armnn-22.02-bp154.1.22

-  Update to 22.02:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v22.02
  * Add libarmnnTestUtils

- Update to 21.11:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v21.11
  * Main changes:
  - New capabilities and improve performance
  - ABI/API Changes
    The following front-end API changes have occurred during the
    implementation of 21.11 that users should be aware of before
    upgrading. Due to these changes we have bumped our ARMNN_VERSION
    to 27.0.0, the Delegate to 25.0.0 and also bumping
    our Parsers to 24.3.0 following Semantic Versioning guidelines.
- Drop upstream patches:
  * 96beb97.diff
  * febc20f.diff
  * e118e04.diff
  * 0011-update-doctest-for-glibc2.34.patch

- Add upstream patch to fix stringop-overread error:
  * e118e04.diff

- Add upstream patch to fix uninitialized var error:
  * febc20f.diff
- Remove most -Wno-error* flags which are not needed anymore

- Add 0011-update-doctest-for-glibc2.34.patch: Update doctest to
  version 2.4.6 to allow Arm NN to build with glibc 2.34; patch
  taken from upstream commits 13d2e0d and 4ec6d42and rebased for
  current version.

- Update to 21.08:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v21.08
  * Main changes:
  - new capabilities and improve performance:
  * Added the ability to import protected DMA Buffers and
    allow Arm NN to run inferences that are in Protected GPU Memory.
    As well as providing Custom Memory Allocator which supports
    importing malloc, Dma_buf and protected Dma buffers.
  * Users with multi core NPUs has been given the ability to pin
    inferences to selected cores giving them the ability to balance
    parallel workloads across the NPU and increase throughput.
  * Boost has been completely removed from the code base making
    Arm NN easier to integrate into other software stacks.
  * Added support for non-constant weights and biases on
    FullyConnected which lay the groundwork for supporting more models.
  * More operators supported on Arm NN, TfLite Parser, TfLite
    Delegate and Android NNAPI driver.
- Drop upstream patch:
  * armnn-fix-include.patch

- Add '-Wno-error=stringop-overread' to workaround build error
  with GCC11 with openCL enabled

- Add '-Wno-error=uninitialized -Wno-error=array-bounds' to
  workaround build issues with GCC11 - https://github.com/ARM-software/armnn/issues/548

- Fix libarmnnOnnxParser version

- Update to 21.05:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v21.05
  * Main changes:
  - new capabilities to allow users attain higher performance by:
  * Making the Arm NN Core thread safe opening the possibility of
    running multiple inferences on the same model in parallel
    software threads.
  * Allowing graphs on the GPU backend import their input and
    output buffers either from correctly aligned main memory or
    from kernel memory exposed as a dma_buf, thus reducing memory
    usage and saving the time involved in copying data into and
    out of the GPU memory space.
  - In addition to this, support was added to allow the MobileBERT
    network to be parsed and run.
  - Finally three deprecated components: the Tensorflow Parser,
    the Caffe Parser and the Arm NN Quantizer tool, were removed
- Add patch to fix include path:
  * armnn-fix-include.patch
- Disable armnn-extratests as it fails to build with current version

- Update to 21.02:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v21.02
- Drop upstream patch:
  * c5c40fe.diff

- Fix instalaltion of cmake files with an upstream patch:
  * c5c40fe.diff

- Backport patch to fix tflite parser when built against
  tensorflow 2.4:
  * 96beb97.diff

- Update to 20.11:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v20.11
- Refresh patch to handle boost::variant to mapbox::util::variant update:
  * 0006-armnn-mobilenet-test-example.patch

- Add python support, disabled for now as it does not install
  files atm

- Package libtimelineDecoderJson

- Update to 20.08:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v20.08
- Refresh patch:
  * 0005-add-armnn-mobilenet-test-example.patch
- Drop upstream patch:
  * armnn-fix-catch.patch
- Disable ONNX on Tumbleweed since there is a compatibility issue
  with ONNX 1.7.0, see: https://github.com/ARM-software/armnn/issues/419

- Build only where ComputeLibrary is built:
  aarch64 armv7 and x86_64

- Unify Leap/SLE options
- Update to 20.05:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v20.05
- Drop upstream patch:
  * armnn-enable-use-of-arm-compute-shared-library.patch
- Refresh patch:
  * 0003-add-more-test-command-line-arguments.patch
- Add new patch to fix build with gcc10:
  * armnn-fix-catch.patch
- Package new libtimelineDecode and libarmnnBasePipeServer

- Apply boost link fixes only for armnn_extra_tests
- Apply patches for armnn_extra_tests only when
  armnn_extra_tests is built

- Disable RPATH to fix build on Leap15.2/SLE15SP2

- Add '-Wno-error=deprecated-declarations' to fix build with latest
  protobuf 3.11.x (Tumbleweed)
  https://github.com/ARM-software/armnn/issues/366
- Use python-onnx package instead of python-onnx-devel, since it
  is now a single package.

- Fix build on Leap 15.2

- Update to 20.02:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v20.02
  * Drop upstream patch:
  - armnn-fix_include.patch
  * Refresh patch:
  - 0006-armnn-mobilenet-test-example.patch
  * Replace downstream patch:
  - 0007-enable-use-of-arm-compute-shared-library.patch
    by upstream patch:
  - armnn-enable-use-of-arm-compute-shared-library.patch
  * Add 'vim' as BuildRequires since it needs 'xxd' tool
- Use TensorFlow 2 also on Leap 15.2 / SLE15SP2

- Use Tensorflow 2.x only for Tumbleweed, as TensorFlow2 is not
  available in Leap 15.2
- Skip some tests if TensorFlow < 1.14 is used

- Enable ONNX on Leap 15.2

- Use tensorflow2 as armnn 19.11 now requires TensorFlow >= 1.14

- Disable ArmnnConverter and ArmnnQuantizer packaging by default
  as it requires libQuantizer.so to be packaged, which is not yet

- Package ArmnnConverter and ArmnnQuantizer

- ExcludeArch %ix86: Parts of the build deps (tensorflow/bazel) are
  not supported on ix86.

- Update to 19.11:
  * Changelog: https://github.com/ARM-software/armnn/releases/tag/v19.11
- Remove upstreamed patches:
  * armnn-generate-versioned-library.patch
  * armnn-fix_boost.patch
  * armnn-fix_arm32_dep.patch
  * armnn-fix_arm32.patch
- Add patch to fix include:
  * armnn-fix_include.patch

- tensorflow-devel package now includes *.pb.* files, so
  remove TensorFlow parser build workaround:
  * armnn-fix_tensorflow_link.patch

- Add a conflict between armnn-extratests and armnn-opencl-extratests

- Add a conflict between armnn-devel and armnn-opencl-devel

- Enable ONNX for Tumbleweed

- Add downstream ArmnnExamples in a separate '-extratests' package
  with patches:
  * 0003-add-more-test-command-line-arguments.patch
  * 0005-add-armnn-mobilenet-test-example.patch
  * 0006-armnn-mobilenet-test-example.patch
  * 0007-enable-use-of-arm-compute-shared-library.patch
  * 0009-command-line-options-for-video-port-selection.patch
  * 0010-armnnexamples-update-for-19.08-modifications.patch
- Fix build when extratests are disabled
  * armnn-fix_find_opencv.patch

- Replace patch with an upstreamable version:
  * armnn-generate-versioned-library.patch

- Add ONNX Parser support (disabled by default as there is no
  official ONNX package yet)

- Re-enable Tensorflow on Tumbleweed as boo#1151150 is now fixed

- Update _constraints