keras-generative | Deep generative networks , coded with Keras | Machine Learning library

by tatsy Python Version: Current License: No License

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

kandi X-RAY | keras-generative Summary

keras-generative is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras, Neural Network applications. keras-generative has no bugs, it has no vulnerabilities and it has low support. However keras-generative build file is not available. You can download it from GitHub.

Keras VAEs and GANs ===. Keras implementation of various deep generative networks such as VAE and GAN.

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Security

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keras-generative has a low active ecosystem.

It has 122 star(s) with 27 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 16 have been closed. On average issues are closed in 525 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of keras-generative is current.

Quality

keras-generative has 0 bugs and 75 code smells.

Security

keras-generative has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

keras-generative code analysis shows 0 unresolved vulnerabilities.

There are 1 security hotspots that need review.

License

keras-generative 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

keras-generative releases are not available. You will need to build from source code and install.

keras-generative has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

keras-generative saves you 1305 person hours of effort in developing the same functionality from scratch.

It has 2929 lines of code, 259 functions and 26 files.

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

Top functions reviewed by kandi - BETA

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

Builds the model
Build a pair of decoders
Build the shared decoder
Build the pair of discriminator
Build the model
Build the decoder
Build the classifier
Build the discriminator layer
Train the model
Save the predicted images
Make a batch
Predict for a given sample
Save labeled images
Save images
Predict from y to x
Return a Conditional Dataset
Downloads a website
Download a file from Google Drive
Extract confirm token from response cookies
Calculate loss function
Calculate loss function
Call the loss function
Call the loss function
Calculate loss
Loads weights from a folder
Sample from a Gaussian distribution

Get all kandi verified functions for this library.

keras-generative Key Features

No Key Features are available at this moment for keras-generative.

keras-generative Examples and Code Snippets

No Code Snippets are available at this moment for keras-generative.

Community Discussions

Trending Discussions on keras-generative

ImportError: cannot import name 'normalize_data_format'

QUESTION

ImportError: cannot import name 'normalize_data_format'

Asked 2018-Nov-23 at 07:47

I have read an article Here and its pretty nice enough to understand. Given its implementation on GitHub. When I am trying to train at my own using given code it gives me an Import Error in this file at line 117 like following. I am using google Colab environment. Having some search over the error i got that the following line is compatible to keras version==2.2.2. I have also installed that yet not solved with the error. Please help me to get over it. By default keras version installed in colab is 2.2.4

...

ANSWER

Answered 2018-Nov-23 at 07:47

https://github.com/keras-team/keras/blob/master/keras/utils/conv_utils.py

master branch's conv_utils doesn't have normalize_data_format. some of the other branches do have it such as tf-keras branch. It is a trivial function here is its implementation:

Source https://stackoverflow.com/questions/53442190

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

Vulnerabilities

No vulnerabilities reported

Install keras-generative

You can download it from GitHub.
You can use keras-generative 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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