The very recent paper on "Mask R-CNN" is really interesting. Is there somebody in the CNTK community who might implement it in CNTK and share?
We are not aware of a CNTK implementation. We will add this to our backlog. We always welcome community contributions.
Related
I am currently failing into find an easy and modular framework to link openAI gym or tensorflow or keras with omnet++ in such a way I can produce communication between each tool and have online learning.
There are tools like omnetpy and veins-gym, however one is very strict and not trustworthy (and no certainty into bridge with openAI, for example) and the other is really poor documented in such a way one person can’t taper how it is supposed to be incorporated into a project.
Being omnet so big project, how is it possible that it is so disconnected to ML world like this?
On top of that, I still will need to use federated learning, so a custom scrappy solution would be even more difficult.
I found various articles that say “we have used omnet++ and keras or tensorflow”, etc, but none of them shared their code, so it is kinda misterious how they did it.
Alternatively, I could use NS3, but as far as I know, it is very steeped to learn it. Some ML tools are well documented, apparently, for NS3. But since I didn’t tried to implement something in NS3 with those tools, I can’t know for sure. Omnet++ was easy to learn for what I need, changing to NS3 still seems a burden with no clear guarantees.
I would like to ask help in both senses:
if u have links regarding good middleware between omnetpp and openai-gym or keras or such, and you have used them, please share with me.
if u have experience with NS3 and ML using ML middleware to link NS3 with openai-gym and keras and so on, please share with me.
I will only be able to finish my POC if I manage to use Reinforcement Learning tooling online a omnet++ simulation (i.e., agent is deciding on simulation runtime which actions to take).
My project is actually complex, but the POC may be simple. I am relying in these tools because I have no sufficient experience to build a complex system translating a domain to another. So a help will be nice.
Thank You.
For example, will it eventually work? Does it work? What are the goals and plans? Where can we read about it.
Is tensorflow_transform a going concern for tf 2.0?
Absolutely! Development is ongoing. Issues are being actively discussed, PRs are being worked on and there have been several changes to the master branch this week.
will it eventually work? Does it work?
Yes it works now (in general at least). Perhaps if you are encountering some specific issue could ask a new question with what, specifically, isnt working for you.
What are the goals and plans? Where can we read about it.
The tensorflow team are really good at communicating plans via RFCs and doing development in the open. I am less familiar with work on tf-transform but all the signs are this is developed with the same culture. Check out:
the github repo
the official site
I'm trying to understand someone else's simple tensorflow model and they make use of contrib.layers.linear.
However I cannot find any information on this anywhere and it's not mentioned in the tensorflow documentation.
The tf.contrib.layers module has API documentation here. As you observed in your answer, the contrib APIs in TensorFlow are (especially) subject to change. The tf.contrib.layers.linear() function appears to have been removed, but you can use tf.contrib.layers.fully_connected(…, activation_fn=None) to achieve the same effect.
I managed to find the answer and felt it was still worth posting this to save others wasting their time.
"In general, tf.contrib contains contributed code. It is meant to contain features and contributions that eventually should get merged into core TensorFlow, but whose interfaces may still change, or which require some testing to see whether they can find broader acceptance.
Code in tf.contrib isn't supported by the Tensorflow team. It is included in the hope that it is helpful, but it might change or be removed at any time; there are no guarantees." source
According to what I can see in the Master branch, the function linear still exists in contrib.layers. It actually is a "simple alias which removes the activation_fn parameter":
linear = functools.partial(fully_connected, activation_fn=None)
Here is a link from the 1.0 branch (to increase link persistence).
Though, if the doc still shows it, the link to contrib.layers.linear seems indeed broken.
i'm looking for 4 best algorithms in neural network optimization. i need the names and any description ,learning method and topology is very helping me.
i think multilayer perceptron (MLP) is one of them but i'm not sure.
thank you all.
Your question is really wide. It's hard to answer because different optimizers have their pros and drawbacks. I would say that among the best today's optimizers you will find ADAM, RMSPROP, ADAGRAD and SGD with Nestov momentum. You can read about these methods (as well as others) here.
First of all, I agree that the question is indeed too broad, however, I would like to add some resorces I personaly found to be usefull in helping me answer this question. In doing so, I hope that this resources will help someone else in as much as they helped me. Here they are:
Sebastian Ruder Mod Yu Zeng's blog post.
Anish Singh Walia's discussion on this topic.
Chapter 8 of The deep learning book by an Goodfellow, Yoshua Bengio and Aaron Courville.
This post from the Morning paper by Adrian Colyer.
I hope this helps someone.
Is there a tool for visualizing a given java3d app's scenegraph? Just like there is tools for auto generating UML diagrams.
Edit: if not, is there any good free tools for drawing such graphs? os x
J3DWorkbench is very good. http://eclectic3d.net/
this Java 3D forum thread might help: http://www.java.net/forum/topic/javadesktop/java-desktop-technologies/java-3d/java3d-loaded-scene-info
August