Pytorch_geometric: How to implement other GraphSAGE Aggregator functions like Max Pool?

[sbonner0]

Thanks for all the great work on the package and sorry if this has been asked before.

I was wondering if it possible to use different aggregation functions, like Max-Pool or LSTM aggregation from the original GraphSAGE paper, with the existing SAGEConv layer? Looking at the documentation, it seems that only the mean aggregation is available.

[rusty1s]

Max-Pool is indeed possible, but we do not have an implementation for it. Feel free to add it if you like. A fast LSTM aggregation is currently possible, but I am working on it.

[sbonner0]

Hi, thanks so much for the reply. I would love to add it if I am able.
Would it be possibe to implemet it how it is in the paper (with a second paramter matrix W_pool) using the current SAGEConv layer? Or would I need to implement it from scratch using MessagePassing? Would you have any tips on where to start?

[rusty1s]

We should maybe first come up with a separate implementation and then decide how to merge the different variants. I suggest to copy most of the SAGEConv layer as a starting point. And yes, you need to introduce W_pool for the max aggregation.

[sbonner0]

Thanks - I'll hopefully get time to look at this over the next week.

[cluel01]

Hey guys, is there an update on the two aggregator functions ? Would be keen to know.

[sbonner0]

Hey - I am still planning to have a go at this as soon as possible, I was inundated with work since the lock down.
If you have any idea, or would like to help, I would be most grateful.

[jchaykow]

It looks like maybe you just have to add an additional function here maybe called scatter_maxpool or something?

[rusty1s]

torch-scatter does already support max reduction :)

[vijay2411]

Hi,
Is there any update on max Pool aggregator? I would love to know.
Also I think, can we not just change the aggregator value by letting pass an extra argument in SAGEConv constructor of torch_geometric/nn/conv/sage_conv.py ? Is there anything else that needs to be done? The aggregator value there is hard-coded as 'add'.
Thanks

Update 1: Okay, somehow my jupyter notebook still shows the previous implementation of Sage_conv.py, I checked the new code and see that the custom aggregator has been added, how are we supposed to pass it as an argument? just like aggr = 'max' right? Error reports

TypeError: __init__() got multiple values for keyword argument 'aggr', Line 36 sage_conv.py

Update 2: Okay, I think I need to reinstall torch_geometric in python.

Update 3: Okay, I am Unable to install the latest code! What to do????? I have uninstall and reinstall all binaries and the pytorch_geometric repo(with --no-cache-dir flag) ?? It says PyG 1.6.1 installed, but I still can't see this update.

HELP!!!!!! :/

Very Very Thanks

[rusty1s]

You can install from source:

pip install git+https://github.com/rusty1s/pytorch_geometric.git

or change the aggr flag after initialization:

conv = SAGEConv(...)
conv.aggr = 'max'