Supported neural networks and runtimes

Supported Neural Networks and formats

Here is a list of neural networks and runtimes that run on the devices DSP that provides adequate performance for real time inferencing.

Network Topology Verified Formats Support for DSP
AlexNet Caffe2 Y
DeepLabV3+ Tensorflow Partial
GoogleNet Caffe2 Y
Inception-V3 Tensorflow, Caffe Y
Inception-V3 2016 Tensorflow Y
Inception-ResNet v2 Tensorflow Y
Inception-V4 Caffe Y
MobileNet TensorFlow *
MobileNet-v2 TensorFlow, Caffe *
MobileNet-SSD TensorFlow, Caffe *
ResNet-50 TensorFlow Y
ResNet-101 Caffe Y
ShuffleNet TensorFlow Y
SqueezeNet TensorFlow Y
VGG-16 TensorFlow Y
VGG-19 Caffe Y

*this network topology requires changes to preserve accuracy when quantized. Instructions for topology modification are available from Qualcomm.

ONNX support

ONNX support is currently experimental and most models will run on the CPU, rather than be offloaded to the DSP.

ONNX models from the following networks can be converted for use with the Vision AI DevKit:

  • bvlc_alexnet
  • bvlc_googlenet
  • bvlc_reference_caffenet
  • bvlc_reference_rcnn_ilsvrc13
  • densenet121
  • inception_v1
  • inception_v2
  • resnet_50
  • vgg16
  • vgg19