Comments (4)
There is no authority to change label to me
from wicwiu.
The first question is that we are concerned about adding cuDNN code for cuDNNRNNForward because we can find cuDNN code in Operator low class, not Module low class.
from wicwiu.
We received the answer of these problems from Professor Kim.
In first matter of RNN class inheritance, he recommended class RNNcell : public Module,
and just cuDNN code in class RNN : public Operator.
In second matter of selecting NeuralNet unit, second case is the best because of expanding LSTM, etc.
Thank you for considering the problem:)
from wicwiu.
I don't have any ideas about it. It depends your decision.
I cannot advice to future implementation.
Thank you.
from wicwiu.
Related Issues (19)
- Convolution Operator CPU Algorithm cannot allow padding
- General-purpose data reader HOT 1
- Implement GAN as two Neural Network sharing one parameter
- (High priority) Implement Deep Copy, Shallow Copy HOT 1
- Triplet Loss ForwardPropogate HOT 3
- LossFunction debugging by cgdb HOT 3
- Question about AnalyzeGraph in Module class HOT 6
- Convolution CPU padding algo
- Implement dataset class extension for well-known data like MNIST, CIFAR, Imagenet HOT 3
- GAN module debug list HOT 1
- Reconstruct the hierarchy of 'tutorials' directory
- logical errors in 'triplet branch'
- Only single thread is used in 'Sampler' HOT 1
- Add va_end function in Operator.cpp
- `BatchNormalize.h`에서 파라미터를 모두 저장하지 않는 문제 HOT 1
- Please consider logger for printing log message
- GradientDescentOptimizer GPU momentum HOT 1
- Operator/PRelu learning rate
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