I have tried to create a TensorRT model using DLA and GPU on Xavier with JetPack 4.5.1, but I have obtained an error. The layer in which I have the problem is a Conv2D that is connected with a Reshape Layer (Lambda). Is there any solution for this problem?
I include two images, the first one with the error and the second shows the summary of the model.
If yes, could you share the detailed input/output dimension of the reshape layer?
There is a similar issue related to the DLA INT8 mode.
And the corresponding fix will be available in the upcoming release:
Yes, my model works well in TensorRT GPU mode. The goal of the reshape layer is to store temporary information in four dimensions. The input dimension is (None, 25, 60, 60, 1) and the output dimension is (None, 60, 60, 1). This way, we move the temporal information to the batch dimension.
A solution could be to choose to map some layers in DLA and others in GPU, but I don’t find any information. Is there any example or way to do it?
Have you verified the output to see if it is correct?
Based on our document, we don’t support cross batch reshaping in both GPU and DLA.
It might work if the reshaping behavior just meets the cross-batch version.
But it’s recommended to double-check the correctness first.