modified the models/johnson.lua's network structure and got wrong results

[fcpi]

I tried to modified the models/johnson.lua's network structure, aimed to reduce running memory and shorten running time, just as follows:

model:add(pad(4, 4, 4, 4))
model:add(backend.SpatialConvolution(3, 32, 9, 9, 2, 2, 0, 0)) --src_stride=1
model:add(normalization(32))
model:add(nn.ReLU(true))
..........
..........
model:add(nn.SpatialFullConvolution(32, 3, 3, 3, 2, 2, 1, 1, 1, 1)) --source is SpatialConvolution
model:add(normalization(3))
model:add(nn.ReLU(true))

return model:add(nn.TVLoss(params.tv_weight))

and training dataSet is COCO, image_size=512, style_size=512, content_weight=10, style_weight=10, tv_weight=0.001, I also tried others content_weight and style_weight, it seemed it had no significant difference, here is my result image by tubingen_kandinsky.jpg

[fcpi]

I found the error, it need delete the last two lines in models/johnson.lua, "model:add(normalization(3))" and "model:add(nn.ReLU(true))". but I still want to know how to reduce running memory and shorten running time, I found it occupancied nearly 2.1G running memory at resolution 640*480 image and I think it can't run in a ios or android mobile phone

[Dmitry Ulyanov]

if you erase intermediate results as you go through the net during forward pass it will be much less memory

[fcpi]

I'm not very familiar with torch and my understanding is I do one "out = model.forward(input)", it actually has saved every layers outputs just like "pool3_feat = model.blobs('pool3').get_data()" in caffe. so if I want to erase intermediate results, I should modify torch's source code to manually release it. I saw "In symbolic programming, user declares the need by f=compiled([D]) instead. It also declares the boundary of computation, telling the system I only want to compute the forward pass. As a result, the system can free the memory of previous results, and share the memory between inputs and outputs." in Mxnet, Does torch exist some like "f=compiled([D])" to clear the intermediate state for me?