Comments (5)
As is, probably not :(
One thing you can do is replace line 16 of generate.py with:
from lasagne.layers import Conv2DLayer as ConvLayer
This should allow you to import and run the code. The problem with this though is it does not handle padding of the VGG-19 convolutional layers correctly, so it will output different (perhaps slightly worse) results. At least this will run, albeit very slowly.
If anyone has an alternative CPU solution which produces the correct output, I would love to know!
Ryan
from neural-storyteller.
Thanks Ryan, I will try.
Perhaps it would be helpful to specify this in the read.me :)
Enza
from neural-storyteller.
Ryan,
Lasagne's documentation for layers.Conv2DLayer
says:
Theano’s underlying convolution (theano.tensor.nnet.conv.conv2d()) only supports pad=0 and pad='full'. This layer emulates other modes by cropping a full convolution or explicitly padding the input with zeros.
while the note for layers.corrmm.Conv2DMMLayer
reads:
Unlike lasagne.layers.Conv2DLayer, this layer properly supports pad='same'. It is not emulated. This should result in better performance.
To me it seems like using the former should yield the same results with pad=1
(equivalent to pad='same'
), albeit with some performance hit beyond simply the use of the CPU. I would like to test this but unfortunately I am not very familiar with Theano currently.
from neural-storyteller.
I'm completely new to these libraries, but I have a less-than-stellar NVIDIA GeForce GT 610 running on my machine and am experiencing the same error.
from neural-storyteller.
We are working on adding Caffe as an additional option, which works fine on both GPU and CPU. This will be included shortly.
from neural-storyteller.
Related Issues (20)
- generate story error HOT 1
- config.py
- Killed (also skip-thoughts) HOT 3
- How to create new posbias for custom encoder/decoder? HOT 2
- Skipthought.py HOT 1
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- Models adjust in config.py HOT 4
- Could I use the code to generate stories for commercial uses? HOT 1
- Generator.py transform.resize error
- Random Nearest captions followed by an error HOT 5
- Embedding captions... HOT 4
- ValueError: could not broadcast input array from shape (3600) into shape (2400)
- How to modify bias to generate longer stories?
- cannot allocate memory error,and i do not know how much RAM it needs HOT 1
- Fine tuning COCO HOT 1
- Have no access to download VGG19 parameters
- No such file or directory: '../uni_skip.npz.pkl' HOT 2
- vgg19.pkl link not available HOT 7
- Error in unzipping npz files
- load_model() takes 0 positional arguments but 2 were given anyone help please
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