GNNLens2 is an interactive visualization tool for graph neural networks (GNN).

Related tags

Deep Learning Model Explanationvisualizationdeep-learningpytorchgraph-visualizationxaigraph-neural-networksgraph-representation-learningexplainabilitydgl
Overview

GNNLens2 is an interactive visualization tool for graph neural networks (GNN). It allows seamless integration with deep graph library (DGL) and can meet your various visualization requirements for presentation, analysis and model explanation. It is an open source version of GNNLens with simplification and extension.

Installation

Requirements

You can install Flask-CORS with

pip install -U flask-cors

Installation for the latest stable version

pip install gnnlens

Installation from source

If you want to try experimental features, you can install from source as follows:

git clone https://github.com/dmlc/GNNLens2.git
cd GNNLens2/python
python setup.py install

Verifying successful installation

Once you have installed the package, you can verify the success of installation with

import gnnlens

print(gnnlens.__version__)
# 0.1.0

Tutorials

We provide a set of tutorials to get you started with the library:

Team

HKUST VisLab: Zhihua Jin, Huamin Qu

AWS Shanghai AI Lab: Mufei Li, Wanru Zhao (work done during internship), Jian Zhang, Minjie Wang

SMU: Yong Wang

Comments
  • Support for heterogeneous graphs

    Support for heterogeneous graphs

    Thanks for this wonderful library. In writer.add_graph(), I saw that it only accepts homogeneous graphs, do you have any plans to support heterogeneous graphs?

    opened by Mrugankakarte 2
  • Is there any test about the limit of graph size?

    Is there any test about the limit of graph size?

    Hi there,

    I'm wondering if the limit of graph size has been tested, such as the maximal number of nodes and edges in the visualized graph? And the correspondence between the memory overhead/simulation time and the graph size also interests me. For example, how big the graph is that can be processed by the GNNLens2 within 10secs on a machine with 16 CPUs and 64GB memory?

    opened by LspongebobJH 1
  • Several update

    Several update

    1. Rename GNNVis to GNNLens
    2. Remove the examples folder, which will be fully replaced by the tutorials
    3. Rename gnnvis to python
    4. Rename gnnvis/mini_serve to python/gnnlens
    5. Update setup.py
    6. Add Writer
    opened by mufeili 0
  • Bump flask-cors from 3.0.0 to 3.0.9 in /gnnvis

    Bump flask-cors from 3.0.0 to 3.0.9 in /gnnvis

    Bumps flask-cors from 3.0.0 to 3.0.9.

    Release notes

    Sourced from flask-cors's releases.

    Release 3.0.9

    Security

    • Escape path before evaluating resource rules (thanks @​praetorian-colby-morgan). Prior to this, flask-cors incorrectly evaluated CORS resource matching before path expansion. E.g. "/api/../foo.txt" would incorrectly match resources for "/api/*" whereas the path actually expands simply to "/foo.txt"

    Release 3.0.8

    Fixes DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working

    Thank you @​juanmaneo and @​jdevera!

    Release 3.0.7

    Updated logging.warn to logging.warning (#234) Thanks Vaibhav

    Release 3.0.6

    Manual error in release process. Identical contents at 3.0.5.

    Release 3.0.5

    Fixes incorrect handling of regexes containg '[', and a few other special characters. https://github-redirect.dependabot.com/corydolphin/flask-cors/issues/212

    Release 3.0.4

    Handle response.headers being None. (Fixes issue #217) Thanks @​dusktreader for the improvement!

    Release 3.0.3

    Ensure that an Origin of '*' is never sent if supports_credentials is True (fixes Issue #202)

    • If always_send=True, and '*' is in the allowed origins, and a request is made without an Origin header, no Access-Control-Allow-Origins header will now be returned. This is breaking if you depended on it, but was a bug as it goes against the spec.

    Release 3.0.2

    Fixes Issue #187: regression whereby header (and domain) matching was incorrectly case sensitive. Now it is not, making the behavior identical to 2.X and 1.X.

    Release 3.0.1

    Fixes Issue #183: regression whereby regular expressions for origins with an "?" are not properly matched.

    Thanks @​di for the report!

    Changelog

    Sourced from flask-cors's changelog.

    3.0.9

    Security

    • Escape path before evaluating resource rules (thanks to Colby Morgan). Prior to this, flask-cors incorrectly evaluated CORS resource matching before path expansion. E.g. "/api/../foo.txt" would incorrectly match resources for "/api/*" whereas the path actually expands simply to "/foo.txt"

    3.0.8

    Fixes : DeprecationWarning: Using or importing the ABCs from 'collections' in Python 3.7. Thank you @​juanmaneo and @​jdevera for the contribution.

    3.0.7

    Updated logging.warn to logging.warning (#234) Thanks Vaibhav

    3.0.6

    Manual error in release process. Identical contents at 3.0.5.

    3.0.5

    Fixes incorrect handling of regexes containg [, and a few other special characters. Fixes Issue #212

    3.0.4

    Handle response.headers being None. (Fixes issue #217)

    3.0.3

    Ensure that an Origin of '*' is never sent if supports_credentials is True (fixes Issue #202)

    • If always_send=True, and '*' is in the allowed origins, and a request is made without an Origin header, no Access-Control-Allow-Origins header will now be returned. This is breaking if you depended on it, but was a bug as it goes against the spec.

    3.0.2

    Fixes Issue #187: regression whereby header (and domain) matching was incorrectly case sensitive. Now it is not, making the behavior identical to 2.X and 1.X.

    3.0.1

    Fixes Issue #183: regression whereby regular expressions for origins with an "?" are not properly matched.

    Commits

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    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies python 
    opened by dependabot[bot] 0
  • Unable to show the graph of ogbn-products

    Unable to show the graph of ogbn-products

    Hi, I follow the instructions in tutorial 1 and try to show the graph structure of ogbn-products. There is no error showed when I run the code, however, when I open the gnnlens website and select the ogbn-products graph in the graph selector, it shows nothing. I wonders what may cause this happen? Is it because the graph too large, or because the graph does not include the label? Hope I describe it clearly, if needed I could show my code.

    opened by EntongL 1
  • ImportError: cannot import name 'safe_join' from 'flask'

    ImportError: cannot import name 'safe_join' from 'flask'

    Since 2.1.0, flask deprecates safe_join, as elaborated in its release note here. For now, a workaround is to degrade flask to an older version like pip install Flask==2.0.3. This should be fixed in the future release of GNNLens2 by either restricting Flask version or follow the latest recommended practice.

    Credit to @SherylHYX for reporting the issue.

    bug 
    opened by mufeili 0
Releases(v0.1.0)
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Distributed (Deep) Machine Learning Community
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