在一个全新的LambdaLabs GPU示例上，我安装了带有Bazelisk的Bazel：

wget https://github.com/bazelbuild/bazelisk/releases/download/v1.8.1/bazelisk-linux-amd64
chmod +x bazelisk-linux-amd64
sudo mv bazelisk-linux-amd64 /usr/local/bin/bazel

然后我下载TF来源：

git clone https://github.com/tensorflow/tensorflow.git
cd tensorflow
git checkout r2.11

然后运行config：

./configure

结果是：

ubuntu@*********:~/tensorflow$ ./configure
You have bazel 5.3.0 installed.
Please specify the location of python. [Default is /usr/bin/python3]: 

Found possible Python library paths:
  /usr/lib/python3/dist-packages
  /usr/local/lib/python3.8/dist-packages
Please input the desired Python library path to use.  Default is [/usr/lib/python3/dist-packages]

Do you wish to build TensorFlow with ROCm support? [y/N]: n
No ROCm support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: y
CUDA support will be enabled for TensorFlow.

Do you wish to build TensorFlow with TensorRT support? [y/N]: y
TensorRT support will be enabled for TensorFlow.

Inconsistent CUDA toolkit path: /usr vs /usr/lib
Asking for detailed CUDA configuration...

Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 11]: 

Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 2]: 

Please specify the TensorRT version you want to use. [Leave empty to default to TensorRT 6]: 

Please specify the locally installed NCCL version you want to use. [Leave empty to use http://github.com/nvidia/nccl]: 

Please specify the comma-separated list of base paths to look for CUDA libraries and headers. [Leave empty to use the default]: 

Inconsistent CUDA toolkit path: /usr vs /usr/lib
Asking for detailed CUDA configuration...

我不知道如何告诉编译器使用哪个CUDA工具包路径，甚至哪个是正确的路径。我只是试图用TFRT支持重建TF。
谢谢
编辑：
当我检查CUDA的安装位置时：

locate cuda | grep /cuda$

/home/ubuntu/tensorflow/tensorflow/compiler/xla/stream_executor/cuda
/home/ubuntu/tensorflow/tensorflow/stream_executor/cuda
/home/ubuntu/tensorflow/third_party/gpus/cuda
/usr/include/cuda
/usr/include/thrust/system/cuda
/usr/lib/cuda
/usr/lib/python3/dist-packages/pycuda/cuda
/usr/lib/python3/dist-packages/tensorflow/include/tensorflow/stream_executor/cuda
/usr/lib/python3/dist-packages/theano/sandbox/cuda
/usr/lib/python3/dist-packages/torch/cuda
/usr/lib/python3/dist-packages/torch/backends/cuda
/usr/lib/python3/dist-packages/torch/include/ATen/cuda
/usr/lib/python3/dist-packages/torch/include/ATen/native/cuda
/usr/lib/python3/dist-packages/torch/include/c10/cuda
/usr/lib/python3/dist-packages/torch/include/torch/csrc/cuda
/usr/lib/python3/dist-packages/torch/include/torch/csrc/jit/cuda
/usr/lib/python3/dist-packages/torch/include/torch/csrc/jit/codegen/cuda
/usr/lib/python3/dist-packages/torch/include/torch/csrc/jit/codegen/fuser/cuda
/usr/share/doc/libthrust-dev/examples/cuda

显然，正确的路径是/usr/lib/，但我不知道如何告诉编译器使用该路径。