diff options
Diffstat (limited to 'src')
-rw-r--r-- | src/armnnCaffeParser/CaffeSupport.md | 1 | ||||
-rw-r--r-- | src/armnnTfLiteParser/TensorFlowLiteSupport.md | 16 | ||||
-rw-r--r-- | src/armnnTfParser/TensorFlowSupport.md | 2 |
3 files changed, 19 insertions, 0 deletions
diff --git a/src/armnnCaffeParser/CaffeSupport.md b/src/armnnCaffeParser/CaffeSupport.md index 5d998937de..ab0d3a4ab8 100644 --- a/src/armnnCaffeParser/CaffeSupport.md +++ b/src/armnnCaffeParser/CaffeSupport.md @@ -11,6 +11,7 @@ Although some other neural networks might work, Arm tests the Arm NN SDK with Ca - Yolov1_tiny. - Lenet. - MobileNetv1. +- SqueezeNet v1.0 and SqueezeNet v1.1 The Arm NN SDK supports the following machine learning layers for Caffe networks: diff --git a/src/armnnTfLiteParser/TensorFlowLiteSupport.md b/src/armnnTfLiteParser/TensorFlowLiteSupport.md index 88db0f07b2..f7828628cb 100644 --- a/src/armnnTfLiteParser/TensorFlowLiteSupport.md +++ b/src/armnnTfLiteParser/TensorFlowLiteSupport.md @@ -94,4 +94,20 @@ Arm tested these operators with the following TensorFlow Lite neural network: * DeepSpeaker +* [DeepLab v3+](https://www.tensorflow.org/lite/models/segmentation/overview) + +* FSRCNN + +* RDN converted from [TensorFlow model](https://github.com/hengchuan/RDN-TensorFlow) + +* Quantized RDN (CpuRef) + +* [Quantized Inception v3](http://download.tensorflow.org/models/tflite_11_05_08/inception_v3_quant.tgz) + +* [Quantized Inception v4](http://download.tensorflow.org/models/inception_v4_299_quant_20181026.tgz) (CpuRef) + +* Quantized ResNet v2 50 (CpuRef) + +* Quantized Yolo v3 (CpuRef) + More machine learning operators will be supported in future releases. diff --git a/src/armnnTfParser/TensorFlowSupport.md b/src/armnnTfParser/TensorFlowSupport.md index 65839e2e57..2dc54b5f85 100644 --- a/src/armnnTfParser/TensorFlowSupport.md +++ 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. |