[英]How to install tensorflowgpu-version with lower(compatible) version of cudatoolkit and cudnn
Every time I install tensorflow-gpu
on anaconda its automatically installing tensorflow-gpu
with the most updated available version of cudatoolkit
and cudnn
evens if it's not compatible with graphic card and cuda which I have already installed on my computer, which creates a big problem later on in simulations.每次我在 anaconda 上安装tensorflow-gpu
时,它会自动安装带有最新可用版本的cudatoolkit
和cudnn
的tensorflow-gpu
,即使它与我已经安装在我的计算机上的显卡和 cuda 不兼容,这会在以后产生一个大问题在模拟中。
For example I have RTX3060 and I am installing tensorflow-gpu 2.5.0
, I have already installed cuda 11.1 but when I install it with anaconda as例如我有 RTX3060 并且我正在安装tensorflow-gpu 2.5.0
,我已经安装了 cuda 11.1 但是当我使用 anaconda 安装它时
"conda install tensorflow-gpu=2.5.0"
It will install cudatoolkit 11.3.x
... and the most advanced available cudnn它将安装cudatoolkit 11.3.x
...和最先进的可用 cudnn
You can install tensorflow-gpu
with the following commands with compatible cudatoolkit
and cudnn
versions.您可以使用以下兼容cudatoolkit
和cudnn
版本的命令安装tensorflow-gpu
。
conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0
#It is recommended to use pip to install TensorFlow since it is officially released to PyPI.
python3 -m pip install tensorflow-gpu==2.5.0
# Verify install:
python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"
For step-by-step instructions, please refer to this link .有关分步说明,请参阅此链接。
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