I’ve downloaded the following docker containers:
- nvcr.io/nvidia/l4t-ml (tag: r34.1.1-py3)
- nvcr.io/nvidia/l4t-tensorflow (tag: r34.1.1-tf2.8-py3)
nvcr.io/nvidia/l4t-tensorflow (tag: r32.6.1-tf2.5-py3)
and run the docker with each one applying the following procedure:
- activating python3
- import tensorflow
When run it with the ml container I got the following notifications:
I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
When run it with the tensorflow 2.8 container it got completed with no notification.
When run it with the tensorflow 2.5 container the following error/warning was noted:
W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library ‘libcudart.so.10.2’; dlerror: libcudart.so.10.2: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda/lib64:/usr/local/cuda-10.2/targets/aarch64-linux/lib:
2022-06-21 06:04:11.875329: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Could someone elaborate on the differences?