recurrentshop | Framework for building complex recurrent neural networks | Machine Learning library

by farizrahman4u Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | recurrentshop Summary

recurrentshop is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Keras applications. recurrentshop has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Framework for building complex recurrent neural networks with Keras

Support

Quality

Security

License

Reuse

Support

recurrentshop has a low active ecosystem.

It has 760 star(s) with 224 fork(s). There are 30 watchers for this library.

It had no major release in the last 6 months.

There are 43 open issues and 39 have been closed. On average issues are closed in 55 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of recurrentshop is current.

Quality

recurrentshop has no bugs reported.

Security

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

License

recurrentshop is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

recurrentshop 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 are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Generate an rnn layer
Builds the model
Convert x to a list
Performs a single step
Generate an RNN layer
Call the model
True if x is an optional input placeholder
Loads training data
Download BAbi - TASTA files
The RWA function
Create a model from a dictionary
Get a dictionary of cells
Generate batch data
RHN
Generate QRN cell
Adds a cell to the model
Returns the shape of a cell
Generate random data
Return the number of states in this sequence
Loads text from recurrentshop
Download data
The number of states
Serialize the function to its name
Create a Cell instance from a dictionary
Add a cell
Creates a matrix representation of a given sentence embedding
Deserialize a function

Get all kandi verified functions for this library.

recurrentshop Key Features

No Key Features are available at this moment for recurrentshop.

recurrentshop Examples and Code Snippets

No Code Snippets are available at this moment for recurrentshop.

Community Discussions

Trending Discussions on recurrentshop

using return_sequences in recurrentshop

Recurrentshop and Keras: multi-dimensional RNN results in a dimensions mismatch error

QUESTION

using return_sequences in recurrentshop

Asked 2018-May-04 at 05:52

I'm trying to write a custom recurrent layer using recurrentshop in Keras. The input is a sequence of length "timesteps" and the output should be the sequence of all timesteps outputs, hence I'm using return_sequences=True.

The recurrent model has two inputs, one of which is recurrent from the last time step. I'm using this layer similar to the reccurentshop example, but I keep getting errors saying "You must feed a value for placeholder tensor 'input_2' with dtype float". What am I doing wrong? The full code follows:

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ANSWER

Answered 2018-May-04 at 05:52

Turns out the problem was in the Lambda layer:

Source https://stackoverflow.com/questions/50133081

QUESTION

Recurrentshop and Keras: multi-dimensional RNN results in a dimensions mismatch error

Asked 2018-Jan-11 at 11:26

I have an issue with Recurrentshop and Keras. I am trying to use Concatenate and multidimensional tensors in a Recurrent Model, and I get dimension issue regardless of how I arrange the Input, shape and batch_shape.

Minimal code:

...

ANSWER

Answered 2018-Jan-11 at 10:29

Try this (the changed lines are commented):

Source https://stackoverflow.com/questions/48155026

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

Vulnerabilities

No vulnerabilities reported

Install recurrentshop

You can download it from GitHub.
You can use recurrentshop 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.