I have the same problem.
It seems that I have already installed it into Ubuntu 16.04 LTS(Ubuntu 18.04 LTS has a gcc compatibility problem, so I uninstalled Ubuntu 18.04 LTS). I have installed two environments including NVIDIA-Linux-x86_64-415.27.run, Anaconda3-2019.03-Linux-x86_64.sh. With usage of conda install tensorflow(v13.1), I installed tensorflow-gpu that includes both cudatoolkit-10.0.130 and cudnn-7.3.1.
I can use the following commands to initiitate the Jupyter environment.
(tf-gpu) mike@mike:~ conda install jupyter
(tf-gpu) mike@mike:~ python -m ipykernel install --user --name tf-gpu --display-name “TensorFlow-GPU”
(tf-gpu) mike@mike:~$ jupyter notebook
However, I had the the error. After I put the MNIST test code into the cell of TensorFlow-GPU, It failed to get convolution algorithm since cuDNN failed to initialize. I update all commands according to this forum suggestoins. However, it still had the problem after updating tensorflow-gpu in the environment of tf-gpu. Please have a look at the following information.
UnknownError: Failed to get convolution algorithm
UnknownError Traceback (most recent call last)
34 model.fit(X_train, y_train, batch_size=128, epochs=15, verbose=1,
—> 35 validation_data=(X_test,y_test), callbacks=[tensor_board])
~/anaconda3/envs/tf-gpu/lib/python3.7/site-packages/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)
-> 1039 validation_steps=validation_steps)
UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
Please help me solve the issue.
Thanks in advance,