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Early Termination of training:Progress 19.42% #2

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qxde01 opened this issue Jul 20, 2018 · 7 comments
Open

Early Termination of training:Progress 19.42% #2

qxde01 opened this issue Jul 20, 2018 · 7 comments

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@qxde01
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qxde01 commented Jul 20, 2018

nv: 1032440, ne: 987454
Need 0.257797 Mb for storing second-order degrees

Generating a corpus for negative samples..

Using vectorized operations
lr 0.020144, Progress 19.42%
Calculations took 12.13 s to run

@xgfs
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xgfs commented Jul 20, 2018

There is definetely a couple of weird things here: number of nodes is larger than the number of edges, and the graph seems almost disconnected. Are you sure you have the correct data preprocessing/data format?

@qxde01
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qxde01 commented Jul 20, 2018

There are thousands of subgraphs, and no connection between them. data preprocessing use https://github.com/xgfs/verse/tree/master/python ,and verse can train correctly.
My computer has 24cpu and 256G memory.
Thanks.

@xgfs
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xgfs commented Jul 20, 2018

If most of the nodes lie in small disconnected subgraphs, node2vec will be much faster (with unknown quality). From the output I would assume that process is ran correctly, and it finishes - most likely, the printing of the progress is not called (it's only called from thread id=0).

@qxde01
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qxde01 commented Jul 20, 2018

I found different places:
If I use the parameter -nwalks 80, the training will be interrupted:
./node2vec -input rela.bscr -output embedding.bin -dim 256 -nwalks 80
and use default nwalks ,training is correct :
./node2vec -input rela.bscr -output embedding.bin -dim 256

@xgfs
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xgfs commented Jul 20, 2018

Interesting. Could you run the default couple of times and see if it crashes anytime?

@qxde01
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qxde01 commented Jul 26, 2018

if nwalks < 40 , the training will not be interrupted.

@xgfs
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xgfs commented Jul 30, 2018

If you post the graph file, I will try to look at the issue some time in the future. If you find a bug yourself, please notify/submit a PR.

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