Error : Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so...

TF-1.12,Keras-2.2.4,cuda 9.0,cudnn 7.2.4 linux ,when keras call convoluation funtion,it will report error.How to fix it?I found any solutions from web search,and it still can’t work.

tf-1.14, cuda 10.0, cudnn 7.4.1 windows10, when keras call convoluation funtion,it will report error.How to fix it?I found any solutions from web search,and it still can’t work.

So after some more experimentation, a reboot and the following sequence made the 1D convolution work:

import tensorflow as tf
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
tf.keras.backend.set_session(tf.Session(config=config))

The thing to highlight is that this required a full reboot, and was the first sequence executed.

This did not work previously when I tried without a reboot. Even shutting down and restarting jupyter notebook did not help.

Here’s what I have installed for reference, with a GTX 1660 Ti on an ASUS ROG Strix laptop under Ubuntu 18.04.

sudo dpkg -i libcudnn7_7.4.1.5-1+cuda10.0_amd64.deb libcudnn7-dev_7.4.1.5-1+cuda10.0_amd64.deb libcudnn7-doc_7.4.1.5-1+cuda10.0_amd64.deb pip3 install --upgrade tensorflow-gpu==1.13.1
$ nvidia-smi
Sat Sep 7 12:02:49 2019
±----------------------------------------------------------------------------+
| NVIDIA-SMI 430.40 Driver Version: 430.40 CUDA Version: 10.1 |
|-------------------------------±---------------------±---------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 166… Off | 00000000:01:00.0 On | N/A |
| N/A 52C P0 33W / N/A | 5011MiB / 5944MiB | 17% Default |
±------------------------------±---------------------±---------------------+

==============================================================================

[1]
import tensorflow as tf

config = tf.ConfigProto()
config.gpu_options.allow_growth = True
tf.keras.backend.set_session(tf.Session(config=config))

from keras.models import Sequential
from keras import layers
from keras.optimizers import RMSprop

Full execution example =>

https://devtalk.nvidia.com/default/topic/1048456/cudnn/-quot-failed-to-get-convolution-algorithm-quot-problem/post/5381714/#5381714