Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Installation errors with CUDNN v5 #3969

Closed
iNeil77 opened this issue Apr 9, 2016 · 23 comments
Closed

Installation errors with CUDNN v5 #3969

iNeil77 opened this issue Apr 9, 2016 · 23 comments

Comments

@iNeil77
Copy link

iNeil77 commented Apr 9, 2016

I have cuda v7.5 and cudnn v5 installed and upon having pre-installed the necessary dependencies through apt-get and pip, I proceeded to make all in my caffe master directory with my makefile config having USE_CUDNN := 1 set, which led to the following error. Can anybody tell me where am I going wrong?
Thanks in advance!

neilpaul77@NeilRig77:~/Documents/Git/caffe$ make all
CXX src/caffe/util/im2col.cpp
In file included from ./include/caffe/util/device_alternate.hpp:40:0,
                 from ./include/caffe/common.hpp:19,
                 from ./include/caffe/util/math_functions.hpp:9,
                 from src/caffe/util/im2col.cpp:4:
./include/caffe/util/cudnn.hpp: In function ‘void caffe::cudnn::createPoolingDesc(cudnnPoolingStruct**, caffe::PoolingParameter_PoolMethod, cudnnPoolingMode_t*, int, int, int, int, int, int)’:
./include/caffe/util/cudnn.hpp:127:41: error: too few arguments to function ‘cudnnStatus_t cudnnSetPooling2dDescriptor(cudnnPoolingDescriptor_t, cudnnPoolingMode_t, cudnnNanPropagation_t, int, int, int, int, int, int)’
         pad_h, pad_w, stride_h, stride_w));
                                         ^
./include/caffe/util/cudnn.hpp:15:28: note: in definition of macro ‘CUDNN_CHECK’
     cudnnStatus_t status = condition; \
                            ^
In file included from ./include/caffe/util/cudnn.hpp:5:0,
                 from ./include/caffe/util/device_alternate.hpp:40,
                 from ./include/caffe/common.hpp:19,
                 from ./include/caffe/util/math_functions.hpp:9,
                 from src/caffe/util/im2col.cpp:4:
/usr/local/cuda/include/cudnn.h:799:27: note: declared here
 cudnnStatus_t CUDNNWINAPI cudnnSetPooling2dDescriptor(
                           ^
Makefile:572: recipe for target '.build_release/src/caffe/util/im2col.o' failed
make: *** [.build_release/src/caffe/util/im2col.o] Error 1
@seanbell
Copy link

seanbell commented Apr 9, 2016

I'm pretty sure that cuDNN v5 isn't supported yet. I think caffe is still on v3. cuDNN v4 is the current supported version.

See #3919

@naibaf7
Copy link
Member

naibaf7 commented Apr 9, 2016

@iNeil77
cuDNN V4/V5 is supported (unofficially though) on https://github.com/BVLC/caffe/tree/opencl
Otherwise as @seanbell pointed out, you have to go to V3 or wait for #3919 to be merged (or make a fork and merge that PR in yourself).

@flx42
Copy link
Contributor

flx42 commented Apr 9, 2016

cuDNN v4 works fine with the master branch, since December. I don't know why people keep saying it doesn't :)
It's just that there is no cuDNN BN layer, but you will benefit from all the performance improvements from v4.

@iNeil77 iNeil77 closed this as completed Apr 9, 2016
@samchorlton
Copy link

iNeil77 did you manage to fix this in the end? If so how as I have the exact same problem? (I have tried version 3,4 and 5

@iNeil77
Copy link
Author

iNeil77 commented Apr 11, 2016

@samchorlton No I needed it setup quickly, so I just proceeded to install with v3

@flx42
Copy link
Contributor

flx42 commented Apr 11, 2016

@samchorlton @iNeil77 again, v4 works fine too. If that's not the case you have a problem with your setup.

@iNeil77
Copy link
Author

iNeil77 commented Apr 11, 2016

Didnt try v4, just stuck to what everyone says works

@shelhamer
Copy link
Member

To reiterate, cuDNN v4 works perfectly fine as of #3439 in Dec. 2015 as @flx42 noted.

@atticcas
Copy link

Since I am using bleeding edge Theano, they force me to upgrade to v5, any way to make caffe to work with v5?

@flx42
Copy link
Contributor

flx42 commented Apr 14, 2016

@atticcas you will need this PR: #3919

@atticcas
Copy link

MANY THANKS!
wonder why this hasn't been pulled to master yet.
Lets see what happens after I pull those three commits.

@ghost
Copy link

ghost commented Apr 26, 2016

I met the same error

@youngwanLEE
Copy link

youngwanLEE commented May 2, 2016

I also met this same error. What should I do? eventually, I have to re-install ubuntu14.04 and start at the beginning?? :(

@ghost
Copy link

ghost commented May 2, 2016

it now support cudnnv4 not v5

On Mon, May 2, 2016 at 12:36 PM youngwanLEE [email protected]
wrote:

I also this same error. What should I do? eventually, I have to re-install
ubuntu14.04 and start at the beginning?? :(


You are receiving this because you commented.
Reply to this email directly or view it on GitHub
#3969 (comment)

@ghost
Copy link

ghost commented May 2, 2016

use cudnn v4

On Mon, May 2, 2016 at 12:36 PM youngwanLEE [email protected]
wrote:

I also this same error. What should I do? eventually, I have to re-install
ubuntu14.04 and start at the beginning?? :(


You are receiving this because you commented.
Reply to this email directly or view it on GitHub
#3969 (comment)

@Clayton-Davis
Copy link

just using V4 worked for me

@flx42
Copy link
Contributor

flx42 commented Jul 13, 2016

@Clayton-Davis v5 is supported now actually

@ghost
Copy link

ghost commented Jul 21, 2016

@flx42 Really? I will have a try now. Thank you for the inform.

@oztc
Copy link

oztc commented Sep 9, 2016

@RuiLiu1217 v5 can work ?

@oztc
Copy link

oztc commented Sep 9, 2016

@flx42 when I run v5, it reports the error:
-- Performing Test BLAS_F2C_DOUBLE_WORKS - Failed

-- Performing Test BLAS_F2C_FLOAT_WORKS

after I change to v4, make runtest can go through properly.

@ekcheng
Copy link

ekcheng commented Sep 11, 2016

Can someone point me to the commit(s) that made cuDNN v5 work?

@lukeyeager
Copy link
Contributor

@ekcheng: #4159

@vguptai
Copy link

vguptai commented Feb 23, 2018

@ekcheng

You can try this fork and let me know if it suffices.

https://github.com/vgupta-ai/py-faster-rcnn

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests