tv_weight = 0 => attempt to index upvalue 'module' (a nil value)

[alehander92]

Hey, I am trying to run the example on Ubuntu, only CPU with

th neural_style.lua -style_image examples/inputs/picasso_selfport1907.jpg -content_image examples/inputs/brad_pitt.jpg -output_image profile.png -model_file models/nin_imagenet_conv.caffemodel -proto_file models/train_val.prototxt -num_iterations 1000 -seed 123 -content_layers relu0,relu3,relu7,relu12 -style_layers relu0,relu3,relu7,relu12 -content_weight 10 -style_weight 1000 -image_size 256 -optimizer adam -gpu -1 -tv_weight 0

I am using -tv_weight because otherwise it's producing only gray images with loss 0 and I saw 149

I am getting

Running optimization with ADAM  
/usr/bin/lua5.1: /usr/local/share/lua/5.1/nn/Container.lua:67: 
In 1 module of nn.Sequential:
/usr/local/share/lua/5.1/nn/Container.lua:59: attempt to index upvalue 'module' (a nil value)
stack traceback:
    /usr/local/share/lua/5.1/nn/Container.lua:59: in function </usr/local/share/lua/5.1/nn/Container.lua:58>
    [C]: in function 'xpcall'
    /usr/local/share/lua/5.1/nn/Container.lua:58: in function 'rethrowErrors'
    /usr/local/share/lua/5.1/nn/Sequential.lua:58: in function 'updateGradInput'
    neural_style.lua:320: in function 'opfunc'
    /usr/local/share/lua/5.1/optim/adam.lua:33: in function 'adam'
    neural_style.lua:343: in function 'main'
    neural_style.lua:500: in main chunk
    [C]: in function 'dofile'
    /usr/local/lib/luarocks/rocks/trepl/scm-1/bin/th:145: in main chunk
    [C]: ?

WARNING: If you see a stack trace below, it doesn't point to the place where this error occured. Please use only the one above.
stack traceback:
    [C]: in function 'error'
    /usr/local/share/lua/5.1/nn/Container.lua:67: in function 'rethrowErrors'
    /usr/local/share/lua/5.1/nn/Sequential.lua:58: in function 'updateGradInput'
    neural_style.lua:320: in function 'opfunc'
    /usr/local/share/lua/5.1/optim/adam.lua:33: in function 'adam'
    neural_style.lua:343: in function 'main'
    neural_style.lua:500: in main chunk
    [C]: in function 'dofile'
    /usr/local/lib/luarocks/rocks/trepl/scm-1/bin/th:145: in main chunk
    [C]: ?

[htoyryla]

This may not help in your case, but I would not use adam with nin-imagenet as my first choice. Nin-imagenet appears more difficult to get to converge and l-bfgs is definitely better in that.

[alehander92]

I am downloading the VGG 19 layers one now, I just wondered if that's a sign that something else on my system is not ok(or a bug)

[htoyryla]

You can use l-bfgs with nin-imagenet, just leave out -optimizer adam.

But there is probably something wrong in your setup. Running the same I get the following. Are you sure you have the correct model? Md5sum gives 8fbacb8dd696607876386e34ff68a84a models/nin_imagenet_conv.caffemodel

th neural_style.lua -style_image examples/inputs/picasso_selfport1907.jpg -content_image examples/inputs/brad_pitt.jpg -output_image profile.png -model_file models/nin_imagenet_conv.caffemodel -proto_file models/train_val.prototxt -num_iterations 1000 -seed 123 -content_layers relu0,relu3,relu7,relu12 -style_layers relu0,relu3,relu7,relu12 -content_weight 10 -style_weight 1000 -image_size 256 -optimizer adam -gpu -1 -tv_weight 0

Successfully loaded models/nin_imagenet_conv.caffemodel
MODULE data UNDEFINED
warning: module 'data [type 5]' not found
conv1: 96 3 11 11
cccp1: 96 96 1 1
cccp2: 96 96 1 1
conv2: 256 96 5 5
cccp3: 256 256 1 1
cccp4: 256 256 1 1
conv3: 384 256 3 3
cccp5: 384 384 1 1
cccp6: 384 384 1 1
conv4-1024: 1024 384 3 3
cccp7-1024: 1024 1024 1 1
cccp8-1024: 1000 1024 1 1
Setting up content layer    2   :   relu0   
Setting up style layer      2   :   relu0   
Setting up content layer    9   :   relu3   
Setting up style layer      9   :   relu3   
Setting up content layer    16  :   relu7   
Setting up style layer      16  :   relu7   
Setting up content layer    28  :   relu12  
Setting up style layer      28  :   relu12  
Running optimization with ADAM  
Iteration 50 / 1000 
  Content 1 loss: 116326.865234 
  Content 2 loss: 364734.375000 
  Content 3 loss: 197101.347656 
  Content 4 loss: 1452.863007   
  Style 1 loss: 139646.621704   
  Style 2 loss: 172335.678101   
  Style 3 loss: 99164.207458    
  Style 4 loss: 3.526320    
  Total loss: 1090765.484481    

[alehander92]

I guess so, but the error persists.
-tv_weight 0 => error
(-tv_weight default) =>
adam => loss 0, gray image
l-bfgs => actually nothing happens, exits immediately aft

Running optimization with L-BFGS    
<optim.lbfgs>   creating recyclable direction/step/history buffers  
<optim.lbfgs>   function value changing less than tolX  ```

[htoyryla]

Nin-imagenet-conv may be a bit difficult to get started with some inputs. Usually it helps to try again a couple of times (with random seed). Leave out the -seed parameter and try again a few times.

On the other hand, on my computer it starts ok with your parameters including -seed 123 so something else is now different in your setup.

Check the model file with md5sum and compare with mine in my previous comment.

[3DTOPO]

Install my pull request #97 and it will fix "function value changing less than tolX" error. Note that when I submitted it it was free of conflicts but does not appear to be the case anymore.