Tensorflow2.X-GPU-CUDA9.0
This Tensorflow2.X-GPU-CUDA9.0 is bazeled from the sorce code of Google.
If you have configured cuda9 and cudnn in your .bashrc, you can skip to Third step.
Create cuda9.0 environment by condaconda create -n cuda9.0 conda activate cuda9.0 conda install cudatoolkit=9.0 cudnn=7.6.0 cuptiAdd dependency in .bashrc
Use conda env list find the path of cuda9.0
(tf2) wxy@sait:~$ conda info -e # conda environments: # cuda9.0 /disk1/lx/conda/envs/cuda9.0 mk /disk1/lx/conda/envs/mk
change the CONDA_ENV to your path of cuda9.0
add the following three lines of code in .bashrc
export CONDA_ENV="/disk1/lx/conda/envs/cuda9.0" export CUDA_HOME="$CUDA_HOME:$CONDA_ENV/lib" export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$CONDA_ENV/lib"
Then source .bashrc in you terminal.
Google-drive: tensorflow2.1-gpu-cudn9.0-py3.7
Google-drive: tensorflow2.0-gpu-cudn9.0-py3.7
Google-drive: tensorflow2.0-gpu-cudn9.0-py3.6
Google-drive: tensorflow2.0-gpu-cudn9.0-py3.5
Create a new env in conda(you can change test to your like)conda create -n test python=3.7 conda activate test pip install tensorflow-2.0.0-cp37-cp37m-linux_x86_64.whl
python import tensorflow as tf tf.test.is_gpu_available()
If it shows True, congratulations.
W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusolver.so.9.0';.....undefined symbol: GOMP_critical_end;
If you have this error, please add follow code in your code.
import tensorflow as tf
import ctypes
ctypes.CDLL("libgomp.so.1", mode=ctypes.RTLD_GLOBAL)
tf.test.is_gpu_available()
If it works , please give me a star.
Thank you!
How to install tensorflow2.X-GPU in your cuda version?you need to bazel from the source code of tensorflow in your machine.
Reference
How to install tensorflow2.0 in cuda9?
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