act-tensorflow | Adaptive Computation Time algorithm in Tensorflow | Machine Learning library

by DeNeutoy Python Version: Current License: No License

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

kandi X-RAY | act-tensorflow Summary

act-tensorflow is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Example Codes applications. act-tensorflow has no vulnerabilities and it has low support. However act-tensorflow has 1 bugs and it build file is not available. You can download it from GitHub.

Adaptive Computation Time algorithm in Tensorflow

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Quality

Security

License

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act-tensorflow has a low active ecosystem.

It has 252 star(s) with 54 fork(s). There are 16 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of act-tensorflow is current.

Quality

act-tensorflow has 1 bugs (1 blocker, 0 critical, 0 major, 0 minor) and 4 code smells.

Security

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

act-tensorflow code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

act-tensorflow 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

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

act-tensorflow 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.

act-tensorflow saves you 152 person hours of effort in developing the same functionality from scratch.

It has 379 lines of code, 19 functions and 8 files.

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

Top functions reviewed by kandi - BETA

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

Create an ACTModel
Generate data from PTB data
Read PTB data from file
Run a single epoch
Return a config object
Build vocabulary
Reads words from a file
Convert a file to a list of word ids
Loads PTB data from file
Return a Config object for the given conf

Get all kandi verified functions for this library.

act-tensorflow Key Features

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

act-tensorflow Examples and Code Snippets

No Code Snippets are available at this moment for act-tensorflow.

Community Discussions

Trending Discussions on act-tensorflow

Unsupported Image Format when trying to load an image from a response body

QUESTION

Unsupported Image Format when trying to load an image from a response body

Asked 2019-Sep-14 at 05:20

Starting from the gotham-rs routing example, I am trying to make a REST API that extracts an image from a request body so that it can be analyzed. I upload the image to the server with the following cURL command:

...

ANSWER

Answered 2019-Sep-14 at 05:20

The problem is that the request body has both http headers and image data. You need to parse it somehow according to RFC 7578.

Surprisingly I couldn't find a ready-made decent MIME multipart/form-data parser crate. The following code works, but it resorts to extremely crude regex split instead of proper parsing. Also, it omits the tensor model training part:

Source https://stackoverflow.com/questions/57929505

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

Vulnerabilities

No vulnerabilities reported

Install act-tensorflow

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