keras-contrib | Keras community contributions | Machine Learning library

 by   keras-team Python Version: Current License: MIT

kandi X-RAY | keras-contrib Summary

kandi X-RAY | keras-contrib Summary

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

Keras community contributions

            kandi-support Support

              keras-contrib has a medium active ecosystem.
              It has 1575 star(s) with 655 fork(s). There are 82 watchers for this library.
              It had no major release in the last 6 months.
              There are 155 open issues and 87 have been closed. On average issues are closed in 120 days. There are 36 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of keras-contrib is current.

            kandi-Quality Quality

              keras-contrib has 0 bugs and 0 code smells.

            kandi-Security Security

              keras-contrib has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              keras-contrib code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              keras-contrib is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              keras-contrib 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.
              Installation instructions, examples and code snippets are available.
              keras-contrib saves you 3589 person hours of effort in developing the same functionality from scratch.
              It has 7674 lines of code, 378 functions and 116 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed keras-contrib and discovered the below as its top functions. This is intended to give you an instant insight into keras-contrib implemented functionality, and help decide if they suit your requirements.
            • A DenseNet
            • Multi - layer dense block
            • Create a dense network
            • Convolution block
            • Wrap a Residual network
            • Helper function for convolutional convolution
            • Create a wide residual network
            • Convolutional CNN
            • Transition up block
            • Compute the jaccard distance between two points
            • Bottleneck bottleneck function
            • Extract image patches
            • Calculate the activation layer
            • Test for replace_import
            • Build the chain
            • Connects the convolutional layer
            • Build the convolution matrix
            • Basic block layer
            • Configure VOC
            • Extracts a list of pascal segmentation images
            • Parse image segmentation statistics
            • A WSNet CIFAR layer
            • Constructs a NASNet large network
            • Snet network
            • Configure the COC library
            • Extracts a list of pairwise segmentation images
            Get all kandi verified functions for this library.

            keras-contrib Key Features

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

            keras-contrib Examples and Code Snippets

            copy iconCopy
            python3 -m venv env
            source env/bin/activate
            pip install -r requirements.txt  

            Community Discussions


            ModuleNotFoundError: No module named 'keras_contrib'
            Asked 2021-Aug-02 at 20:25

            I installed keras_contrib using:



            Answered 2021-Aug-02 at 18:16

            When running 'pip install ' in the command line, it usually print information while installing the module. On some OSs, you can find the download location there. Otherwise, you can use the following command line code to download towards a precise directory:



            How to implement hierarchical model in Keras?
            Asked 2020-Nov-15 at 16:06

            I am trying to rebuild the model featured in

            The authors break text up into utterances (think of them like sentences), then use bi-directional LSTMs to combine these utterances, then use bi-directional LSTMs again, this time on the series of utterance representations and finish it off by using a CRF layer to predict the labels associated with every utterance.

            This is a visual of the model architecture: enter image description here

            Here is my attempt, implemented in Keras and using the CRF layer from



            Answered 2020-Nov-15 at 16:06

            I ended up using, which is maintained and works with tf2.



            Implementing gradient penalty loss with tensorflow 2
            Asked 2020-Apr-08 at 17:06

            Good morning,

            I am trying to implement the improved WGAN for 1D data as described on this paper:

            It has been implemented as an example in the keras-contrib github: Nevertheless, this implementation of the gradient penalty loss is not working anymore with tf2. K.gradients() returns [None].



            Answered 2020-Apr-08 at 17:06

            If you do what is proposed in the UPDATE, tf will just ignore the loss function

            With Tensorflow 2, it seems imposible to to this the old way. I finally change the code to adapt it to this way of creating models. What I suggest?

            1. Create the gen/disc models with keras
            2. Join them extending tf.keras.Model class like the WGAN of :


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


            No vulnerabilities reported

            Install keras-contrib

            For instructions on how to install Keras, see the Keras installation page. For contributor guidelines see


            Keras-contrib is deprecated. Use TensorFlow Addons.
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