Hi,

The weights value discretisation functionality is only applicable with Frame_CUDA model, and not Frame.
Are you planning to add this feature on Frame model?

Thanks in advance,
Capucine

Is there anywhere I can change which board model to export to?

When I try to download the KITTI_road dataset with :
./tools/install_stimuli_gui.py
then I have selected KITTI_road dataset

And I get this error :

http://kitti.is.tue.mpg.de/kitti/data_road.zip
KITTI
Traceback (most recent call last):
File "./tools/install_stimuli_gui.py", line 140, in load_database
+ urllib.quote(fileName), target, progress)
File "/usr/lib64/python2.7/urllib.py", line 94, in urlretrieve
return _urlopener.retrieve(url, filename, reporthook, data)
File "/usr/lib64/python2.7/urllib.py", line 240, in retrieve
fp = self.open(url, data)
File "/usr/lib64/python2.7/urllib.py", line 208, in open
return getattr(self, name)(url)
File "/usr/lib64/python2.7/urllib.py", line 345, in open_http
h.endheaders(data)
File "/usr/lib64/python2.7/httplib.py", line 1013, in endheaders
self._send_output(message_body)
File "/usr/lib64/python2.7/httplib.py", line 864, in _send_output
self.send(msg)
File "/usr/lib64/python2.7/httplib.py", line 826, in send
self.connect()
File "/usr/lib64/python2.7/httplib.py", line 807, in connect
self.timeout, self.source_address)
File "/usr/lib64/python2.7/socket.py", line 553, in create_connection
for res in getaddrinfo(host, port, 0, SOCK_STREAM):
IOError: [Errno socket error] [Errno -2] Name or service not known

Python is a language that is gaining a lot of interest recently - most of the Neural Networks frameworks (e.g. Caffe and Tensorflow) support Python, which makes it a lot easier to use than C++

Are you planning on adding a Python API for N2D2 in the future?

Thanks for your answer

Hi
I'm trying to build N2D2 in CPU-only mode but can't de-activate the automatic CUDA build.
Is there a way to make without CUDA?
Thanks.

EDIT : Ok nevermind, there's a hidden USE_CUDA parameter.
You can build without CUDA by using

cmake .. -DUSE_CUDA=0

@olivierbichler-cea
It could be nice to be told in the documentation that it's possible, maybe even un-hide this parameter, i think many users would be glad to compile N2D2 for a CPU-only use.

in include/conv1.h:
static const BDATA_T conv1_biases[CONV1_NB_OUTPUTS] = {0, 0, 0, 0, 0, 0**, **};

Step to reproduce:
n2d2 /opt/N2D2/models/LeNet.ini -export C -nbbits 16 -calib -1

Hello,

When I try to do inference in the spiking domain with LeNet example present in "models/" (first, learn the model in frame domain using "LeNet.ini", and then test it in spike domain using "LeNet_spike.ini"), I have the following error:

Final recognition rate: 99.13% (error rate: 0.87%)
Sensitivity: 99.12% / Specificity: 99.90% / Precision: 99.12%
Accuracy: 99.83% / F1-score: 99.12% / Informedness: 99.02%

Importing weights from directory 'weights_range_normalized'.
Time elapsed: 5.12 s
Error: Could not open synaptic file: weights_range_normalized/conv1_weights.syntxt

When I verified in the folder where the simulation is held, I've seen that there is no directory called "weights_range_normalized". In the previous versions of N2D2, there was a folder with that name. I think that some changes made the directory disappeared and which caused this error.

Thank you for helping,
Nassim.

Hello !

I have red in N2D2 User Guide that it was possible to use a custom or handmade database for NN training. But I can't find further information on how to integrate those custom datanases in the said documentation, and how to use them for training.
Do you have further informations ?
Thank you by advance,

Best regards,

Edgar LEMAIRE
(Grenoble INP - Phelma & UGA, Internship @ LEAT (CNRS) w/ Spintec (CEA))

Hi,
Can anyone please help me in removing following error?

prachi@prachi-V530-15ICB:~/N2D2$ ./build/bin/n2d2 .models/mnist24_16c4s2_24c5s2_150_10.ini -learn 600000 -log 10000
Option -log: number of steps between logs [10000]
Option -learn: number of backprop learning steps [600000]
Loading network configuration file .models/mnist24_16c4s2_24c5s2_150_10.ini
Notice: Unused section in INI file
Time elapsed: 0.000194836 s
Error: Could not open INI file: .models/mnist24_16c4s2_24c5s2_150_10.ini

In the manual, the instructions for the compilation use cmake, but there is also a Makefile in the main directory. Do we get the same results from both methods ?
Moreover, in both cases, there is no install targets. How can we finish the installation after the compilation ?

Hi,

I tried to build on Windows using MinGW. I would like to avoid Visual Studio.

CMake configure and generate is ok, but an error occurs when building:

$ mingw32-make
[  0%] Building CXX object CMakeFiles/N2D2-OS.dir/src/Activation/LogisticActivation_Frame.cpp.obj
N2D2\src\Activation\LogisticActivation_Frame.cpp:1:0: warning: -fPIC ignored for target (all code is position independent)
 /*
 ^
In file included from N2D2/include/Environment.hpp:31:0,
                 from N2D2/include/Activation/Activation.hpp:24,
                 from N2D2/include/Activation/LogisticActivation.hpp:24,
                 from N2D2/include/Activation/LogisticActivation_Frame.hpp:24,
                 from N2D2\src\Activation\LogisticActivation_Frame.cpp:21:
N2D2/include/Network.hpp:43:22: fatal error: execinfo.h: No such file or directory
compilation terminated.
CMakeFiles\N2D2-OS.dir\build.make:62: recipe for target 'CMakeFiles/N2D2-OS.dir/src/Activation/LogisticActivation_Frame.cpp.obj' failed
mingw32-make[2]: *** [CMakeFiles/N2D2-OS.dir/src/Activation/LogisticActivation_Frame.cpp.obj] Error 1
CMakeFiles\Makefile2:66: recipe for target 'CMakeFiles/N2D2-OS.dir/all' failed
mingw32-make[1]: *** [CMakeFiles/N2D2-OS.dir/all] Error 2
makefile:128: recipe for target 'all' failed
mingw32-make: *** [all] Error 2

Would you have any suggestion to solve it ? Or am I stuck with VIsualStudio ?

Hello

After generating the HLS export and running vivado_hls on it, I'm trying to use the generated IP on Vivado, but the block design has a huge number of inputs (in_data_X_Y_q, in_data_X_Y_we, in_data_X_Y_ce, in_data_X_Y_address, in_data_X_Y_d and etc) and I'm not really sure how to connect them. What is the recommended way to do it?

Thank you

Hello,
I tried to run the aer_viewer to convert a video file(.mp4) to a spike encoding file (.dat) but i got the same error for different video. Do you know where does it come from? Thanks

./aer_viewer /home/vankhoa/IMRA_le/2_Dataset/Video/CarRacing.mp4
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[loadVideo] 46000573 events @ frame #840
[loadVideo] 46126933 events @ frame #844
[loadVideo] 46208923 events @ frame #847
[loadVideo] 46302339 events @ frame #851
[loadVideo] 46410207 events @ frame #857
[loadVideo] 46516388 events @ frame #863
[loadVideo] 46602131 events @ frame #867
[loadVideo] 46716089 events @ frame #872
[loadVideo] 46818998 events @ frame #876
[loadVideo] 46916410 events @ frame #880
[loadVideo] 47363918 events @ frame #885
[loadVideo] 47412902 events @ frame #898
[loadVideo] 47561337 events @ frame #901
[loadVideo] 47625200 events @ frame #902
[loadVideo] 47712966 events @ frame #903
[loadVideo] 47805432 events @ frame #904
[loadVideo] 47982576 events @ frame #906
[loadVideo] *** 47982576 events generated for 907 frames (36.28 s)
Floating point exception [floating point invalid operation]
backtrace() returned 22 addresses
./aer_viewer[0x600945]
/lib/x86_64-linux-gnu/libc.so.6(+0x354b0)[0x7fdbd323f4b0]
/usr/lib/x86_64-linux-gnu/libQt5XcbQpa.so.5(_ZN14QXcbConnection16touchDeviceForIdEi+0x328)[0x7fdbbe58af08]
/usr/lib/x86_64-linux-gnu/libQt5XcbQpa.so.5(_ZN14QXcbConnection15xi2SetupDevicesEv+0x118d)[0x7fdbbe58c44d]
/usr/lib/x86_64-linux-gnu/libQt5XcbQpa.so.5(_ZN14QXcbConnection17initializeXInput2Ev+0x126)[0x7fdbbe58ca86]
/usr/lib/x86_64-linux-gnu/libQt5XcbQpa.so.5(_ZN14QXcbConnectionC1EP19QXcbNativeInterfacebjPKc+0x301)[0x7fdbbe566891]
/usr/lib/x86_64-linux-gnu/libQt5XcbQpa.so.5(_ZN15QXcbIntegrationC1ERK11QStringListRiPPc+0x2ad)[0x7fdbbe569bad]
/usr/lib/x86_64-linux-gnu/qt5/plugins/platforms/libqxcb.so(+0x13ad)[0x7fdbbe63a3ad]
/usr/lib/x86_64-linux-gnu/libQt5Gui.so.5(ZN27QPlatformIntegrationFactory6createERK7QStringRK11QStringListRiPPcS2+0xa2)[0x7fdbd23d2d92]
/usr/lib/x86_64-linux-gnu/libQt5Gui.so.5(_ZN22QGuiApplicationPrivate25createPlatformIntegrationEv+0x4f4)[0x7fdbd23defc4]
/usr/lib/x86_64-linux-gnu/libQt5Gui.so.5(_ZN22QGuiApplicationPrivate21createEventDispatcherEv+0x2d)[0x7fdbd23dfecd]
/usr/lib/x86_64-linux-gnu/libQt5Core.so.5(_ZN16QCoreApplication4initEv+0x4f6)[0x7fdbd20a77e6]
/usr/lib/x86_64-linux-gnu/libQt5Core.so.5(_ZN16QCoreApplicationC1ER23QCoreApplicationPrivate+0x26)[0x7fdbd20a7856]
/usr/lib/x86_64-linux-gnu/libQt5Gui.so.5(_ZN15QGuiApplicationC1ER22QGuiApplicationPrivate+0x9)[0x7fdbd23e1cc9]
/usr/lib/x86_64-linux-gnu/libQt5Widgets.so.5(_ZN12QApplicationC2ERiPPci+0x3d)[0x7fdbd2998bcd]
/usr/local/lib/libopencv_highgui.so.3.2(+0x15c60)[0x7fdbd523ac60]
/usr/local/lib/libopencv_highgui.so.3.2(+0x18462)[0x7fdbd523d462]
/usr/local/lib/libopencv_highgui.so.3.2(cvNamedWindow+0x120)[0x7fdbd524a500]
./aer_viewer[0x919510]
./aer_viewer[0x439051]
/lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xf0)[0x7fdbd322a830]
./aer_viewer[0x439799]

Hi

I am building N2D2 without CUDA on ubuntu 14.04
The problem is echoed below:

`[ 97%] Generating ../bin/tests/class_CsvDataFile.passed
Test case "CsvDataFile" FAILED with 0 error(s), 2 failure(s), 10 success(es):
Test "read" FAILED (5/6):
Failure: "mat.at(i, 1) != 0.5 + i * 0.1 with values 0.6 != 0.6" line 46 in file /home/hamid/N2D2/N2D2-master/tests/DataFile/class_CsvDataFile.cpp
Test "write" FAILED (5/6):
Failure: "mat.at(i, 1) != 0.5 + i * 0.1 with values 0.6 != 0.6" line 70 in file /home/hamid/N2D2/N2D2-master/tests/DataFile/class_CsvDataFile.cpp

Test summary: FAIL
Number of test cases ran: 1
Tests that succeeded: 10
Tests with errors: 0
Tests that failed: 2
Tests skipped: 0
make[2]: *** [bin/tests/class_CsvDataFile.passed] Error 1
make[1]: *** [tests/CMakeFiles/run_class_CsvDataFile.dir/all] Error 2
make: *** [all] Error 2
`

I have use N2D2 to run on Nvidia Telsa P4 GPU, and I want to run on a new AI soc,in order to compare the performance of them.
How can I use N2D2 to run on a new AI soc,it is also a PCIE card.

Hi. I'm trying to use the tool to export the trained model into C_HLS codes as shown in the manual. However the tool prompts me that additional modules are needed for the export. I wonder if the module for C_HLS export is missing? It seems the only available export right now is CPP_cuDNN. Thanks.

Hi,

I believe there is a small problem with a header guard mismatch in include/Generator/LSTMCellGenerator.hpp. Lines 22-23 are:

#ifndef N2D2_LSTMCELLGENERATOR_H
#define N2D2_LSTMVCELLGENERATOR_H

The same name should be used on both lines.

Hello, I am having a little bit of trouble understanding how to use this kind of layer and I haven't found any examples...

What I want to do is to create the following block: Conv (without activation) -> BatchNorm -> ReLU .

As I understand it, the output size after normalization should remain unchanged, so I'm not sure about the NbOutputs option. It would help to see an example of an .ini file using this kind of combination.

Thank you!

Hello,
I tried to run the example to convert CNN to SNN (LeNet), by these two commands:
../build/bin/n2d2 "../models/LeNet.ini" -learn 6000000 -log 100000
../build/bin/n2d2 "../models/LeNet_Spike.ini" -test

And I ran into this error:
Option -test: perform testing
Loading network configuration file ../models/LeNet_Spike.ini
Layer: conv1 [Conv(Transcode_CUDA)]
Notice: Could not open configuration file: conv1.cfg
Notice: Unused section fc2.Target in INI file
Notice: Unused section fc2.config in INI file
Time elapsed: 0.882318 s
Error: Cell_Spike::addInput(): mapping length must be equal to the number of outputs

Do you know where does it come from?
Thanks

During the build process I'm getting the following

/N2D2-master/src/DeepNet.cpp: In member function ‘void N2D2::DeepNet::cTicks(N2D2::Time_T, N2D2::Time_T, N2D2::Time_T, bool)’:
/home/lonewalker/NN/N2D2-master/src/DeepNet.cpp:2068:13: error: variable ‘itBegin’ set but not used [-Werror=unused-but-set-variable]
itBegin = mLayers.begin(),
^~~~~~~
/home/lonewalker/NN/N2D2-master/src/DeepNet.cpp: In member function ‘void N2D2::DeepNet::initializeCMonitors(unsigned int)’:
/home/lonewalker/NN/N2D2-master/src/DeepNet.cpp:2157:5: error: variable ‘itBegin’ set but not used [-Werror=unused-but-set-variable]
itBegin = mLayers.begin(),
^~~~~~~
cc1plus: all warnings being treated as errors
CMakeFiles/N2D2-OS.dir/build.make:3302: recipe for target 'CMakeFiles/N2D2-OS.dir/src/DeepNet.cpp.o' failed
make[2]: *** [CMakeFiles/N2D2-OS.dir/src/DeepNet.cpp.o] Error 1
CMakeFiles/Makefile2:67: recipe for target 'CMakeFiles/N2D2-OS.dir/all' failed
make[1]: *** [CMakeFiles/N2D2-OS.dir/all] Error 2
Makefile:129: recipe for target 'all' failed
make: *** [all] Error 2

The import process of own databases is not very clear.
From my understanding each input dataset has to be saved in a separate file.
Is that right?

Is it possible to import a database, where the inputs are saved in one file,
and the desired labels are saved in a separate file?

Hello,
When I train a network with frame_CUDA, and then generate the folder weight_range_normalize for test with spike, sometimes the weight exceed the range [-1,1] and I can not use these weights for spike inference. Do you know about this?
Thanks

Hello,

I am currently trying to build a network for CIFAR-10 classification. I have tried some different topologies, but I only reach 66,7% on the test dataset (91% on learning) after 48 hours of training. Those topologies were inspired from tensorflow descriptions I could find on the net, but I am quite sure I am missing something as accuracy on test example should be much higher.

Consequently, I was wondering if you had an example INI file for CIFAR-10 (I didn't find any in the models directory) which provides satisfying results.

Thanks in advance,

Regards,

Edgar Lemaire
(PhD student @ Thales Research Technology and LEAT lab, CNRS & Université Cote d'Azur)

Did I missed something ?
here is (relevant part of) the log :

[ 10%] Building CXX object CMakeFiles/N2D2-OS.dir/src/Cell/DeconvCell_Frame_CUDA.cpp.o
In file included from /home/fred/dev/n2d2/N2D2/include/CudaContext.hpp:27:0,
                 from /home/fred/dev/n2d2/N2D2/include/Activation/LogisticActivation_Frame_CUDA.hpp:26,
                 from /home/fred/dev/n2d2/N2D2/include/Cell/Cell_Frame_CUDA.hpp:24,
                 from /home/fred/dev/n2d2/N2D2/include/Cell/DeconvCell_Frame_CUDA.hpp:25,
                 from /home/fred/dev/n2d2/N2D2/src/Cell/DeconvCell_Frame_CUDA.cpp:23:
/home/fred/dev/n2d2/N2D2/src/Cell/DeconvCell_Frame_CUDA.cpp: In member function ‘virtual void N2D2::DeconvCell_Frame_CUDA::initialize()’:
/home/fred/dev/n2d2/N2D2/src/Cell/DeconvCell_Frame_CUDA.cpp:78:64: error: too few arguments to function ‘cudnnStatus_t cudnnSetConvolution2dDescriptor(cudnnConvolutionDescriptor_t, int, int, int, int, int, int, cudnnConvolutionMode_t, cudnnDataType_t)’
                                         CUDNN_CROSS_CORRELATION));

gcc 5.4.0, linux 4.4.0-66, cuda 8.0, libcudnn 6.0.

Cheers.

HI,
I think there are few mistakes in the manual and in some comments in the code about the name of the KITTI dataset name.

We can find some "KITTY_Road_Database" instead of "KITTI_Road_Database" for example.

Is it an error of naming ? Or is it normal ?

http://www.cvlibs.net/datasets/kitti/eval_road.php

Hello I did as you said for #52 . Now when I try to run install_stimuli_gui.py , I get a MNIST file of size of 66 MB , whereas I should get it around 110MB (as per the message on gui). May be this is causing #51 . Can anyone plsease help me on this?

when I run 'make ./bin/n2d2_test' , I get this displayed,
'cc' is not recognized as an internal or external command,
operable program or batch file.
make: `bin/n2d2_test' is up to date.

How can I fix this?

Hello,
could you help me solve this error of Run the learning

~/N2D2-master/build/bin$ ./n2d2 "mnist24_16c4s2_24c5s2_150_10.ini" -learn 60000 -log 10000
Option -log: number of steps between logs [10000]
Option -learn: number of backprop learning steps [60000]
Loading network configuration file mnist24_16c4s2_24c5s2_150_10.ini
Warning: to use Frame_CUDA models, N2D2 must be compiled with CUDA enabled.
*** Using Frame model instead. ***
Notice: Unused section sp in INI file
Notice: Unused section sp.Transformation in INI file
Notice: Unused section conv1 in INI file
Notice: Unused section conv2 in INI file
Notice: Unused section fc1 in INI file
Notice: Unused section fc1.drop in INI file
Notice: Unused section fc2 in INI file
Notice: Unused section softmax in INI file
Notice: Unused section softmax.Target in INI file
Notice: Unused section common.config in INI file
Time elapsed: 0.000491815 s
Error: Could not open images file: /local/qwdr7777/n2d2_data/mnist/train-images-idx3-ubyte

Hello, do you have any example .ini that create a SNN and train with STDP? Thank you

Hello, thanks for the support, I just want to know where is the reference paper for the Poissonian spike generator that you used in N2D2.
As my understanding, the intensity is used to calculate the delay, and the variable delay will decide the periodmean is closer to the minmeanperiod or maxminperiod. Please correct me if I'm wrong. Thank you

Hi,

I want to see how N2D2 works in general. You have provided few application executable. Could you please tell me how can i export them with Vivado HLS. I am very new to this. If possible please tell me this from start to end.

Hello, I'm trying an experiment like training an ANN (1 layer FC) with MNIST, and then import the weights to a SNN with same structure to do inference on NMNIST. But there are two many options in the ini file that I don't understand, like should I choose the base model of the SNN as Transcode, or as Spike_Analog. And then there are two channels in the SNN, so the model is not similar.

I post the two ini file here, could you help me to check it.

the training ini to train ANN with back propagation on MNIST:

; Command:
; ./n2d2.sh "$N2D2_MODELS/LeNet.ini" -learn 6000000 -log 100000

DefaultModel=Frame_CUDA

; Database
[database]
Type=MNIST_IDX_Database
Validation=0.2 ; Use 20% of the dataset for validation

; Environment
[sp]
SizeX=32
SizeY=32
BatchSize=128

[sp.Transformation_1]
Type=ChannelExtractionTransformation
CSChannel=Gray

[sp.Transformation_2]
Type=RescaleTransformation
Width=[sp]SizeX
Height=[sp]SizeY

; Output layer (fully connected)
[fc1]
Input=sp
Type=Fc
NbOutputs=500
ActivationFunction=Rectifier
WeightsFiller=HeFiller
ConfigSection=common.config

[fc2]
Input=fc1
Type=Fc
NbOutputs=10
ActivationFunction=Linear
ConfigSection=common.config

[softmax]
Input=fc2
Type=Softmax
NbOutputs=[fc2]NbOutputs
WithLoss=1

[softmax.Target]

; Common config for static model
[common.config]
NoBias=0
WeightsSolver.LearningRate=0.05
WeightsSolver.Momentum=0.9
WeightsSolver.Decay=0.0005
Solvers.LearningRatePolicy=StepDecay
Solvers.LearningRateStepSize=[sp]_EpochSize
Solvers.LearningRateDecay=0.993
Solvers.Clamping=0.0:1.0

The test ini to import the weight from ANN to use on SNN:

DefaultModel=Transcode_CUDA

; Database
[database]
Type=N_MNIST_Database

; Environment
[env]
SizeX=32
SizeY=32
BatchSize=1
NbChannels=2
ConfigSection=env.config

[env.config]
ReadAerData=1

[env.Transformation_1]
Type=RescaleTransformation
Width=[env]SizeX
Height=[env]SizeY

; Output layer (fully connected)
[fc1]
Input=env
Type=Fc
NbOutputs=500
ConfigSection=common.config
ConfigSection(Spike_Analog)=common_Spike_Analog.config
ConfigSection(Spike_RRAM)=common_Spike_RRAM.config

[fc2]
Input=fc1
Type=Fc
NbOutputs=10
ConfigSection=common.config,fc2.config
ConfigSection(Spike_Analog)=common_Spike_Analog.config
ConfigSection(Spike_RRAM)=common_Spike_RRAM.config

[fc2.Target]

[fc2.config]
; Spike-based computing
TerminateDelta=4
BipolarThreshold=1

; Common config for static model
[common.config]
NoBias=0
WeightsSolver.LearningRate=0.005
Threshold=1.0
Refractory=10,000,000

; Common config for Spike_Analog model
[common_Spike_Analog.config]
EnableStdp=0
Threshold=50.0
StdpLtp=50,000,000
InhibitRefractory=1,000
Leak=100,000,000
BipolarIntegration=0
RefractoryIntegration=0
WeightsMinMean="1.0e-4; 10%"
WeightsMaxMean="1.0; 10%"
WeightsRelInit="0.67; 20%"
WeightIncrement="0.0017; 1%"
WeightIncrementDamping=-3
WeightDecrement="0.0007; 1%"
WeightDecrementDamping=0

; Common config for Spike_RRAM model
[common_Spike_RRAM.config]
EnableStdp=0
Threshold=1.52e-2
LtdProba=0.0007
LtpProba=0.0020
StdpLtp=50,000,000
InhibitRefractory=1,000
Leak=100,000,000
BipolarWeights=0
BipolarIntegration=0
RefractoryIntegration=0
WeightsMinMean="1.19e-5; 1.67e-5"
WeightsMaxMean="3.04e-4; 3.86e-5"
WeightsRelInit="2.0e-4; 20%"
WeightsMaxVarSlope=-1.7575
WeightsMaxVarOrigin=-17.1691
WeightsMinVarSlope=-0.0791
WeightsMinVarOrigin=-1.7081
WeightsSetProba="0.843; 0.197"
WeightsResetProba="0.992; 0.00748"
SynapticRedundancy=64

Thanks

Hello, when I do the cmake, I had to remove everything in the exec folder except the n2d2.cpp because if not it will lead to this error:
"add_executable cannot create target "n2d2" because another target with the same name already exists."

Then I did the make like usual. But when I test the model I ran on this error with CUDA, and if I set to Frame only, the model does not learn. Do you know what is the problem that I made? Thanks

sudo ./build/bin/n2d2 models/mnist24_16c4s2_24c5s2_150_10.ini -learn 40000000 -log 100000
Option -log: number of steps between logs [100000]
Option -learn: number of backprop learning steps [40000000]
Loading network configuration file models/mnist24_16c4s2_24c5s2_150_10.ini
Layer: conv1 [Conv(Frame_CUDA)]
Notice: Could not open configuration file: conv1.cfg

Shared synapses: 256

Virtual synapses: 30976

Inputs dims: 24 24 1

Outputs dims: 11 11 16

Warning: No monitor could be added to Cell: conv1
Layer: conv2 [Conv(Frame_CUDA)]
Notice: Could not open configuration file: conv2.cfg

Shared synapses: 2250

Virtual synapses: 36000

Inputs dims: 11 11 16

Outputs dims: 4 4 24

Warning: No monitor could be added to Cell: conv2
Layer: fc1 [Fc(Frame_CUDA)]
Notice: Could not open configuration file: fc1.cfg

Synapses: 57600

Inputs dims: 4 4 24

Outputs dims: 1 1 150

Warning: No monitor could be added to Cell: fc1
Layer: fc1.drop [Dropout(Frame_CUDA)]
Notice: Could not open configuration file: fc1.drop.cfg

Inputs dims: 1 1 150

Outputs dims: 1 1 150

Warning: No monitor could be added to Cell: fc1.drop
Layer: fc2 [Fc(Frame_CUDA)]
Notice: Could not open configuration file: fc2.cfg

Synapses: 1500

Inputs dims: 1 1 150

Outputs dims: 1 1 10

Warning: No monitor could be added to Cell: fc2
Layer: softmax [Softmax(Frame_CUDA)]
Notice: Could not open configuration file: softmax.cfg

Inputs dims: 1 1 10

Outputs dims: 1 1 10

Target: softmax (target value: 1 / default value: 0 / top-n value: 1)
Warning: No monitor could be added to Cell: softmax
Total number of neurons: 2640
Total number of nodes: 2640
Total number of synapses: 61606
Total number of virtual synapses: 126076
Total number of connections: 126076
Notice: Unused section softmax.Target in INI file
CUDNN failure: CUDNN_STATUS_NOT_INITIALIZED (1) in /home/kevin/IMRA_le/3_Program/SNN/N2D2/include/CudaContext.hpp:58
Time elapsed: 1.79893 s
Error: CUDNN failure: CUDNN_STATUS_NOT_INITIALIZED (1) in /home/kevin/IMRA_le/3_Program/SNN/N2D2/include/CudaContext.hpp:58

can N2D2 be used in the spike NN? If there are some examples to do the same work?

Ji,
It seems that N2D2 treats the option "ActivationFunction" for a layer of type "Fc".
But in the manual, "Fc" layer don't allow the option ActivationFunction.

Is it an oversight into the manual ?

I just cloned the master branch and tried to install N2D2 following the manual. My first try failed due to (I think) this line:

FIND_PACKAGE(OpenCV 2.0.0 REQUIRED)

Indeed I am using Fedora 26, that ships OpenCV 3.2.0. I change the aforementioned line for:

FIND_PACKAGE(OpenCV)  # NB: commenting the whole line was not working (CMake newbie...).

and the install process went fine. The integrated tests did not fail, and I was able to test the learning on MNIST as described in the manual.

So if there was no peculiar reason to pin the version of OpenCV to 2.0.0, you might want to get rid of this pinning.

Hello how can I remove the following error?

prachi@prachi-V530-15ICB:~/N2D2$ ./build/bin/n2d2 ./models/mnist24_16c4s2_24c5s2_150_10.ini -learn 600000 -log 10000
Option -log: number of steps between logs [10000]
Option -learn: number of backprop learning steps [600000]
Loading network configuration file ./models/mnist24_16c4s2_24c5s2_150_10.ini
Warning: to use Frame_CUDA models, N2D2 must be compiled with CUDA enabled.
*** Using Frame model instead. ***
Notice: Unused section sp in INI file
Notice: Unused section sp.Transformation in INI file
Notice: Unused section conv1 in INI file
Notice: Unused section conv2 in INI file
Notice: Unused section fc1 in INI file
Notice: Unused section fc1.drop in INI file
Notice: Unused section fc2 in INI file
Notice: Unused section softmax in INI file
Notice: Unused section softmax.Target in INI file
Notice: Unused section common.config in INI file
Time elapsed: 0.000383066 s
Error: Could not open images file: /local/prachi/n2d2_data/mnist/train-images-idx3-ubyte

Hello:

I want to test the exported network, but i have problem. How to solve this problem?

qwdr7777@ubuntu:~/N2D2-master/build/bin/export_CPP_cuDNN_float0$ sudo make ./n2d2_cudnn_test
[sudo] password for qwdr7777:
g++ -I./include/ -I./include/dnn/ -I./include/utils/ -std=c++0x n2d2_cudnn_test.cpp -o n2d2_cudnn_test
In file included from ./include/cpp_utils.hpp:22:0,
from ./include/n2d2_cudnn_inference.hpp:25,
from n2d2_cudnn_test.cpp:32:
./include/typedefs.h:88:21: fatal error: ap_cint.h: No such file or directory
#include <ap_cint.h>
^
compilation terminated.
make: *** [n2d2_cudnn_test] Error 1

C export in integers has stopped working (tested with , -nbbits 8, -nbbits 16 and -nbbits 32)

$ n2d2 $N2D2_ROOT/models/LeNet.ini -export C
[...]
Exporting Test dataset to "export_C_int8/stimuli"....................
Generating C export to "export_C_int8":
-> Generating cell conv1
Time elapsed: 1.79093 s
Error: Can't export a non-integral double as integral parameter.

Step to reproduce:

n2d2 N2D2/models/LeNet.ini -learn 6000 -log 3000
n2d2 N2D2/models/LeNet.ini -export C

Running the command:
./n2d2.sh "../../../tuto/tutorial.ini" -learn 1 -log 1

I get lot of errors with gnuplot, here is an example:

gnuplot> if (!exists("multiplot")) set term png size 800,600 enhanced large
                                                                      ^
         line 0: unrecognized terminal option

Linux distribution: Red Hat Enterprise Linux Server release 6.7 (Santiago)
Gnuplot version: gnuplot 4.6 patchlevel 5

Hello,
I have a problem when I do "make" on step 3 compilation. How to solve this?

esl@ubuntu:~/N2D2-master/build$ cmake .. && make
-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - not found
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE
-- Found Gnuplot: /usr/bin/gnuplot (found version "5.0.3")
-- No PugiXML found
-- MongoDB not found.
-- Found CUDA: /usr/local/cuda-9.0 (found version "9.0")
-- Found CuDNN: /usr/include
-- CuDNN library status:
-- version: 7.0.5
-- include path: /usr/include
-- libraries: /usr/lib/x86_64-linux-gnu/libcudnn.so
-- Configuring done
-- Generating done
-- Build files have been written to: /home/esl/N2D2-master/build
[ 0%] Building NVCC (Device) object CMakeFiles/n2d2_lib_cuda.dir/src/containers/n2d2_lib_cuda_generated_CudaTensor.cu.o
[ 0%] Building NVCC (Device) object CMakeFiles/n2d2_lib_cuda.dir/src/n2d2_lib_cuda_generated_CEnvironment_CUDA_kernels.cu.o
[ 0%] Building NVCC (Device) object CMakeFiles/n2d2_lib_cuda.dir/src/n2d2_lib_cuda_generated_CMonitor_CUDA_kernels.cu.o
[ 0%] Building NVCC (Device) object CMakeFiles/n2d2_lib_cuda.dir/src/Solver/n2d2_lib_cuda_generated_SGDSolver_CUDA_Kernels.cu.o
/usr/local/cuda-9.0/include/thrust/detail/tuple.inl(276): warning: calling a constexpr host function("half_float::half::half") from a host device function("cons") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
detected during:
instantiation of "thrust::detail::cons<HT, TT>::cons() [with HT=half_float::half, TT=thrust::detail::cons<signed long, thrust::null_type>]"
/usr/local/cuda-9.0/include/thrust/tuple.h(213): here
instantiation of "thrust::tuple<T0, T1, T2, T3, T4, T5, T6, T7, T8, T9>::tuple() [with T0=half_float::half, T1=signed long, T2=thrust::null_type, T3=thrust::null_type, T4=thrust::null_type, T5=thrust::null_type, T6=thrust::null_type, T7=thrust::null_type, T8=thrust::null_type, T9=thrust::null_type]"
(276): here
instantiation of "thrust::detail::cons<HT, TT>::cons() [with HT=thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, TT=thrust::detail::cons<thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::null_type>]"
/usr/local/cuda-9.0/include/thrust/tuple.h(213): here
instantiation of "thrust::tuple<T0, T1, T2, T3, T4, T5, T6, T7, T8, T9>::tuple() [with T0=thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, T1=thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, T2=thrust::null_type, T3=thrust::null_type, T4=thrust::null_type, T5=thrust::null_type, T6=thrust::null_type, T7=thrust::null_type, T8=thrust::null_type, T9=thrust::null_type]"
/usr/local/cuda-9.0/include/thrust/system/cuda/detail/reduce.h(393): here
instantiation of "T thrust::cuda_cub::__reduce::ReduceAgent<InputIt, OutputIt, T, Size, ReductionOp>::impl::consume_range_impl(Size, Size, CAN_VECTORIZE) [with InputIt=thrust::cuda_cub::transform_input_iterator_t<thrust::tuple<thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::zip_iterator<thrust::tuple<thrust::device_ptr<half_float::half>, thrust::cuda_cub::counting_iterator_t, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>>, thrust::cuda_cub::__extrema::arg_minmax_f<half_float::half, signed long, thrust::less<half_float::half>>::duplicate_tuple>, OutputIt=thrust::tuple<thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type> *, T=thrust::tuple<thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, Size=signed long, ReductionOp=thrust::cuda_cub::__extrema::arg_minmax_f<half_float::half, signed long, thrust::less<half_float::half>>, CAN_VECTORIZE=thrust::cuda_cub::__reduce::is_true]"
/usr/local/cuda-9.0/include/thrust/system/cuda/detail/reduce.h(454): here
[ 6 instantiation contexts not shown ]
instantiation of "T thrust::cuda_cub::__extrema::extrema(thrust::cuda_cub::execution_policy &, InputIt, Size, BinaryOp, T *) [with Derived=thrust::cuda_cub::tag, InputIt=thrust::cuda_cub::transform_input_iterator_t<thrust::tuple<thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::zip_iterator<thrust::tuple<thrust::device_ptr<half_float::half>, thrust::cuda_cub::counting_iterator_t, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>>, thrust::cuda_cub::__extrema::arg_minmax_f<half_float::half, signed long, thrust::less<half_float::half>>::duplicate_tuple>, Size=signed long, BinaryOp=thrust::cuda_cub::__extrema::arg_minmax_f<half_float::half, signed long, thrust::less<half_float::half>>, T=thrust::tuple<thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::tuple<half_float::half, signed long, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>]"
/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(548): here
instantiation of "thrust::pair<ItemsIt, ItemsIt> thrust::cuda_cub::minmax_element(thrust::cuda_cub::execution_policy &, ItemsIt, ItemsIt, BinaryPred) [with Derived=thrust::cuda_cub::tag, ItemsIt=thrust::device_ptr<half_float::half>, BinaryPred=thrust::less<half_float::half>]"
/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(572): here
instantiation of "thrust::pair<ItemsIt, ItemsIt> thrust::cuda_cub::minmax_element(thrust::cuda_cub::execution_policy &, ItemsIt, ItemsIt) [with Derived=thrust::cuda_cub::tag, ItemsIt=thrust::device_ptr<half_float::half>]"
/usr/local/cuda-9.0/include/thrust/detail/extrema.inl(75): here
instantiation of "thrust::pair<ForwardIterator, ForwardIterator> thrust::minmax_element(const thrust::detail::execution_policy_base &, ForwardIterator, ForwardIterator) [with DerivedPolicy=thrust::cuda_cub::tag, ForwardIterator=thrust::device_ptr<half_float::half>]"
/usr/local/cuda-9.0/include/thrust/detail/extrema.inl(153): here
instantiation of "thrust::pair<ForwardIterator, ForwardIterator> thrust::minmax_element(ForwardIterator, ForwardIterator) [with ForwardIterator=thrust::device_ptr<half_float::half>]"
/home/esl/N2D2-master/src/Solver/SGDSolver_CUDA_Kernels.cu(394): here

/usr/local/cuda-9.0/include/thrust/functional.h(611): warning: calling a host function("half_float::detail::operator << ::half_float::half, ::half_float::half> ") from a host device function("thrust::less< ::half_float::half> ::operator () const") is not allowed

/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(61): error: calling a host function("half_float::detail::operator << ::half_float::half, ::half_float::half> ") from a device function("thrust::cuda_cub::__extrema::arg_min_f< ::half_float::half, long, ::thrust::less< ::half_float::half> > ::operator ()") is not allowed

/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(61): error: identifier "half_float::detail::operator << ::half_float::half, ::half_float::half> " is undefined in device code

/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(63): error: calling a host function("half_float::detail::operator << ::half_float::half, ::half_float::half> ") from a device function("thrust::cuda_cub::__extrema::arg_min_f< ::half_float::half, long, ::thrust::less< ::half_float::half> > ::operator ()") is not allowed

/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(63): error: identifier "half_float::detail::operator << ::half_float::half, ::half_float::half> " is undefined in device code

/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(92): error: calling a host function("half_float::detail::operator << ::half_float::half, ::half_float::half> ") from a device function("thrust::cuda_cub::__extrema::arg_max_f< ::half_float::half, long, ::thrust::less< ::half_float::half> > ::operator ()") is not allowed

/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(92): error: identifier "half_float::detail::operator << ::half_float::half, ::half_float::half> " is undefined in device code

/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(94): error: calling a host function("half_float::detail::operator << ::half_float::half, ::half_float::half> ") from a device function("thrust::cuda_cub::__extrema::arg_max_f< ::half_float::half, long, ::thrust::less< ::half_float::half> > ::operator ()") is not allowed

/usr/local/cuda-9.0/include/thrust/system/cuda/detail/extrema.h(94): error: identifier "half_float::detail::operator << ::half_float::half, ::half_float::half> " is undefined in device code

8 errors detected in the compilation of "/tmp/tmpxft_00000d89_00000000-6_SGDSolver_CUDA_Kernels.cpp1.ii".
CMake Error at n2d2_lib_cuda_generated_SGDSolver_CUDA_Kernels.cu.o.cmake:262 (message):
Error generating file
/home/esl/N2D2-master/build/CMakeFiles/n2d2_lib_cuda.dir/src/Solver/./n2d2_lib_cuda_generated_SGDSolver_CUDA_Kernels.cu.o

CMakeFiles/n2d2_lib_cuda.dir/build.make:77: recipe for target 'CMakeFiles/n2d2_lib_cuda.dir/src/Solver/n2d2_lib_cuda_generated_SGDSolver_CUDA_Kernels.cu.o' failed
make[2]: *** [CMakeFiles/n2d2_lib_cuda.dir/src/Solver/n2d2_lib_cuda_generated_SGDSolver_CUDA_Kernels.cu.o] Error 1
CMakeFiles/Makefile2:1920: recipe for target 'CMakeFiles/n2d2_lib_cuda.dir/all' failed
make[1]: *** [CMakeFiles/n2d2_lib_cuda.dir/all] Error 2
Makefile:94: recipe for target 'all' failed
make: *** [all] Error 2

I use Ubuntu 16.04, and install cuda-core-9-0, cuda-cudart-dev-9-0, cuda-cublas-dev-9-0, cuda-curand-dev-9-0, libcudnn7-dev.
The CUDA library path is
export PATH="/usr/local/cuda-9.0/bin${PATH:+:${PATH}}"
export LD_LIBRARY_PATH="/usr/local/cuda-9.0/lib64$LD_LIBRARY_PATH"

Hello,
I have a question about the difference between the number of output events in the "Neuron stats", and the read events in the "Synapse stats". Could you explain this difference?

Thanks,

On Windows, when I run the learning on mnist:
./n2d2 "mnist24_16c4s2_24c5s2_150_10.ini" -learn 600000 -log 10000
I get many non-fatal errors in console output:
'pgnuplot.exe' is not recognized as an internal or external command

Indeed the folder gnuplot/bin contains wgnuplot.exe and gnuplot.exe but no pgnuplot.exe.

Can you fix it in file Gnuplot.cpp ?

#ifdef WIN32
        mCmdPipe = _popen("pgnuplot.exe", "w");
#else
        mCmdPipe = popen("gnuplot", "w");
#endif

Hello,
For our project, I want to import my own dataset to N2D2.
It could be both images dataset or spike dataset from event camera like files .raw, .aedat, .dat, etc.
Do you have any tutorial for that function.
Thanks

Hello,
Can someone please help me i solving following issue?

prachi@prachi-V530-15ICB:~/N2D2/tools$ python install_stimuli_gui.py
Installation path of the stimuli [default is /local/prachi/n2d2_data]:
http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz
mnist
Traceback (most recent call last):
File "install_stimuli_gui.py", line 127, in load_database
os.makedirs(target)
File "/usr/lib/python2.7/os.py", line 150, in makedirs
makedirs(head, mode)
File "/usr/lib/python2.7/os.py", line 150, in makedirs
makedirs(head, mode)
File "/usr/lib/python2.7/os.py", line 150, in makedirs
makedirs(head, mode)
File "/usr/lib/python2.7/os.py", line 157, in makedirs
mkdir(name, mode)
OSError: [Errno 13] Permission denied: '/local'

Hello everyone, I'm currently facing an issue that I don't understand so much.

Issue

I'm trying to train a ResNet with N2D2 and I have the following error :
Couldn't open connection to gnuplot (is it in the PATH?)

Debug

Then I try to understand why this error is raised :

libstdc++.so.6!__cxxabiv1::__cxa_throw(void * obj, std::type_info * tinfo, void (*)(void *) dest) (\usr\src\debug\gcc-4.8.5-20150702\libstdc++-v3\libsupc++\eh_throw.cc:62)
N2D2::Gnuplot::Gnuplot(N2D2::Gnuplot * const this, const std::string & fileName) (\home\thales\N2D2\src\utils\Gnuplot.cpp:44)
N2D2::PoolCell::writeMap(const N2D2::PoolCell * const this, const std::string & fileName) (\home\thales\N2D2\src\Cell\PoolCell.cpp:95)
N2D2::PoolCellGenerator::generate(N2D2::Network & network, const N2D2::DeepNet & deepNet, N2D2::StimuliProvider & sp, const std::vector<std::shared_ptr<N2D2::Cell>, std::allocator<std::shared_ptr<N2D2::Cell> > > & parents, N2D2::IniParser & iniConfig, const std::string & section) (\home\thales\N2D2\src\Generator\PoolCellGenerator.cpp:211)
std::_Function_handler<std::shared_ptr<N2D2::Cell> (N2D2::Network&, N2D2::DeepNet const&, N2D2::StimuliProvider&, std::vector<std::shared_ptr<N2D2::Cell>, std::allocator<std::shared_ptr<N2D2::Cell> > > const&, N2D2::IniParser&, std::string const&), std::shared_ptr<N2D2::PoolCell> (*)(N2D2::Network&, N2D2::DeepNet const&, N2D2::StimuliProvider&, std::vector<std::shared_ptr<N2D2::Cell>, std::allocator<std::shared_ptr<N2D2::Cell> > > const&, N2D2::IniParser&, std::string const&)>::_M_invoke(std::_Any_data const&, N2D2::Network&, N2D2::DeepNet const&, N2D2::StimuliProvider&, std::vector<std::shared_ptr<N2D2::Cell>, std::allocator<std::shared_ptr<N2D2::Cell> > > const&, N2D2::IniParser&, std::string const&)(const std::_Any_data & __functor,  __args#0,  __args#1,  __args#2,  __args#3,  __args#4,  __args#5) (\usr\include\c++\4.8.2\functional:2057)
std::function<std::shared_ptr<N2D2::Cell> (N2D2::Network&, N2D2::DeepNet const&, N2D2::StimuliProvider&, std::vector<std::shared_ptr<N2D2::Cell>, std::allocator<std::shared_ptr<N2D2::Cell> > > const&, N2D2::IniParser&, std::string const&)>::operator()(N2D2::Network&, N2D2::DeepNet const&, N2D2::StimuliProvider&, std::vector<std::shared_ptr<N2D2::Cell>, std::allocator<std::shared_ptr<N2D2::Cell> > > const&, N2D2::IniParser&, std::string const&) const(const std::function<std::shared_ptr<N2D2::Cell>(N2D2::Network&, const N2D2::DeepNet&, N2D2::StimuliProvider&, const std::vector<std::shared_ptr<N2D2::Cell>, std::allocator<std::shared_ptr<N2D2::Cell> > >&, N2D2::IniParser&, const std::basic_string<char, std::char_traits<char>, std::allocator<char> >&)> * const this,  __args#0,  __args#1,  __args#2,  __args#3,  __args#4,  __args#5) (\usr\include\c++\4.8.2\functional:2471)
N2D2::CellGenerator::generate(N2D2::Network & network, const N2D2::DeepNet & deepNet, N2D2::StimuliProvider & sp, const std::vector<std::shared_ptr<N2D2::Cell>, std::allocator<std::shared_ptr<N2D2::Cell> > > & parents, N2D2::IniParser & iniConfig, const std::string & section) (\home\thales\N2D2\src\Generator\CellGenerator.cpp:45)
N2D2::DeepNetGenerator::generate(N2D2::Network & network, const std::string & fileName) (\home\thales\N2D2\src\Generator\DeepNetGenerator.cpp:249)
main(int argc, char ** argv) (\home\thales\N2D2\exec\n2d2.cpp:1739)

It seems that the construction of a N2D2::GnuPlot::GnuPlot object causes the error because the popen function returns NULL value.

Therefore, I print the strerror(errno) resulting in this issue and I have the following message : Cannot allocate memory

After some researches it seems that the fork function called by the popen is the only one that can generate this kind of error, so it make me think that it's maybe a configuration issue.

Configuration

I'm currently working into a Centos7 VM with the following configuration :

• RAM : 8192Mo
• Processors : 4 of Intel(R) Core(TM) i7-8650 CPU 1.9GHz 2.11 GHz
• Hard Drive : 100Go

Conclusions

This error seems to be a configuration error because the training of mnist24_16c4s2_24c5s2_150_10 model works perfectly fine.

On the ResNet models (18 and 50) error are thrown on the Utils::exec function where popen returns NULL too, so it comforts me in the idea that it's a configuration problem.

Here is an archive with the ini file I used : ResNet-mini.zip

Did you face this issue before ?

Bonjour,
pourriez vous m'aider à résoudre cette erreur du Run the learning

~/Desktop/N2D2-master/bin/exec$ ./n2d2 "mnist24_16c4s2_24c5s2_150_10.ini" -learn 600000 -log 10000Option -log: number of steps between logs [10000]
Option -learn: number of backprop learning steps [600000]
Loading network configuration file mnist24_16c4s2_24c5s2_150_10.ini
Notice: Unused section in INI file
Time elapsed: 0.000160913 s
Error: Could not open INI file: mnist24_16c4s2_24c5s2_150_10.in

Bonjour
lorsque je lance cette commande
./n2d2 "mnist24_16c4s2_24c5s2_150_10.ini" -learn 600000 -log 10000
un message d'erreur concernant CUDA s'affiche comme le suivant :
Option -log: number of steps between logs [10000]
Option -learn: number of backprop learning steps [600000]
Cuda failure: CUDA driver version is insufficient for CUDA runtime version (35) in /home/ahlem/Téléchargements/N2D2-master/include/CudaContext.hpp:34
Error: Cuda failure: CUDA driver version is insufficient for CUDA runtime version (35) in /home/ahlem/Téléchargements/N2D2-master/include/CudaContext.hpp:34

Hello,

Assuming a functional DNN written as a .ini file, and a training already done, I would like to be able to extract the output (the Target) of a particular frame.

The -test-idx options allows to test the neural network on specific frames, which creates a folder frames/ containing images with values in {-1, 0, 1}. What I would like to get instead, is the actual output that says e.g. 57% chance that's it's a car, 18% chance that it's a horse, etc.., the binary content with one float value per possible label.

Is there a possibility to do that within the current framework?

I also tried messing with the -export functions, but unfortunately it generates no Makefile to compile the generated files, it seems that either something is missing or i am missing something. I tried with the CPP export, since I would like to run it on my CPU.

Thanks for your answers

Il y a une anomalie avec N2D2 car j'obtiens des résultats différents avec deux versions de N2D2.

Version actuelle "21/03/2018": accuracy = 77.92 %
Version antérieure "16/03/2017": accuracy = 95.37 %

Ce problème est présent seulement pour les réseaux à spikes.

Je utilise la commande "n2d2 mnist28_300_10_Spike.ini -test" pour les deux versions.