charrnn | General Tensorflow implementation of a RNN Character Level | Machine Learning library

by samre12 Python Version: Current License: MIT

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

kandi X-RAY | charrnn Summary

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

General Tensorflow implementation of a RNN Character Level Language Model based on Truncated Backpropagation Through Time (TBPTT)

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charrnn has a low active ecosystem.

It has 4 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

charrnn has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of charrnn is current.

Quality

charrnn has no bugs reported.

Security

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

License

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

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

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

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

Top functions reviewed by kandi - BETA

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

Get a logger .
Create a ConfigParser object from a filename .
Prints a message list to logger .
Prints a message to logger

Get all kandi verified functions for this library.

charrnn Key Features

No Key Features are available at this moment for charrnn.

charrnn Examples and Code Snippets

No Code Snippets are available at this moment for charrnn.

Community Discussions

Trending Discussions on charrnn

lstm dimension not match by tensorflow

Python numpy raises BadZipfile Error while trying to read uncompressed npz file

QUESTION

lstm dimension not match by tensorflow

Asked 2018-May-13 at 23:42

I construct a LSTM network, and my input's dimension is 100*100*83 ( batch_size=100, steps = 100, char_vector = 83). I build a two LSTM layers which has 512 hidden units.

...

ANSWER

Answered 2018-Jan-29 at 08:24

cell = tf.nn.rnn_cell.MultiRNNCell([drop for _ in range(num_layers)])

cell = tf.nn.rnn_cell.MultiRNNCell([drop])

because your given input tensor and produces tensor are not the same.

Source https://stackoverflow.com/questions/48494356

QUESTION

Python numpy raises BadZipfile Error while trying to read uncompressed npz file

Asked 2017-Jun-13 at 19:03

I am currently modifyiong this gist to save the state of the neural network using numpy .npz files. The problematic code uses the variables:

...

ANSWER

Answered 2017-Jun-13 at 19:03

by doing this:

Source https://stackoverflow.com/questions/44529555

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

Vulnerabilities

No vulnerabilities reported

Install charrnn

You can download it from GitHub.
You can use charrnn 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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