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cudnn.torch
===========
Torch7 FFI bindings for NVidia CuDNN kernels!
Modules are API compatible their [`nn`](https://github.com/torch/nn) equivalents. Fully unit-tested against `nn` implementations.
#### Installation
* Install CuDNN
* Have at least Cuda 6.5
* Have `libcudnn.so` in your library path (Install it from https://developer.nvidia.com/cuDNN )
#### Modules
```
-- All inputs have to be 4D, even for ReLU, SoftMax etc.
cudnn.SpatialConvolution(nInputPlane, nOutputPlane, kW, kH, dW, dH, padW, padH)
cudnn.SpatialMaxPooling(kW, kH, dW, dH)
cudnn.SpatialAveragePooling(kW, kH, dW, dH)
cudnn.ReLU()
cudnn.Tanh()
cudnn.Sigmoid()
-- SoftMax can be run in fast mode or accurate mode. Default is accurate mode.
cudnn.SoftMax(fastMode [= false]) -- SoftMax across each image (just like nn.SoftMax)
cudnn.SpatialSoftMax(fastMode [= false]) -- SoftMax across feature-maps (per spatial location)
```
I have no time to support these, so please don't expect a quick response to filed github issues.
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