I try "torch-2.0.0+nv23.05-cp38-cp38-linux_aarch64.whl " and “torch-2.0.0a0+fe05266f.nv23.04-cp38-cp38-linux_aarch64.whl” as AttributeError: module 'torch.distributed' has no attribute 'ReduceOp' ,but still failed .
my versions as below :
jetpack is 5.1.1
$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Sun_Oct_23_22:16:07_PDT_2022
Cuda compilation tools, release 11.4, V11.4.315
‘DISPLAY’ environment variable not set… skipping surface info
- Jetson AGX Orin
- Jetpack UNKNOWN [L4T 35.3.1]
- NV Power Mode: MAXN - Type: 0
- jetson_stats.service: active
- CUDA: NOT_INSTALLED
- cuDNN: 18.104.22.168
- TensorRT: 22.214.171.124
- Visionworks: NOT_INSTALLED
- OpenCV: 4.5.4 compiled CUDA: NO
- VPI: 2.2.7
- Vulkan: 1.3.204
Have you run the script on another platform before?
If yes, which PyTorch version is used?
I want to run renet50 on my jetson agx orin 64G , when I install mmpretrain from source (skip conda) by https://mmpretrain.readthedocs.io/en/latest/index.html， it failed as ：
while I flash my jetson agx orin 64 to jetpack 5.1 ，this problem happens again
@qiangqiangsir the PyTorch 1.11 wheel was the last one to be built with USE_DISTRIBUTED:
- JetPack 5.0 (L4T R34.1) / JetPack 5.0.2 (L4T R35.1) / JetPack 5.1 (L4T R35.2.1) / JetPack 5.1.1 (L4T R35.3.1)
If you require a newer version of PyTorch with distributed enabled, please see this thread for instructions on building PyTorch from source:
Or perhaps it’s possible to disable distributed mode in the mmpretrain library you are using?
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