Comments (3)
could really benefit from some outlining of the dependencies.
nomen
, torch
, etc. and what you're assuming about the environment.
I got this pretty absurd stack trace, and setting TMPDIR as an environment variable doesn't seem to do the trick.
It would also have helped to say that there's an assumption of an NVIDIA GPU.
I feel like I spent an inordinate amount of time trying to get your code to run (after reading your variational autoencoder article), and much of this could have been prevented with a few lines of environmental context in the README. =(
from variational-autoencoder.
Thanks @mathematicalmichael — you are right that this code is a few years old and needs to be updated
from variational-autoencoder.
@mathematicalmichael can you take a look at b43325e please?
It should suppress most of the warnings. Is that better now? Any other ways to make it easier to understand? I'm not sure I'm using tf.datasets in the simplest way, but I think feed_dict's are more intuitive than tfrecords...
I also added an environment.yml
file for anaconda with the latest tensorflow version.
from variational-autoencoder.
Related Issues (20)
- Graphs for pyTorch version HOT 3
- Adaptation to CNN HOT 1
- SystemExit HOT 4
- unable to open file: name = 'dat/binarized_mnist.hdf5' HOT 10
- Tensor size mismatch in VariationalMeanField.forward
- Why not average over batch dimension? HOT 6
- Interpretation of each dimension on the shape HOT 1
- I very much hope that you can also give this paper Code implementation HOT 3
- Possible error in loss function HOT 2
- the expected_log_likelihood is not a expected value, but only an log likelihood HOT 1
- Size of output weights file HOT 2
- Beta lower than one HOT 11
- AttributeError: module 'flow' has no attribute 'InverseAutoregressiveFlow'
- Surprising results with no convergence HOT 4
- A question regarding q_z HOT 2
- Regarding the loss function HOT 1
- Follow up on why inputs must be between 0 and 1 HOT 1
- Dataset is lost
- Working version for Python 3+
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 variational-autoencoder.