Matlab - CuDNN Error with MatConvNet
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I am trying to use Matlab and Matconvnet for Deep Learning and particularly to work on this implementation : Finding Tiny Faces.
I am working on Ubuntu 16.04, with Cuda 9 (GTX 1080Ti). For the implementation, I am using Matlab R2017b. I have follow the instructions to install and compile Matconvnet vl_compilenn('enableImreadJpeg', true) and I have passed the furnished test.
When I try to run the first function bboxes = tiny_face_detector('data/demo/selfie.jpg', './selfie.png', 0.5, 0.1, 1) I have an error with CuDNN :
Error using vl_nnconv
forward: cuDNN error [cudnn:
"/home/alexattia/Work/RecVis/tiny/matconvnet/matlab/src/bits/impl/nnconv_cudnn.cu":141
(CUDNN_STATUS_BAD_PARAM)]
Error in dagnn.Conv/forward (line 11)
outputs{1} = vl_nnconv(...
Error in dagnn.Layer/forwardAdvanced (line 85)
outputs = obj.forward(inputs, {net.params(par).value}) ;
Error in dagnn.DagNN/eval (line 91)
obj.layers(l).block.forwardAdvanced(obj.layers(l)) ;
Error in tiny_face_detector (line 130)
net.eval(inputs);
Do you have any idea how to solve this ?
Thank you very much in advance.
matlab ubuntu deep-learning cudnn
edited Dec 19 '17 at 11:26
talonmies
58.9k17126192
asked Dec 19 '17 at 11:10
A. Attia
4571820
add a comment |
up vote
0
down vote
favorite
I am trying to use Matlab and Matconvnet for Deep Learning and particularly to work on this implementation : Finding Tiny Faces.
I am working on Ubuntu 16.04, with Cuda 9 (GTX 1080Ti). For the implementation, I am using Matlab R2017b. I have follow the instructions to install and compile Matconvnet vl_compilenn('enableImreadJpeg', true) and I have passed the furnished test.
When I try to run the first function bboxes = tiny_face_detector('data/demo/selfie.jpg', './selfie.png', 0.5, 0.1, 1) I have an error with CuDNN :
Error using vl_nnconv
forward: cuDNN error [cudnn:
"/home/alexattia/Work/RecVis/tiny/matconvnet/matlab/src/bits/impl/nnconv_cudnn.cu":141
(CUDNN_STATUS_BAD_PARAM)]
Error in dagnn.Conv/forward (line 11)
outputs{1} = vl_nnconv(...
Error in dagnn.Layer/forwardAdvanced (line 85)
outputs = obj.forward(inputs, {net.params(par).value}) ;
Error in dagnn.DagNN/eval (line 91)
obj.layers(l).block.forwardAdvanced(obj.layers(l)) ;
Error in tiny_face_detector (line 130)
net.eval(inputs);
Do you have any idea how to solve this ?
Thank you very much in advance.
matlab ubuntu deep-learning cudnn
edited Dec 19 '17 at 11:26
talonmies
58.9k17126192
asked Dec 19 '17 at 11:10
A. Attia
4571820
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I am trying to use Matlab and Matconvnet for Deep Learning and particularly to work on this implementation : Finding Tiny Faces.
I am working on Ubuntu 16.04, with Cuda 9 (GTX 1080Ti). For the implementation, I am using Matlab R2017b. I have follow the instructions to install and compile Matconvnet vl_compilenn('enableImreadJpeg', true) and I have passed the furnished test.
When I try to run the first function bboxes = tiny_face_detector('data/demo/selfie.jpg', './selfie.png', 0.5, 0.1, 1) I have an error with CuDNN :
Error using vl_nnconv
forward: cuDNN error [cudnn:
"/home/alexattia/Work/RecVis/tiny/matconvnet/matlab/src/bits/impl/nnconv_cudnn.cu":141
(CUDNN_STATUS_BAD_PARAM)]
Error in dagnn.Conv/forward (line 11)
outputs{1} = vl_nnconv(...
Error in dagnn.Layer/forwardAdvanced (line 85)
outputs = obj.forward(inputs, {net.params(par).value}) ;
Error in dagnn.DagNN/eval (line 91)
obj.layers(l).block.forwardAdvanced(obj.layers(l)) ;
Error in tiny_face_detector (line 130)
net.eval(inputs);
Do you have any idea how to solve this ?
Thank you very much in advance.
matlab ubuntu deep-learning cudnn
edited Dec 19 '17 at 11:26
talonmies
58.9k17126192
asked Dec 19 '17 at 11:10
A. Attia
4571820
I am trying to use Matlab and Matconvnet for Deep Learning and particularly to work on this implementation : Finding Tiny Faces.
I am working on Ubuntu 16.04, with Cuda 9 (GTX 1080Ti). For the implementation, I am using Matlab R2017b. I have follow the instructions to install and compile Matconvnet vl_compilenn('enableImreadJpeg', true) and I have passed the furnished test.
When I try to run the first function bboxes = tiny_face_detector('data/demo/selfie.jpg', './selfie.png', 0.5, 0.1, 1) I have an error with CuDNN :
Error using vl_nnconv
forward: cuDNN error [cudnn:
"/home/alexattia/Work/RecVis/tiny/matconvnet/matlab/src/bits/impl/nnconv_cudnn.cu":141
(CUDNN_STATUS_BAD_PARAM)]
Error in dagnn.Conv/forward (line 11)
outputs{1} = vl_nnconv(...
Error in dagnn.Layer/forwardAdvanced (line 85)
outputs = obj.forward(inputs, {net.params(par).value}) ;
Error in dagnn.DagNN/eval (line 91)
obj.layers(l).block.forwardAdvanced(obj.layers(l)) ;
Error in tiny_face_detector (line 130)
net.eval(inputs);
Do you have any idea how to solve this ?
Thank you very much in advance.
matlab ubuntu deep-learning cudnn
matlab ubuntu deep-learning cudnn
edited Dec 19 '17 at 11:26
talonmies
58.9k17126192
asked Dec 19 '17 at 11:10
A. Attia
4571820
edited Dec 19 '17 at 11:26
talonmies
58.9k17126192
asked Dec 19 '17 at 11:10
A. Attia
4571820
edited Dec 19 '17 at 11:26
talonmies
58.9k17126192
edited Dec 19 '17 at 11:26
talonmies
58.9k17126192
edited Dec 19 '17 at 11:26
talonmies
58.9k17126192
58.9k17126192
asked Dec 19 '17 at 11:10
A. Attia
4571820
asked Dec 19 '17 at 11:10
A. Attia
4571820
asked Dec 19 '17 at 11:10
A. Attia
4571820
4571820
add a comment |
add a comment |
1 Answer
1
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0
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Most probably, your CPU setting is still on. If you have changed that to GPU, the images and and params of the network need to be of type gpuArray.
answered 18 hours ago
h612
619
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
Most probably, your CPU setting is still on. If you have changed that to GPU, the images and and params of the network need to be of type gpuArray.
answered 18 hours ago
h612
619
add a comment |
up vote
0
down vote
Most probably, your CPU setting is still on. If you have changed that to GPU, the images and and params of the network need to be of type gpuArray.
answered 18 hours ago
h612
619
add a comment |
up vote
0
down vote
up vote
0
down vote
Most probably, your CPU setting is still on. If you have changed that to GPU, the images and and params of the network need to be of type gpuArray.
answered 18 hours ago
h612
619
Most probably, your CPU setting is still on. If you have changed that to GPU, the images and and params of the network need to be of type gpuArray.
answered 18 hours ago
h612
619
answered 18 hours ago
h612
619
answered 18 hours ago
h612
619
answered 18 hours ago
h612
619
619
add a comment |
add a comment |
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