de Oliveira Faria ccf8e5ee70 Summary of major features and improvements
- More GenAI coverage and framework integrations to minimize code 
  changes
  * New models supported on CPUs & GPUs: Phi-4, 
    Mistral-7B-Instruct-v0.3, SD-XL Inpainting 0.1, Stable 
    Diffusion 3.5 Large Turbo, Phi-4-reasoning, Qwen3, and 
    Qwen2.5-VL-3B-Instruct. Mistral 7B Instruct v0.3 is also 
    supported on NPUs.
  * Preview: OpenVINO ™ GenAI introduces a text-to-speech 
    pipeline for the SpeechT5 TTS model, while the new RAG 
    backend offers developers a simplified API that delivers 
    reduced memory usage and improved performance.
  * Preview: OpenVINO™ GenAI offers a GGUF Reader for seamless 
    integration of llama.cpp based LLMs, with Python and C++ 
    pipelines that load GGUF models, build OpenVINO graphs, 
    and run GPU inference on-the-fly. Validated for popular models:
    DeepSeek-R1-Distill-Qwen (1.5B, 7B), Qwen2.5 Instruct 
    (1.5B, 3B, 7B) & llama-3.2 Instruct (1B, 3B, 8B).
- Broader LLM model support and more model compression 
  techniques
  * Further optimization of LoRA adapters in OpenVINO GenAI
    for improved LLM, VLM, and text-to-image model performance
    on built-in GPUs. Developers can use LoRA adapters to 
    quickly customize models for specialized tasks.
  * KV cache compression for CPUs is enabled by default for 
    INT8, providing a reduced memory footprint while maintaining
    accuracy compared to FP16. Additionally, it delivers
    substantial memory savings for LLMs with INT4 support compared
    to INT8.
  * Optimizations for Intel® Core™ Ultra Processor Series 2 
    built-in GPUs and Intel® Arc™ B Series Graphics with the 
    Intel® XMX systolic platform to enhance the performance of
    VLM models and hybrid quantized image generation models, as 
    well as improve first-token latency for LLMs through dynamic
    quantization.
- More portability and performance to run AI at the edge, in the 
  cloud, or locally.
  * Enhanced Linux* support with the latest GPU driver for 
    built-in GPUs on Intel® Core™ Ultra Processor Series 2 
    (formerly codenamed Arrow Lake H).
  * Support for INT4 data-free weights compression for ONNX 
    models implemented in the Neural Network Compression 
    Framework (NNCF).
  * NPU support for FP16-NF4 precision on Intel® Core™ 200V 
    Series processors for models with up to 8B parameters is
    enabled through symmetrical and channel-wise quantization,
    improving accuracy while maintaining performance efficiency.
Support Change and Deprecation Notices
- Discontinued in 2025:
  * Runtime components:
    + The OpenVINO property of Affinity API is no longer 
      available. It has been replaced with CPU binding 
      configurations (ov::hint::enable_cpu_pinning).
    + The openvino-nightly PyPI module has been discontinued. 
      End-users should proceed with the Simple PyPI nightly repo
      instead. More information in Release Policy. The 
      openvino-nightly PyPI module has been discontinued. 
      End-users should proceed with the Simple PyPI nightly repo
      instead. More information in Release Policy.
  * Tools:
    + The OpenVINO™ Development Tools package (pip install 
      openvino-dev) is no longer available for OpenVINO releases
      in 2025.
    + Model Optimizer is no longer available. Consider using the
      new conversion methods instead. For more details, see the 
      model conversion transition guide.
    + Intel® Streaming SIMD Extensions (Intel® SSE) are currently
      not enabled in the binary package by default. They are 
      still supported in the source code form.
    + Legacy prefixes: l_, w_, and m_ have been removed from 
      OpenVINO archive names.
  * OpenVINO GenAI:
    + StreamerBase::put(int64_t token)
    + The Bool value for Callback streamer is no longer accepted.
      It must now return one of three values of StreamingStatus
      enum.
    + ChunkStreamerBase is deprecated. Use StreamerBase instead.
  * NNCF create_compressed_model() method is now deprecated. 
    nncf.quantize() method is recommended for 
    Quantization-Aware Training of PyTorch and TensorFlow models.
  * OpenVINO Model Server (OVMS) benchmark client in C++
    using TensorFlow Serving API.
- Deprecated and to be removed in the future:
  * Python 3.9 is now deprecated and will be unavailable after
    OpenVINO version 2025.4.
  * openvino.Type.undefined is now deprecated and will be removed
    with version 2026.0. openvino.Type.dynamic should be used 
    instead.
  * APT & YUM Repositories Restructure: Starting with release
    2025.1, users can switch to the new repository structure 
    for APT and YUM, which no longer uses year-based 
    subdirectories (like “2025”). The old (legacy) structure
    will still be available until 2026, when the change will 
    be finalized. Detailed instructions are available on the
    relevant documentation pages:
    + Installation guide - yum
    + Installation guide - apt
  * OpenCV binaries will be removed from Docker images in 2026.
  * Ubuntu 20.04 support will be deprecated in future OpenVINO
    releases due to the end of standard support.
  * “auto shape” and “auto batch size” (reshaping a model in
    runtime) will be removed in the future. OpenVINO’s dynamic
    shape models are recommended instead.
  * MacOS x86 is no longer recommended for use due to the 
    discontinuation of validation. Full support will be removed
    later in 2025.
  * The openvino namespace of the OpenVINO Python API has been
    redesigned, removing the nested openvino.runtime module. 
    The old namespace is now considered deprecated and will be
    discontinued in 2026.0.

OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/openvino?expand=0&rev=37
2025-06-24 04:28:58 +00:00

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Diff

diff -uNr openvino.orig/samples/cpp/build_samples.sh openvino/samples/cpp/build_samples.sh
--- openvino.orig/samples/cpp/build_samples.sh 2024-04-25 01:04:42.451868881 -0300
+++ openvino/samples/cpp/build_samples.sh 2024-04-25 01:05:04.678342617 -0300
@@ -59,7 +59,7 @@
printf "\nSetting environment variables for building samples...\n"
if [ -z "$INTEL_OPENVINO_DIR" ]; then
- if [[ "$SAMPLES_SOURCE_DIR" = "/usr/share/openvino"* ]]; then
+ if [[ "$SAMPLES_SOURCE_DIR" = "/usr/share/OpenVINO"* ]]; then
true
elif [ -e "$SAMPLES_SOURCE_DIR/../../setupvars.sh" ]; then
setupvars_path="$SAMPLES_SOURCE_DIR/../../setupvars.sh"