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RapidAI / RapidOCR

📄 Awesome OCR multiple programing languages toolkits based on ONNXRuntime, OpenVINO and PaddlePaddle.
https://rapidai.github.io/RapidOCRDocs
Apache License 2.0
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chore(deps): update openvino requirement from <=2024.0.0,>=2022.2.0 to >=2022.2.0,<=2024.4.0 in /python #236

Closed dependabot[bot] closed 1 month ago

dependabot[bot] commented 1 month ago

Updates the requirements on openvino to permit the latest version.

Release notes

Sourced from openvino's releases.

2024.4.0

Summary of major features and improvements  

  • More Gen AI coverage and framework integrations to minimize code changes

    • Support for GLM-4-9B Chat, MiniCPM-1B, Llama 3 and 3.1, Phi-3-Mini, Phi-3-Medium and YOLOX-s models.
    • Noteworthy notebooks added: Florence-2, NuExtract-tiny Structure Extraction, Flux.1 Image Generation, PixArt-α: Photorealistic Text-to-Image Synthesis, and Phi-3-Vision Visual Language Assistant.

  • Broader Large Language Model (LLM) support and more model compression techniques.

    • OpenVINO™ runtime optimized for Intel® Xe Matrix Extensions (Intel® XMX) systolic arrays on built-in GPUs for efficient matrix multiplication resulting in significant LLM performance boost with improved 1st and 2nd token latency, as well as a smaller memory footprint on Intel® Core™ Ultra Processors (Series 2).
    • Memory sharing enabled for NPUs on Intel® Core™ Ultra Processors (Series 2) for efficient pipeline integration without memory copy overhead.
    • Addition of the PagedAttention feature for discrete GPUs* enables a significant boost in throughput for parallel inferencing when serving LLMs on Intel® Arc™ Graphics or Intel® Data Center GPU Flex Series.

  • More portability and performance to run AI at the edge, in the cloud, or locally.

    • Support for Intel® Core Ultra Processors Series 2 (formerly codenamed Lunar Lake) on Windows.
    • OpenVINO™ Model Server now comes with production-quality support for OpenAI-compatible API which enables significantly higher throughput for parallel inferencing on Intel® Xeon® processors when serving LLMs to many concurrent users.
    • Improved performance and memory consumption with prefix caching, KV cache compression, and other optimizations for serving LLMs using OpenVINO™ Model Server.
    • Support for Python 3.12.
    • Support for Red Hat Enterprise Linux (RHEL) version 9

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:
  • 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 now considered deprecated, and it will not be available beyond the 2024.4 OpenVINO version.
    • dKMB support is now considered deprecated and will be fully removed with OpenVINO 2024.5
    • Intel® Streaming SIMD Extensions (Intel® SSE) will be supported in source code form, but not enabled in the binary package by default, starting with OpenVINO 2025.0
    • The openvino-nightly PyPI module will soon be discontinued. End-users should proceed with the Simple PyPI nightly repo instead. More information in Release Policy.
    • The OpenVINO™ Development Tools package (pip install openvino-dev) will be removed from installation options and distribution channels beginning with OpenVINO 2025.0.
    • Model Optimizer will be discontinued with OpenVINO 2025.0. Consider using the new conversion methods instead. For more details, see the model conversion transition guide.
    • OpenVINO property Affinity API will be discontinued with OpenVINO 2025.0. It will be replaced with CPU binding configurations (ov::hint::enable_cpu_pinning).
    • OpenVINO Model Server components:
      • “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.
    • A number of notebooks have been deprecated. For an up-to-date listing of available notebooks, refer to the OpenVINO™ Notebook index (openvinotoolkit.github.io).

You can find OpenVINO™ toolkit 2024.4 release here:

... (truncated)

Commits
  • c3152d3 [GPU] Fix lack of support for 3D (and smaller) shapes in TransposeFusion pass...
  • 8c9d4be [CPU] Add interface to release compiled model internal memory (#26390)
  • ad3f51b [CPU] fix QKVProjection fake-matching for accuracy with bert models (#26417)
  • 0bfa578 [GPU] Disable transpose fusion in case of no transpose found on both branches...
  • b34295c Change log level from error to warning if backend is not found (#26418)
  • a9234a9 [intel-npu] Additional documentation for NPU_MAX_TILES property's usage (#26385)
  • 04e68ee Disabled LTO for gcc older than 9.0 (#26330) (#26399)
  • b543ebb [GPU] out-of-bound access from convolution kernel (#26377)
  • df65664 [NPU] Fix coverity issue (#26373)
  • 63923c7 [GPU] Fix accuracy issue of qwen-2 model (#26389)
  • Additional commits viewable in compare view


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dependabot[bot] commented 1 month ago

OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version. You can also ignore all major, minor, or patch releases for a dependency by adding an ignore condition with the desired update_types to your config file.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.

SWHL commented 1 month ago

经过尝试，openvino>2024.0.0,<=2024.4.0推理会过不了单元测试