A release candidate package for TensorRT 3.0 and cuDNN 7.0 is now available for Jetson TX1/TX2. Intended to be installed on top of an existing JetPack 3.1 installation, the TensorRT 3.0 RC provides the latest performance improvements and features:
Please see section 2.3.1.2 (Caffe Python Workflow) TensorRT 3 User Guide (included in download) for docs and code examples of using the Python API.
Note that the Python API is currently supported on x86-only due to some .whl dependencies, see this item from the updated Release Notes:
TensorFlow UFF models can still be imported on ARM platforms from C++ using the NvUffParser.h API.
Does the Python API for TensorRT 3.0 RC gives us the flexibility to modify tensors? More specifically, are there functions which allow us to permute/reshape tensors similar to the following functions on pyTorch?
[url]torch.Tensor — PyTorch master documentation
[url]torch.Tensor — PyTorch master documentation
I wasn’t able to find them in the current documentation.
Thanks for your reply.
Unfortunately, there is no documentation about using the shuffle layer in python/doc/python3.5. It just says that the layer can be used to reshape or transpose data.
Is there any example/documentation which I can refer to?
The Jetpack needs to be installed on the host (amd64). After that connect the Jetson board to the host and the Jetpack will install all the required software on the Jetson.