wangxuhongcn / apan Goto Github PK
View Code? Open in Web Editor NEWLicense: MIT License
License: MIT License
🔨Work Item
Issue Description:
I am facing an error despite following the provided guide and creating a new environment with Python 3.6.13, PyTorch version 1.5.0, DGL version 0.5.2, and numpy version 1.19. The specific error I encounter is as follows:
"""from pytorch_lightning.metrics.functional import accuracy, auroc, average_precision, roc, f1
ModuleNotFoundError: No module named ‘pytorch_lightning’"""
To Reproduce:
Steps to reproduce the behavior:
Create a new environment with Python 3.6.13 using a virtual environment or conda.
Install the required packages with specific versions:
Copy code
pip install torch==1.5.0
pip install dgl==0.5.2
pip install numpy==1.19
Run the code that utilizes the pytorch_lightning module.
Observe the error mentioned above.
Expected behavior:
I expected the code to run without any errors and to find the pytorch_lightning module without any issues.
Environment:
Python version: 3.6.13
PyTorch version: 1.5.0
DGL version: 0.5.2
Numpy version: 1.19
Additional context:
I cannot proceed by installing an older version of PyTorch, DGL, or numpy, as my device requires specific versions. I seek assistance in resolving this issue while using the specified versions and considering my specific device specifications.
Thank you for your help!
Hi Xuhong,
Thanks for providing this nice open-sourced code!
In Section 4.4 of your paper (Arxiv, March version), you mentioned "the number of message passing layer is 2". Is this referring to two-layer of self-attention when aggregating from the mailbox, or two-layer when delivering the mails? In your code, it seems that both these two procedures have one-layer.
Thanks in advance.
Best,
Hongkuan
Hi,thanks for providing this nice open-sourced code!
NotImplementedError will be reported when inheriting EdgeCollator to process data and the reason I can not find.
File "/dgl/dataloading/base.py", line 230, in sample_blocks
raise NotImplementedError
Hi Xuhong,
Thanks for providing this nice open-sourced code!
I have missed the mistake of "AttributeError: 'TemporalEdgeCollator' object has no attribute 'block_sampler'"
Thanks in advance.
Hello, teacher, can you give me your ppt of the paper, I would like to use it during the group meeting,Thank you.
Hii Xuhong, thanks a lot for your promising and effective work and codes!! I have one concern about how to implement the continual training & inference form of APAN. That is, e.g. assume the model has been trained and saved in data of several months and more data is given now. Only using the pretrained encoder and decoder model seems insufficient and unreasonable for continual training, since it also leverages the history mailbox and last-modified feature of each nodes in graph. Therefore, if I wanna train the model continuely with pretrained model, is it necessary to keep record of the final mailbox and embedding on each nodes at the end of the previous interval? Thanks in advance!! :)
Dear author of APAN,
Great work on your paper! I'm particularly interested in the model comparison between APAN and the other models, such as TGN, TGAT, JODIE
Could you please provide the code you used to produce the results in the following table?
+------------------+-------------------+-------------------+-------------------+
| Method | Wikipedia | Reddit | Alipay |
+------------------+-------------------+-------------------+-------------------+
| GAE | 74.85 (0.6) | 58.39 (0.5) | - |
| VGAE | 73.67 (0.8) | 57.98 (0.6) | - |
| GAT | 82.34 (0.8) | 64.52 (0.5) | 69.47 (0.4) |
| SAGE | 82.42 (0.7) | 61.24 (0.6) | 67.91 (0.5) |
| CIDNE | 75.89 (0.5) | 59.43 (0.6) | - |
| DyRep | 84.59 (2.2) | 62.91 (2.4) | 65.09 (1.0) |
| JODIE | 83.17 (0.5) | 59.90 (2.1) | 81.89 (0.7) |
| TGAT | 83.69 (0.7) | 65.56 (0.7) | 77.84 (0.9) |
| TGN | 88.56 (0.3) | 68.63 (0.7) | 84.01 (0.9) |
| APAN | 89.86 (0.3) | 65.34 (0.4) | 83.37 (0.7) |
+------------------+-------------------+-------------------+-------------------+
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.