*My installed packages are:CUDA 11.7, cudnn 8.5, theano 1.0.5When I run the
convolution network in the test file of Michael Nielsen's tutorial on Deep
Learning <https://github.com/MichalDanielDobrzanski/DeepLearningPython>:*
import network3
from network3 import Network, ConvPoolLayer, FullyConnectedLayer,
SoftmaxLayer
training_data, validation_data, test_data = network3.load_data_shared()
mini_batch_size = 10
net = Network([
ConvPoolLayer(image_shape=(mini_batch_size, 1, 28,
28),filter_shape=(20, 1, 5, 5), poolsize=(2,
2)),FullyConnectedLayer(n_in=20*12*12, n_out=100),SoftmaxLayer(n_in=100,
n_out=10)], mini_batch_size)
net.SGD(training_data, 60, mini_batch_size, 0.1,
validation_data, test_data)
* Problem occurred during compilation with the command line below:*
dnn_fwd.c:326:60: error: invalid conversion from 'size_t {aka long unsigned
int}' to 'int*' [-fpermissive]
dnn_fwd.c:326:60: error: cannot convert 'cudnnConvolutionFwdAlgo_t*' to
'cudnnConvolutionFwdAlgoPerf_t* {aka cudnnConvolutionFwdAlgoPerfStruct*}'
for argument '8' to 'cudnnStatus_t
cudnnGetConvolutionForwardAlgorithm_v7(cudnnHandle_t,
cudnnTensorDescriptor_t, cudnnFilterDescriptor_t,
cudnnConvolutionDescriptor_t, cudnnTensorDescriptor_t, int, int*,
cudnnConvolutionFwdAlgoPerf_t*)'
*I understand that incompatibility of packages should be the reason,
however I was wondering if there is any way to resolve this by modify the
module or the theano's config file without downgrading the packages?*
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