Transposed Convolution


I’m working on a project where we want to compare different implementation of DNN. One of these implementation is in cuDNN.
We need to implement a transposed convolution as the Conv2DTranspose in TensorFlow Keras.

Can we found some example or guide about implementation of the transposed convolution in cuDNN ?

Thanks in advance,


Hi @hugo.kieffer ,
Deconvolution/transposed convolution is basically the “dgrad” operation. Dgrad is designed for the backwards phase of training, so you may need to choose your filter layout accordingly. (If a forward convolution from Tensor A NCHW to Tensor C NKPQ uses a KRSC filter, then the dgrad operation would take Tensor C as input and Tensor A as ouput, but still use the KRSC filter.)
Note also that unstrided (unit strided) deconvolution is just a convolution with the filter transposed (hence the alternate name “transposed convolution”). So if it’s not a strided deconvolution, just use cudnn’s convolution operator and flip the cross correlation flag.

However i am afraid, I dont think we have a sample available for the same.



Have you had any success implementing this layer in cuDNN?

Hello, I haven’t had time to rework on the subject yet, we have several parallel implementations (FPGA and GPU) and we have had work on the FPGA target.
I’ll share an example when I have a functional code.