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| author | Cathal Corbett <cathal.corbett@arm.com> | 2022-09-01 11:34:37 +0100 |
|---|---|---|
| committer | Cathal Corbett <cathal.corbett@arm.com> | 2022-12-12 12:38:15 +0000 |
| commit | 5383767a7a759c867235ab66bd71f88281e3bd06 (patch) | |
| tree | 5704c33171d39dda9e4428c953e2efdd62ead656 /InstallationViaAptRepository.md | |
| parent | a98e79a709f7c29728e1fc79c21ba5265993b8b6 (diff) | |
| download | armnn-5383767a7a759c867235ab66bd71f88281e3bd06.tar.gz | |
Optimize the calling of IsLayerSupported().
* Done as part of 22.11/23.02 innovation days.
* IsLayerSupported() is called in model prepare (delegate, android-nn-driver and shim/support_library)
and again in ArmNN once model otimization is performed.
* From calling IsLayerSupported() the first time, we should know that the layers are supported
and what backend they are supported on.
* Solution is to set the BackendId of the IConnectableLayer when IsLayerSupported() is called the first time,
* In the Optimize() function we then check if the backend is set. If so, we do not call IsLayerSupported() again.
* In the case a layer that is supported gets optimized, then the BackendId of that layer get set to "Unknown"
for the new optimized layer and IsLayerSupported() will get called on the newly optimized layer.
* Includes bug fix IVGCVSW-7213 for Android Mean FP16 CpuAcc tests. Also related to bug IVGCVSW-7211.
Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: I7a7820d0cdb079ffb5a3a2e0c44e252f652df53b
Diffstat (limited to 'InstallationViaAptRepository.md')
| -rw-r--r-- | InstallationViaAptRepository.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/InstallationViaAptRepository.md b/InstallationViaAptRepository.md index 037e5cc7f1..fac714f2a6 100644 --- a/InstallationViaAptRepository.md +++ b/InstallationViaAptRepository.md @@ -117,7 +117,7 @@ The easiest way to install all of the available packages for your systems archit sudo apt-get install -y python3-pyarmnn armnn-latest-all # Verify installation via python: python3 -c "import pyarmnn as ann;print(ann.GetVersion())" - # Returns '{ARMNN_MAJOR_VERSION}.0.0' e.g. 31.0.0 + # Returns '{ARMNN_MAJOR_VERSION}.0.0' e.g. 32.0.0 ``` This will install PyArmNN and the three backends for Neon (CpuAcc), OpenCL (GpuAcc) and our Reference Backend. It will also install their dependencies including the arm-compute-library package along with the Tensorflow Lite Parser |