I’m working on autonomous cars in a university setting and we would like to create a lane detection model in Tensorflow (1.15.0 - Python API) that is compatible with the native TensorRT API so we can create an optimized C++ inference engine. I checked the support matrix you provided for the TensorRT version we use (22.214.171.124) here to see what TF operations are supported:
My questions would be:
1 .How do I know what TensorFlow module these listed operations belong to? Do I have to use the tf.nn module or perhaps is it okay to use the tf.keras module (we were working with this) ?
- Why Dense layer is not listed in the supported operations? I’m asking because it is quite common to use it in deep networks one way or another and I can’t see how can I create the TF network without it.
Thanks in advance!
TensorRT Version: 126.96.36.199.
GPU Type: GeForce RTX 2080 Ti (3x)
Nvidia Driver Version: 450.51.05
CUDA Version: 10.0
CUDNN Version: 7.6.5
Operating System + Version: Ubuntu 18.04
Python Version (if applicable): 3.6.9
TensorFlow Version (if applicable): 1.15.0
PyTorch Version (if applicable): -
Baremetal or Container (if container which image + tag): -