Description
I plan to deploy tensorrt OSS 7.1 on both of my jetson tx2 platform and jetson NX, I follow the instructions on website:
GitHub - NVIDIA/TensorRT at release/7.1,
git clone -b master GitHub - NVIDIA/TensorRT: TensorRT is a C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators. TensorRT
cd TensorRT
git submodule update --init --recursive
export TRT_SOURCE=pwd
When I try “git submodule update --init --recursive” , It always give me:
Submodule path ‘parsers/onnx’: checked out ‘84b5be1d6fc03564f2c0dba85a2ee75bad242c2e’
Cloning into ‘third_party/onnx’…
remote: Enumerating objects: 13, done.
remote: Counting objects: 100% (13/13), done.
remote: Compressing objects: 100% (12/12), done.
error: RPC failed; curl 18 transfer closed with outstanding read data remaining
fatal: The remote end hung up unexpectedly
fatal: early EOF
fatal: index-pack failed
fatal: clone of ‘GitHub - onnx/onnx: Open standard for machine learning interoperability’ into submodule path ‘third_party/onnx’ failed
Failed to recurse into submodule path ‘parsers/onnx’
I know i need to update three submodules as shown in .gitmodule, but i can’t successfully update any one of them
[submodule “third_party/protobuf”]
path = third_party/protobuf
url = GitHub - protocolbuffers/protobuf: Protocol Buffers - Google's data interchange format
branch = 3.8.x
[submodule “third_party/cub”]
path = third_party/cub
url = GitHub - NVlabs/cub: THIS REPOSITORY HAS MOVED TO github.com/nvidia/cub, WHICH IS AUTOMATICALLY MIRRORED HERE.
branch = 1.8.0
[submodule “parsers/onnx”]
path = parsers/onnx
url = GitHub - onnx/onnx-tensorrt: ONNX-TensorRT: TensorRT backend for ONNX
branch = 7.1
I got stuck at this for several days, help me.
Environment
TensorRT Version: TensorRT7.1
GPU Type: Jetson TX2/Jetson NX
Nvidia Driver Version:
CUDA Version: cuda10.2
CUDNN Version: 8.0.0.180-1
Operating System + Version: ubuntu18.04
Python Version (if applicable):
TensorFlow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):
Relevant Files
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Steps To Reproduce
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