Export network to ONNX model format
This function requires the Deep Learning Toolbox Converter for ONNX Model Format support package. If this support package is not installed, then the function provides a download link.
Load a pretrained SqueezeNet convolutional neural network. If Deep Learning
Toolbox Model for SqueezeNet Network is not installed, then
squeezenet function provides a download link.
net = squeezenet
net = DAGNetwork with properties: Layers: [68×1 nnet.cnn.layer.Layer] Connections: [75×2 table]
Export the network to an ONNX format file
squeezenet.onnx in the current folder. If the Deep Learning Toolbox Converter for ONNX Model Format support package is not installed, then the function provides a link to the
required support package in the Add-On Explorer. To install the support package, click
the link, and then click Install.
filename = 'squeezenet.onnx'; exportONNXNetwork(net,filename)
You can now import the
squeezenet.onnx file to another deep
learning framework that supports import from ONNX.
filename— Name of file
Name of file, specified as a character vector or string.
netName— Name of ONNX network
'Network'(default) | character vector | string
Name of ONNX network to store in the saved file, specified as a character vector or string.
exportONNXNetwork does not export settings or properties related to
network training such as training options, learning rate factors, or regularization
If the network that you want to export contains a layer that the ONNX format does not support, then
exportONNXNetwork saves a placeholder ONNX operator in place of the unsupported layer and returns a warning. It
is not possible to import the exported ONNX model to other deep learning