Could not load library libcublasLt.so.12. Error: libcublasLt.so.12: cannot open shared object file: No such file or directory

这个错误提示表明程序在运行过程中需要使用名为"libcublasLt.so.12"的库文件，但是找不到该文件。这通常是由于缺少CUDA的相关库文件或者CUDA安装不正确导致的。

解决这个问题的方法通常是检查CUDA的安装情况和版本是否正确，并重新安装或更新相应的CUDA库文件。你可以尝试使用以下命令来安装缺失的库文件：

sudo apt-get install nvidia-cuda-toolkit

如果你已经安装了CUDA，但是仍然出现这个错误，可能需要更新你的CUDA版本或者升级GPU驱动程序。

相关问题

paddle Could not load library libcudnn_ops_infer.so.8. Error: libcublas.so.11: cannot open shared object file: No such file or directory

paddle报错"Could not load library libcudnn_ops_infer.so.8. Error: libcublas.so.11: cannot open shared object file: No such file or directory"是由于缺少libcublas.so.11库文件导致的。解决这个问题的方法是通过设置LD_LIBRARY_PATH环境变量，将库文件路径添加到环境变量中。

可以按照以下步骤解决该问题：
1. 打开终端，运行命令`export LD_LIBRARY_PATH=.:/usr/local/cuda-10.2/lib64:/home/username/demo/cuda/lib64`，将所需的库文件路径添加到LD_LIBRARY_PATH环境变量中。其中，`.`表示当前目录，`/usr/local/cuda-10.2/lib64`和`/home/username/demo/cuda/lib64`是库文件所在的路径。请根据实际情况修改路径。
2. 运行paddle程序，查看是否仍然报错。如果问题得到解决，则说明添加环境变量成功。如果仍然报错，请确认库文件路径是否正确，并确保库文件存在。
3. 如果问题仍然存在，可以尝试重新安装paddle和相关依赖项，或者更新CUDA和cuDNN版本，以确保与库文件兼容。

Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory

This error indicates that the dynamic library 'libnvinfer.so.6' could not be found or loaded. This library is typically associated with NVIDIA's TensorRT framework. To resolve this issue, you can try the following steps:

1. Make sure that you have installed TensorRT and its dependencies correctly.
2. Check if the library file 'libnvinfer.so.6' exists in the specified directory. If not, you may need to reinstall TensorRT.
3. Ensure that the library path is correctly set in the LD_LIBRARY_PATH environment variable. You can use the following command to check if the library path is included:

   echo $LD_LIBRARY_PATH

If it is not included, you can add it by running:

   export LD_LIBRARY_PATH=/path/to/tensorrt:$LD_LIBRARY_PATH

Replace '/path/to/tensorrt' with the actual path where TensorRT is installed.

If the issue persists, please provide more information about your system configuration, such as the operating system and version, CUDA version, and any other relevant details.