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author | Teresa Charlin <teresa.charlinreyes@arm.com> | 2020-11-20 13:08:42 +0000 |
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committer | Teresa Charlin <teresa.charlinreyes@arm.com> | 2020-11-24 09:44:45 +0000 |
commit | c6ac856be4f2d10f1d90d05dfd65885f380ee6af (patch) | |
tree | 807cbddeab0b0538a1499a1920e4e8891a3db782 /src | |
parent | 999d136c247e080d131398dba078f15a3e82ddf2 (diff) | |
download | armnn-c6ac856be4f2d10f1d90d05dfd65885f380ee6af.tar.gz |
IVGCVSW-5347 Update Readme for 20.11
* Adding delegate readme.md and TensorFlowLiteDelegateSupport.md
Change-Id: I1b8012440cf4cd6120902ad69c5b3a2a5e410d71
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Diffstat (limited to 'src')
-rw-r--r-- | src/armnnDeserializer/DeserializerSupport.md | 1 | ||||
-rw-r--r-- | src/armnnSerializer/SerializerSupport.md | 1 | ||||
-rw-r--r-- | src/armnnTfLiteParser/TensorFlowLiteSupport.md | 2 |
3 files changed, 4 insertions, 0 deletions
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md index 4e2ead41bc..2ff3a24503 100644 --- a/src/armnnDeserializer/DeserializerSupport.md +++ b/src/armnnDeserializer/DeserializerSupport.md @@ -29,6 +29,7 @@ The Arm NN SDK Deserialize parser currently supports the following layers: * Input * InstanceNormalization * L2Normalization +* Logical * LogSoftmax * Lstm * Maximum diff --git a/src/armnnSerializer/SerializerSupport.md b/src/armnnSerializer/SerializerSupport.md index 438335341a..67dc5d1596 100644 --- a/src/armnnSerializer/SerializerSupport.md +++ b/src/armnnSerializer/SerializerSupport.md @@ -28,6 +28,7 @@ The Arm NN SDK Serializer currently supports the following layers: * Input * InstanceNormalization * L2Normalization +* Logical * LogSoftmax * Lstm * Maximum diff --git a/src/armnnTfLiteParser/TensorFlowLiteSupport.md b/src/armnnTfLiteParser/TensorFlowLiteSupport.md index 9718b22798..faad3d0fa9 100644 --- a/src/armnnTfLiteParser/TensorFlowLiteSupport.md +++ b/src/armnnTfLiteParser/TensorFlowLiteSupport.md @@ -104,6 +104,8 @@ Arm tested these operators with the following TensorFlow Lite neural network: * FSRCNN +* EfficientNet-lite + * RDN converted from [TensorFlow model](https://github.com/hengchuan/RDN-TensorFlow) * Quantized RDN (CpuRef) |