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authorNarumol Prangnawarat <narumol.prangnawarat@arm.com>2020-05-25 14:44:46 +0100
committerJan Eilers <jan.eilers@arm.com>2020-05-26 13:56:40 +0100
commitedcd7417c2bddc1d9155fda86f078b11583c4b2a (patch)
treee992daf0e68f765ea09512b1e9acab6a0025b3fb /src/armnnTfParser/TensorFlowSupport.md
parent68d827f1e433664c05fe03b91891b268b012a708 (diff)
downloadarmnn-edcd7417c2bddc1d9155fda86f078b11583c4b2a.tar.gz
IVGCVSW-4792 Update armnn readme and support files
* Add TPIP used by Arm NN * Add SqueezeNet to CaffeSupport.md * Add ResNet v2 50 to TensorFlowSupport.md * Update tested networks in TensorFlowLiteSupported.md Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com> Change-Id: I15927ea600a3dfffee082933d32f235f3940730e
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+++ b/src/armnnTfParser/TensorFlowSupport.md
@@ -189,4 +189,6 @@ Arm tests these operators with the following TensorFlow fp32 neural networks:
* inception_v3. The Arm NN SDK only supports the official inception_v3 transformed model. See the TensorFlow documentation on [preparing models for mobile deployment](https://www.tensorflow.org/mobile/prepare_models) for more information on how to transform the inception_v3 network.
+* ResNet v2 50 implementation from the [TF Slim model zoo](https://github.com/tensorflow/models/tree/master/research/slim)
+
More machine learning operators will be supported in future releases.