tensorflow-with-go | see blogpost for content description description | Runtime Evironment library

by nilsmagnus Python Version: Current License: No License

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kandi X-RAY | tensorflow-with-go Summary

tensorflow-with-go is a Python library typically used in Server, Runtime Evironment, Nodejs applications. tensorflow-with-go has no bugs, it has no vulnerabilities and it has low support. However tensorflow-with-go build file is not available. You can download it from GitHub.

see blogpost for content description description:.

Support

Quality

Security

License

Reuse

Support

tensorflow-with-go has a low active ecosystem.

It has 34 star(s) with 4 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 233 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tensorflow-with-go is current.

Quality

tensorflow-with-go has 0 bugs and 0 code smells.

Security

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

tensorflow-with-go code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

tensorflow-with-go 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

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

tensorflow-with-go has no build file. You will be need to create the build yourself to build the component from source.

tensorflow-with-go saves you 27 person hours of effort in developing the same functionality from scratch.

It has 73 lines of code, 3 functions and 2 files.

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

Top functions reviewed by kandi - BETA

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

Train the model .

Get all kandi verified functions for this library.

tensorflow-with-go Key Features

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

tensorflow-with-go Examples and Code Snippets

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

Community Discussions

Trending Discussions on tensorflow-with-go

Saving TF model trained with keras and then evaluated in Go

QUESTION

Saving TF model trained with keras and then evaluated in Go

Asked 2017-Sep-22 at 16:23

I'm trying to setup a classical MNIST challenge model with keras, then save the tensorflow graph and subsequently load it in Go and evaluate with some input. I've been following this article which supplies full code on github. Nils is using just tensorflow to setup the comp.graph but I would like to use keras. I managd to save the model the same way as he does

model:

...

ANSWER

Answered 2017-Sep-22 at 16:23

Your code should work fine. You're right about the cause of the nil-operation.

You just have to find the complete node name of your "inputNode".

From python, after your model definition, you can loop over the graph nodes and look for the complete name, in that way:

Source https://stackoverflow.com/questions/46366954

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

Vulnerabilities

No vulnerabilities reported

Install tensorflow-with-go

You can download it from GitHub.
You can use tensorflow-with-go 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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