Comments (1)
For this you need to prepare separate adj files, adj_train
that defines the connectivity among training nodes only and adj_full
that defines connectivity among nodes seen or unseen during training. adj_full
will be used during the validation & test phases.
For example, on the Flickr graph, we perform inductive training (I think it aligns with your use case). In the config yaml you can specify that the training is inductive:
Then when loading the graph for training, the model will separately load adj_train
and adj_full
, and information of adj_full
is unseen during training:
Here is an example of the data format conversion script (GraphSAINT format --> shaDow format): https://github.com/facebookresearch/shaDow_GNN/blob/main/para_graph_sampler/graph_engine/frontend/loader.py#L43
In this section, we defined all the data files required to train shaDow-GNN (you don't need to prepare those optional files, as they will be auto-generated):
https://github.com/facebookresearch/shaDow_GNN#general-shadow-format
Please let me know of any additional questions. Thanks.
from shadow_gnn.
Related Issues (8)
- compile.sh doesn't run on Windows HOT 6
- Windows : Building wheel for ParallelSampler (setup.py) ... error HOT 2
- Can it be run on CPU? HOT 9
- Please share the requirement file. HOT 4
- Please provide the wheel file for ParallelSampler, if possible. HOT 3
- How to disable shaDow_GNN sampling? HOT 5
- How to solve the metric in data
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from shadow_gnn.