How to get the output_data using VART API in PYNQ-DPU about dpu-pynq

[skalade]

The model in the example already outputs the final fully connected layer output values before softmax and its shape is (1, 10). Softmax is calculated as a separate python function.

If you are having issues training custom models on the Vitis AI docker then Vitis AI would be a better place to find support. I would also investigate the Vitis AI Tutorials as there are plenty of training examples of more complex architectures.

Thanks
Shawn

[Afef00]

Hello,
Thanks for the clarification!
Actually, I was trying to build a hybrid CNN -SVM model, where I use the output values of the final fully connected layer as inputs for SVM classifier.
The problem is that in the software validation of this approach the output shape of this layer was (1,128).
I tried the following to get the output values of the final fully connected layer

getFeature = K.function([model.layers[0].input, K.learning_phase()],
                        [model.layers[4].output])
exTrain = getFeature([x_train, 0])[0]

The output shape of extrain was (1,128). That's why am confused
Thanks

[skalade]

Closing this out as it has been a few weeks without activity and it seems more of a general ML/tensorflow issue, than to do with DPU-PYNQ.