无法加载库 libcublasLt.so.12。错误：libcublasLt.so.12：无法打开共享对象文件：没有这样的文件或目录，Conv2D TensorFlow

Question

我正在尝试在 WSL2 中设置具有 GPU 支持的 TensorFlow。我正在遵循本指南。

当我运行这段代码时：

>>> from tensorflow import keras
>>> import numpy as np
>>> t = np.ones([5,32,32,3])
>>> c = keras.layers.Conv2D(32, 3, activation="relu")
>>> c(t)

我收到此错误：

2023-07-09 09:59:38.820408: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-07-09 09:59:39.031437: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-07-09 09:59:39.031864: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-07-09 09:59:39.034068: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-07-09 09:59:39.034535: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-07-09 09:59:39.034921: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-07-09 09:59:40.590457: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-07-09 09:59:40.590941: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-07-09 09:59:40.591052: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1722] Could not identify NUMA node of platform GPU id 0, defaulting to 0.  Your kernel may not have been built with NUMA support.
2023-07-09 09:59:40.591459: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-07-09 09:59:40.591526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1635] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 3858 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 2060, pci bus id: 0000:01:00.0, compute capability: 7.5
Could not load library libcublasLt.so.12. Error: libcublasLt.so.12: cannot open shared object file: No such file or directory
Aborted

令人困惑的是，当我运行这段代码时：

>>> from tensorflow import keras
>>> import numpy as np
>>> t = np.ones([5,32,32,3])
>>> c = keras.layers.Dense(32, activation="relu")
>>> c(t)

我得到输出并且没有错误。

• 我尝试过重新安装Cuda、CuDNN
• 我尝试在 wsl ubuntu 20.04 和 22.04.2 的全新安装中安装所有内容
• 我尝试过 Tensorflow 2.10、2.11、2.12 和 2.13
• 我也尝试过apt install libcublasLt

没有任何作用

环境：

• Windows 11 家庭版
• WSL 2
• 英特尔 i7-9750h
• Nvidia RTX 2060 笔记本
• 张量流2.12.1
• Python 3.9
• WSL2 Ubuntu 20.04
• 库达11.8
• 铜DNN 8.6

我也在 conda 环境中运行它

Answer 1

和您一样，我在使用 TensorFlow 和 CUDA 11 时突然开始看到这些错误，要求使用 CUDA 12 库。

经过一番搜索后，我发现libcublas-12-0Ubuntu 软件包确实提供了所有必需的文件：

/usr/local/cuda-12.0/targets/x86_64-linux/lib/
 libcublas.so.12 -> libcublas.so.12.0.2.224
 libcublasLt.so.12 -> libcublasLt.so.12.0.2.224
 libnvblas.so.12 -> libnvblas.so.12.0.2.224

然而，我不想搞乱我完美的 CUDA 11 安装，所以我只是手动下载该包并将所需的文件提取到当前的 CUDA 目录中：

/usr/local/cuda-12.0/targets/x86_64-linux/lib/
 libcublas.so.12 -> libcublas.so.12.0.2.224
 libcublasLt.so.12 -> libcublasLt.so.12.0.2.224
 libnvblas.so.12 -> libnvblas.so.12.0.2.224

仍然不知道为什么 TensorFlow 首先需要这些库......