Azure / Azure/MachineLearningNotebooks

Not recognizing libcudart when running commands

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描述

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?

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研究方向

從報告中的命令 `python3 -c "import tensorflow as tf; print(tf.__version__)"` 開始,將 TensorFlow 2.3 預期的 CUDA runtime 與 Azure ML 3.8 環境進行比較。檢查 `/usr/local/cuda`、`/usr/local/cuda-11` 和 `/usr/local/cuda-11.1` 路徑以及 `LD_LIBRARY_PATH`;完成標準是解釋版本不相符的原因,並記錄一種經過驗證的移除或避免該警告的方法。

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評估

技術堆疊
azure, jupyter-notebook, python, tensorflow
領域
cloud, machine-learning
Issue 類型
缺陷
難度
3/5
預估耗時
1-2 天
活躍度
停滯
描述清晰度
基本清楚
新手友好度
25/100

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