I am encountering an incompatibility on a specific operation when generating an engine with the trtexec command line. I would like to use the DLA as much as possible and not rely on the GPU fallback.
converting the shapes format with ".type( tensor.type(torch.int8)) " before the interpolation operation.
My configuration :
Pytorch (on host) : 1.13
Platform : Orin AGX Dev. kit
JetPack : 5.0.2
TensorRT : 8.4.0.1
CUDA : 11.4
Could you please help me to interpret the “Please explicitly use CAST operator in ONNX model or add an identity layer to convert INT32 to other types for DLA” message?
I have finally understood why the DLA did not layer not support the layer. It was my fault.
In the constraints DLA guide, I mixed up the scale and the output shape terms for the onnx equivalent resize layer. Therefore, the actual underlying scale factor could not be an integer in my case and the DLA constraints were not satisfied.
Replacing the torch.nn.Functional.interpolate(size= …) with the torch.nn.Upsample(scale_factor = …) solves the problem.