tensorflow-wavenet | A TensorFlow implementation of DeepMind 's WaveNet paper | Machine Learning library

by ibab Python Version: Current License: MIT

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

kandi X-RAY | tensorflow-wavenet Summary

tensorflow-wavenet is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. tensorflow-wavenet 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.

A TensorFlow implementation of DeepMind's WaveNet paper

Support

Quality

Security

License

Reuse

Support

tensorflow-wavenet has a medium active ecosystem.

It has 5345 star(s) with 1291 fork(s). There are 267 watchers for this library.

It had no major release in the last 6 months.

There are 161 open issues and 117 have been closed. On average issues are closed in 78 days. There are 14 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of tensorflow-wavenet is current.

Quality

tensorflow-wavenet has 0 bugs and 18 code smells.

Security

tensorflow-wavenet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

tensorflow-wavenet code analysis shows 0 unresolved vulnerabilities.

There are 2 security hotspots that need review.

License

tensorflow-wavenet 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

tensorflow-wavenet 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.

tensorflow-wavenet saves you 740 person hours of effort in developing the same functionality from scratch.

It has 1706 lines of code, 89 functions and 10 files.

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

Top functions reviewed by kandi - BETA

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

Creates the embeddings
Create an embedding table
Creates a bias variable
Create a tf Variable
Predict probability for a waveform
Generate the causal layer
Convolution layer
Creates the generator
Main thread
Randomize a list of files
Return a list of all files in the given directory
Load generic audio files
Computes the loss
Create the causal layer
Create a causal convolution layer
Create the network
Creates a seed from a given audio file
Start threads
Decode mu - law transformation
Save checkpoint to logdir
Get arguments
Try to load a previously saved checkpoint
Compute the probability for the given waveform
Validate the given arguments
Write the waveform to a wav file

Get all kandi verified functions for this library.

tensorflow-wavenet Key Features

No Key Features are available at this moment for tensorflow-wavenet.

tensorflow-wavenet Examples and Code Snippets

tensorflow-wavenet,Usage

Python

Lines of Code : 5

License : Permissive (BSD-3-Clause)

Copy

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dr4-mkcl0-sx11 h#,hh,iy,w,el,ax,l,aw,q,ax,r,eh,r,l,ay,h#
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UTTERANCE_NAME SEQUENCE_OF_PHONES
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Community Discussions

Trending Discussions on tensorflow-wavenet

reading files in google cloud machine learning

QUESTION

reading files in google cloud machine learning

Asked 2017-Mar-13 at 14:06

I tried to run tensorflow-wavenet on the google cloud ml-engine with gcloud ml-engine jobs submit training but the cloud job crashed when it was trying to read the json configuration file:

...

ANSWER

Answered 2017-Mar-13 at 14:06

Python's open function cannot read files from GCS. You will need to use a library capable of doing so. TensorFlow includes one such library:

Source https://stackoverflow.com/questions/42761075

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

Vulnerabilities

No vulnerabilities reported

Install tensorflow-wavenet

You can download it from GitHub.
You can use tensorflow-wavenet 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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