wanfang13 / c-mil Goto Github PK

My environment is Ubuntu16.04, CUDA9.0, Cudnn7.0. When I run the training code, I run into the following problem: cannot create a directory, and cannot write files to disk

The command th train_cmil.lua 0 SSW gives the following output:
{
0 : "/home/ubuntu/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th"
1 : "0"
2 : "SSW"
-2 : "-e"
-5 : "/home/ubuntu/torch/install/bin/luajit"
-3 : "package.path="/home/ubuntu/.luarocks/share/lua/5.1/?.lua;/home/ubuntu/.luarocks/share/lua/5.1/?/init.lua;/home/ubuntu/torch/install/share/lua/5.1/?.lua;/home/ubuntu/torch/install/share/lua/5.1/?/init.lua;"..package.path; package.cpath="/home/ubuntu/.luarocks/lib/lua/5.1/?.so;/home/ubuntu/torch/install/lib/lua/5.1/?.so;"..package.cpath"
-4 : "-e"
-1 : "local k,l,_=pcall(require,"luarocks.loader") _=k and l.add_context("trepl","scm-1")"
}
SETTINGS:
{
NUM_EPOCHS : 20
DATASET : "VOC2007"
annealFromEpoch3 : true
LearningRate : 0.005
model_path : "model/CMIL.lua"
ContinuationFunc : "Log"
AnnealEpoch : 10
SUBSET_FOR_TESTING : "test"
ifContinuation : true
PROPOSALS : "SSW"
BASE_MODEL : "VGGF"
LearningRateAneal : 0.0005
RESULT_SAVE_FOLDER : "VOC2007/VGGF/CMIL-SSW"
lambda : 0.7
DetRate : 0.1
CO_TRAINING_PATTERN : "Anneal0.63"
CliqueNTOP : 200
SUBSET : "trainval"
test_epoch_num : 20
}
Pre-processing voc dataset and VGG models...
VOC has been processed
VGG models has been processed
Done
Loading Dataset in: /home/ubuntu/C-MIL-master/data/datasets/VOC2007_SSW.t7
/home/ubuntu/torch/install/bin/luajit: cannot open </home/ubuntu/C-MIL-master/data/datasets/VOC2007_SSW.t7> in mode r at /home/ubuntu/torch/pkg/torch/lib/TH/THDiskFile.c:673
stack traceback:
[C]: at 0x7f7dfc8e8460
[C]: in function 'DiskFile'
/home/ubuntu/torch/install/share/lua/5.1/torch/File.lua:405: in function 'load'
dataset.lua:8: in main chunk
[C]: in function 'dofile'
train_cmil.lua:5: in main chunk
[C]: in function 'dofile'
...untu/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:150: in main chunk
[C]: at 0x00405d50

When I try to run the code that's what I get
Segmentation fault (core dumped)
When I tried to debug the code, I found that the code stop when it excute
local output = self.model:forward(inputs) in function Optim:optimize(optimMethod, inputs, targets, criterion, scale) in fbnn_Optim.lua file , line 145

I anyone could help I would be forever grateful

你们论文中关于示例选择器损失函数在y=1时为什么会是非凸的，为什么在λ=0时改造后的函数又变为凸性的？这个性质是如何变化的？

The question is above.

Best regards,

magemoumou

I have successfully compiled all things. Dataset and model are also processed.
During training, I got this error:

In 1 module of nn.ParallelTable:
In 2 module of nn.Sequential:
layers/ContinuationSubset.lua:42: attempt to call field 'ME_LocalConsistencyFast' (a nil value)
stack traceback:
        layers/ContinuationSubset.lua:42: in function 'compute_consistency_sorted'
        layers/ContinuationSubset.lua:141: in function 'ComputeIndsFast'
        layers/ContinuationSubset.lua:173: in function <layers/ContinuationSubset.lua:156>
        [C]: in function 'xpcall'
        ~/torch/install/share/lua/5.1/nn/Container.lua:63: in function 'rethrowErrors'
        ~/torch/install/share/lua/5.1/nn/Sequential.lua:44: in function <~/torch/install/share/lua/5.1/nn/Sequential.lua:41>
        [C]: in function 'xpcall'
        ~/torch/install/share/lua/5.1/nn/Container.lua:63: in function 'rethrowErrors'
        ~/torch/install/share/lua/5.1/nn/ParallelTable.lua:12: in function <~/torch/install/share/lua/5.1/nn/ParallelTable.lua:10>
        [C]: in function 'xpcall'
        ~/torch/install/share/lua/5.1/nn/Container.lua:63: in function 'rethrowErrors'
        ~/torch/install/share/lua/5.1/nn/Sequential.lua:44: in function 'forward'
        fbnn_Optim.lua:146: in function 'optimize'
        train_cmil.lua:94: in main chunk
        [C]: in function 'dofile'
        ...torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:150: in main chunk
        [C]: at 0x00405d50

It works if I exchange the comment of these two lines:
https://github.com/Winfrand/C-MIL/blob/410a66a70c131267093ed55762ad38ffe4740338/layers/ContinuationSubset.lua#L41-L42
So what's ME_LocalConsistencyFast about?