Not recognizing libcudart when running commands

I have a GPU compute (Standard_NC6s_v3), and I want to train a model using that. The kernel/environment (Azure ML 3.8) has tensorflow 2.3 install by default, and CUDA 11. But when I run a few commands (example: python3 -c "import tensorflow as tf;print(tf.__version__)" to get the TF version), it gives me a warning:

```
2021-11-16 13:23:10.274930: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory
2021-11-16 13:23:10.274970: 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.

```

Why is it looking for libcudart.so.10.1 when version 11 is installed? I also can't manually install CUDA 10.1. I tried resetting the LD_LIBRARY_PATH variable, using `export LD_LIBRARY_PATH=/usr/local/cuda-11.1/targets/x86_64-linux/lib` but that didn't work either.

Checking `ls /usr/local/ `using the terminal, I have three cuda folders; cuda, cuda 11, and cuda 11.1.

How can I bypass that error/warning?

報告されたコマンド `python3 -c "import tensorflow as tf; print(tf.__version__)"` から始め、TensorFlow 2.3 が想定する CUDA runtime と Azure ML 3.8 環境を比較します。`/usr/local/cuda`、`/usr/local/cuda-11`、`/usr/local/cuda-11.1` のパスと `LD_LIBRARY_PATH` を確認します。バージョンの不一致を説明し、警告を削除または回避する検証済みの方法を文書化できれば完了です。

索引モデルが issue の本文から書いたものです。