When importing a pretrained network from a third-party framework that results in an uninitialized network, you need to initialize the network. See the examples on each function's documentation page on how to do this:
- importNetworkFromONNX: Import ONNX Network and Initialize
- importNetworkFromTensorFlow: Import and Initialize TensorFlow Network
- importNetworkFromPyTorch: Import Network from PyTorch and Initialize
Considerations for "importNetworkFromONNX":
For "importNetworkFromONNX", a Custom Input Layer is added if the input dimensions in the ONNX model are unknown. Try to apply "InputDataFormats" when importing the ONNX model:
By specifying InputDataFormats, you avoid the generation of the custom input layer, and MATLAB may be able to import more Deep Learning Toolbox layers instead of custom layers:
>> net = importNetworkFromONNX('model.onnx','InputDataFormats','BC');
>> net.Layers
ans =
10×1 Layer array with layers:
1 'input' Feature Input 4 features
2 'sequential_hidden1_4' Fully Connected 10 fully connected layer
3 'sequential_hidden1_2' Scaling Scaling
4 'sequential_hidden1_5' ReLU ReLU
5 'sequential_hidden2_4' Fully Connected 5 fully connected layer
6 'sequential_hidden2_2' Scaling Scaling
7 'sequential_hidden2_5' ReLU ReLU
8 'sequential_output__3' Fully Connected 1 fully connected layer
9 'sequential_output__1' Scaling Scaling
10 'outputOutput' Custom output ('CB') See the OutputInformation property to find the output dimension ordering that is produced by this layer.
>> net = importNetworkFromONNX('model.onnx')
Warning: Returning an uninitialized dlnetwork because some input layers have unknown data formats or undetermined image sizes. Initialize the network by passing example input data to the initialize object function.
>> net.Layers
ans =
3×1 Layer array with layers:
1 'input' Custom input ('UU') See the InputInformation property to find the required input dimension ordering for this layer.
2 'MatMul_To_AddLayer1000' model_keras.MatMul_To_AddLayer1000 model_keras.MatMul_To_AddLayer1000
3 'outputOutput' Custom output ('UU') See the OutputInformation property to find the output dimension ordering that is produced by this layer.
>> net.Layers(1).InputInformation
ans =
"Layer input must be a labeled dlarray with the dimension order shown in the ONNX model file.
You must pass the size:
(unk__6, 1)
The dlarray must have a format string consisting of one 'U' for each dimension: 'dlarray(data, 'UU')'"
When you inspect the Custom Input Layer's InputInformation using "net.Layers(1).InputInformation", placeholders like "unk", "unk__6", or "-1" may appear. If "InputDataFormats" can't be applied, you can try to manually initialize the network based on the InputInformation:
For (unk__6, 1), try:
net = net.initialize(dlarray(single(1),"U"));
For (unk__6, 4), try:
net = net.initialize(dlarray(ones([1,4],'single'),"UU"));
