soobinseo / attentive-neural-process Goto Github PK
View Code? Open in Web Editor NEWA Pytorch Implementation of Attentive Neural Process
License: Apache License 2.0
A Pytorch Implementation of Attentive Neural Process
License: Apache License 2.0
The paper specifically mentions that they do not use attention in the latent path. Was there a reason that you added it into the latent path in your repo?
Thank you for sharing the code.
According to the paper, Appendix A 2nd paragraph, dropout is not used for attention.
In line 205, the residual and result are concatenated, but I think they should be added elementwise and then passed through a layer_norm (Figure 8 ANP paper). I wonder if there is some reason for this modification.
Thanks,
Deep Pandey
In networ.py BCELoss has the default settings, which (looking both for pytorch1.1 and pytorch0.4) does the mean reduction. However, the KL divergence function (also in network.py) seems to be using the sum reduction. Intuitively, either both should be sum or both mean. Is this a bug or is this correct?
Thanks!
Hi,
Thanks for your implementation!
I am a little confused about result = t.cat([residual, result], dim=-1)
in line 205 as you mentioned very important. Why do you need to concatenate the original residual result ?
Hi everyone,
There is the following code which load “checkpoint_50.pth.tar”, but I didn't find it in the project, please help to get the file.
"state_dict = t.load('./checkpoint/checkpoint_50.pth.tar')"
Hi. i am very interested in your code. My problem is to know if it is possible to use it for language translation. If it is the case how?
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.