The instructions below have been tested on a Jetson TX1 board with JetPack 4.2.2 installed via the NVIDIA SDK Manager.
When installing a Jetpack via the NVIDIA SDK Manager, tick the TensorFlow option. For JetPack 4.2.2, this installs TensorFlow 1.14.0.
$ ck detect soft:lib.tensorflow --full_path=/usr/local/lib/python3.6/dist-packages/tensorflow/__init__.py
$ ck install package --tags=lib,python-package,onnx,from-source
$ ck install package --tags=lib,python-package,tf2onnx --force_version=1.5.1
NB: Both 1.5.2. and 1.5.3 can be installed but fail to convert ResNet to ONNX on TX1.
$ ck install package --tags=model,resnet,onnx,converted-from-tf
When converting an ONNX model to TensorRT, you can select the numerical data type (fp32
or fp16
)
and the maximum batch size (currently 1 .. 20
).
precision=fp32
, max_batch_size=1
$ ck install package --tags=model,resnet,tensorrt,converted-from-onnx
precision=fp16
, max_batch_size=1
$ ck install package --tags=model,resnet,tensorrt,converted-from-onnx,fp16
precision=fp32
, max_batch_size=2
$ ck install package --tags=model,resnet,tensorrt,converted-from-onnx,fp32,maxbatch.2
precision=fp16
, max_batch_size=2
$ ck install package --tags=model,resnet,tensorrt,converted-from-onnx,fp16,maxbatch.2