Enable usage of mirrored.tarredistributions in CUDA repository ru… May 1, 2025 .bazelversion Upgrade to Bazel 7.4.1 for TensorFlow Feb 27, 2025 .clang-format [.clang-format] Init @ root Dec 7, 2021 .gitignore Added venv/ to .gitignore ...
CUDA driver version is insufficient for CUDA runtime version 经过分析,我发现使用anaconda自动分析依赖安装的cudatoolkit的版本是CUDA 10.0 (10.0.130),而ubuntu装机自带的NVIDIA驱动版本是nvidia-38 使用如下命令查询Nvidia驱动版本: nvidia-smi 使用如下命令查询cudatoolkit, cuda, cudnn版本: conda list cudatoolkit...
Make sure you are using compatible TF and CUDA versions. Please refer following TF version and CUDA version compatibility table. TFCUDA 2.1.0 - 2.2.010.1 1.13.1 - 2.010.0 1.5.0 - 1.12.09.0 If you have above configuration and usingWindowsplatform - ...
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Release 20.07 is based on NVIDIA CUDA 11.0.194, which requires NVIDIA Driver release 450 or later. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.xx or 440.30. The CUDA driver's compatibility package only supports ...
The following table shows what versions of Ubuntu, CUDA, TensorFlow, and TensorRT are supported in each of the NVIDIA containers for TensorFlow. For older container versions, refer to the Frameworks Support Matrix. Expand Container VersionUbuntuCUDA ToolkitTensorFlowTensorRT 22.06 20.04 NVIDIA CUDA 11....
NVIDIA driver 391.35 or newer, CUDA toolkit 9.0 or newer, cuDNN 7.3.1 or newer. Using pre-trained networks A minimal example of using a pre-trained StyleGAN generator is given inpretrained_example.py. When executed, the script downloads a pre-trained StyleGAN generator from Google Drive and...
The libcupti-dev library, which is the NVIDIA CUDA Profile Tools Interface. This library provides advanced profiling support. To install this library, issue the following command for CUDA Toolkit >= 8.0: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 $ sudo apt-get install cuda-command-line...
On Windows, you need to use TensorFlow 1.14 — TensorFlow 1.15 will not work. One or more high-end NVIDIA GPUs, NVIDIA drivers, CUDA 10.0 toolkit and cuDNN 7.5. To reproduce the results reported in the paper, you need an NVIDIA GPU with at least 16 GB of DRAM. ...
Again the RTX3080 is doing very well with mixed precision fp16. I expect this number to improve with a new driver and some CUDA patches. There is a dramatic improvement for the RTX Titan at fp16 1082 img/sec vs 653 img/sec from the older testing!