So, because hex-packages depends on both jax[cuda12] (0.4.23) and tensorflow[and-cuda] (2.15.0), version solving failed. and none of thejax[cuda12]versions with GPU compatibility supportnvidia-nccl-cu12=2.16.5; does this requirement need to be hard or can it be looser to accomodate h...
先在官网查显卡的算力(Compute Capability),如 RTX 3060 为 8.6 再查该算力支持的 CUDA SDK,如 8.6 支持的 CUDA SDK 为 11.1 - 11.4(建议 RTX 3060 装 11.1) 一、显卡型号 桌面右键→NVIDIA控制面板→帮助→系统信息 显卡型号为GTX 1660 若桌面右键无NVIDIA控制面板,查看参考文献 二、CUDA 查找显卡对应的CUDA...
cuda-9.0 requires gcc-6. I installed gcc-6, but that didn’t solved the problem. My question: Am i heading to the right direction. Will the nvidia-396 display drivers work in hand with cuda-9.0 If the answer of 1. is yes , then how to solve the complier version issueRobert...
Please refer to this link to use the correct compatibility. Saduf2019 added the stat:awaiting response label Dec 12, 2021 Author pn12 commented Dec 12, 2021 @Saduf2019 - It's resolved now, there was a version compatibility issue among cuda , tf , cudnn. Thanks. pn12 closed this as...
安装好过后cuda应该就在/usr/local/路径下了。然后安装CUDNN Toolkit,进入其下载目录: AI检测代码解析 tar xvzf cudnn-7.0-linux-x64-v3.0-prod.tgz cp cuda/include/cudnn.h /usr/local/cuda/include cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 1. 2. 3. 然后设置 LD_LIBRARY_PATH 和 CUDA_...
E tensorflow/stream_executor/cuda/cuda_dnn.cc:390]Loaded runtime CuDNN library: 5005 (compatibility version 5000) but source wascompiled with 5110 (compatibility version 5100). If using a binary install, upgrade your CuDNNlibrary to match. If building fromsources, make sure the library loaded ...
I tensorflow/core/common_runtime/gpu/gpu_device.cc:838] Creating TensorFlow device(/gpu:0) -> (device:0, name: Tesla K20m, pci bus id:0000:02:00.0) E tensorflow/stream_executor/cuda/cuda_dnn.cc:347] Loaded runtime CuDNN library: 6022(compatibility version5000) but source was compiled ...
conda install cudatoolkit=10.1 # GPU 加速，需要英伟达GPU，要跟 python 的版本一一对应 conda ...
E tensorflow/stream_executor/cuda/cuda_dnn.cc:347] Loaded runtime CuDNN library: 4007 (compatibility version 4000) but source was compiled with 5103 (compatibility version 5100). If using a binary install, upgrade your CuDNN library to match. If building from sources, make sure the library ...
CUDA: 11.4.2 cuDNN: 8.2.4 正如在下面的代码中,当加载一个通过不向Normalization()传递参数来规范化的模型时,当该模型由load_model()加载时,它会抛出一个异常,但是在加载模型之前,我可以使用它,而不会出现任何明显的问题,这会让您认为这一切都很好,因为Normalization()没有抱怨并处理了输入形状。加载由Normaliz...