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authorAmir Arsalan Soltani <Amir-Arsalan@users.noreply.github.com>2016-10-09 01:34:59 +0300
committerGitHub <noreply@github.com>2016-10-09 01:34:59 +0300
commit298d56013488955e208d632c2a424c0c98be4e56 (patch)
tree4572eaf9c698b0b0bad906cb814aef84e610226f
parentff8ae89f1399131c5199c6d81fafea20de434851 (diff)
Update README.md
-rw-r--r--README.md5
1 files changed, 4 insertions, 1 deletions
diff --git a/README.md b/README.md
index 303619f..e454303 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,8 @@ Conversion between `nn` and `cudnn` is available through `cudnn.convert` functio
* Install cuDNN (version R5 EA)
* Have at least CUDA 7.0
-* Have `libcudnn.so` in your library path (Install it from https://developer.nvidia.com/cuDNN )
+* Have `libcudnn.so` in your library path ($LD_LIBRARY_PATH) (Install cuDNN it from https://developer.nvidia.com/cuDNN )
+* Instead of the previous step, you can copy the library files into /usr/local/cuda/lib64/ or to the corresponding folders in CUDA directory
#### Modules
@@ -90,6 +91,8 @@ If you don't want to convert all modules you can pass a function as the third ar
It will be called at each step, with a module that is currently converted. It is meant to exclude
modules i.e. if it returns `true`, they will be left untouched, otherwise they will be subject to conversion.
+`Note that you cannot do backward pass when using cuDNN and when your model has batch normaliation layers and is in evaluate mode.`
+
```lua
net = nn.Sequential()
net:add(nn.SpatialConvolution(3,96,11,11,3,3))