neuraltalk | numpy project for learning Multimodal Recurrent Neural | Machine Learning library

by karpathy Python Version: Current License: No License

X-Ray Key Features Code Snippets(1)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | neuraltalk Summary

neuraltalk is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Numpy, Neural Network applications. neuraltalk has no bugs, it has no vulnerabilities, it has build file available and it has medium support. You can download it from GitHub.

NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.

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Support

neuraltalk has a medium active ecosystem.

It has 5322 star(s) with 1351 fork(s). There are 442 watchers for this library.

It had no major release in the last 6 months.

There are 26 open issues and 12 have been closed. On average issues are closed in 18 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of neuraltalk is current.

Quality

neuraltalk has 0 bugs and 0 code smells.

Security

neuraltalk has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

neuraltalk code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

neuraltalk does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

neuraltalk releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

neuraltalk saves you 712 person hours of effort in developing the same functionality from scratch.

It has 1646 lines of code, 49 functions and 19 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed neuraltalk and discovered the below as its top functions. This is intended to give you an instant insight into neuraltalk implemented functionality, and help decide if they suit your requirements.

Predicts LSTM
Compute the y - value of the maximum value of the y - axis
Performs a forward computation
Decode a generator
Backpropagate backward
Calculate the sum of npicts
Predict the model
Predict from a batch of features

Get all kandi verified functions for this library.

neuraltalk Key Features

No Key Features are available at this moment for neuraltalk.

neuraltalk Examples and Code Snippets

theia,Training your own RNN on the Flickr or Coco datasets,Fetch data

Shell

Lines of Code : 1

License : Permissive (MIT)

Copy

sh fetch-data.sh

Community Discussions

Trending Discussions on neuraltalk

How to use reset_states(states) function in Keras?

QUESTION

How to use reset_states(states) function in Keras?

Asked 2017-Nov-04 at 13:26

I'm trying to set the LSTM internal state before training each batch. I'm sharing my test code and findings, hoping to find an answer and help others that are addressing similar problems.

In particular, for each data I have a feature X (which doesn't change over time) and a sequence P = p1, p2, p3,... p30. The goal is: given X and p1,p2,p3 predict p4, p5, .. p30.

To this aim, I want to initialize the hidden state of an LSTM with X, as done in several works (e.g., neuraltalk), then the LSTM has to be fit with p1,p2,p3 to predict p4,..,p30. This initialization is needed before each batch (batch_size=1), therefore I need to have the control of the LSTM states initialization. Considerint this question Initializing LSTM hidden state Tensorflow/Keras I've tested the following code:

First of all I've added some prints in the reset_states() function defined in recurrent.py, in order to understand what exactly happens.

...

ANSWER

Answered 2017-Nov-04 at 13:26

As you may read here, value parameter sets a value by which a variable should be initialized. So when you call tf.global_variables_initializer().run() your states are initialized with values defined here:

Source https://stackoverflow.com/questions/47034892

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install neuraltalk

You can download it from GitHub.
You can use neuraltalk like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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