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diff --git a/src/armnnCaffeParser/CaffeSupport.md b/src/armnnCaffeParser/CaffeSupport.md new file mode 100644 index 0000000000..e7724800f6 --- /dev/null +++ b/src/armnnCaffeParser/CaffeSupport.md @@ -0,0 +1,31 @@ +#Caffe layers supported by the Arm NN SDK +This reference guide provides a list of Caffe layers the Arm NN SDK currently supports. + +Although some other neural networks might work, Arm tests the Arm NN SDK with Caffe implementations of the following neural networks: + +- AlexNet. +- Cifar10. +- Inception-BN. +- Resnet_50, Resnet_101 and Resnet_152. +- VGG_CNN_S, VGG_16 and VGG_19. +- Yolov1_tiny. +- Lenet. +- MobileNetv1. + +The Arm NN SDK supports the following machine learning layers for Caffe networks: + + +- BatchNorm, in inference mode. +- Convolution, excluding the Dilation Size, Weight Filler, Bias Filler, Engine, Force nd_im2col, and Axis parameters. +- Eltwise, excluding the coeff parameter. +- Inner Product, excluding the Weight Filler, Bias Filler, Engine, and Axis parameters. +- Input. +- LRN, excluding the Engine parameter. +- Pooling, excluding the Stochastic Pooling and Engine parameters. +- ReLU. +- Scale. +- Softmax, excluding the Axis and Engine parameters. +- Split. +- Dropout, in inference mode. + +More machine learning layers will be supported in future releases.
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