tfgo | Tensorflow + Go , the gopher way | Machine Learning library

by galeone Go Version: Current License: Apache-2.0

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

kandi X-RAY | tfgo Summary

tfgo is a Go library typically used in Artificial Intelligence, Machine Learning, Tensorflow applications. tfgo has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

TensorFlow's Go bindings are hard to use: tfgo makes it easy!.

Support

Quality

Security

License

Reuse

Support

tfgo has a medium active ecosystem.

It has 2226 star(s) with 156 fork(s). There are 60 watchers for this library.

It had no major release in the last 6 months.

There are 17 open issues and 42 have been closed. On average issues are closed in 41 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tfgo is current.

Quality

tfgo has 0 bugs and 0 code smells.

Security

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

tfgo code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

tfgo is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

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

Installation instructions, examples and code snippets are available.

It has 1499 lines of code, 125 functions and 15 files.

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

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tfgo Key Features

No Key Features are available at this moment for tfgo.

tfgo Examples and Code Snippets

No Code Snippets are available at this moment for tfgo.

Community Discussions

Trending Discussions on tfgo

Opening Keras model with embedding layer in Tensorflow in Golang

QUESTION

Opening Keras model with embedding layer in Tensorflow in Golang

Asked 2018-Aug-20 at 19:39

I am trying to implement my Keras neural network in Go using the tfgo package. The model includes 2 regular inputs and two Keras embedding layers. It looks like this:

...

ANSWER

Answered 2018-Aug-20 at 19:39

So, it turns out that I did not need to specify the inputs for the embedding layers. I was actually structuring the input incorrectly. It should look like this:

Source https://stackoverflow.com/questions/51904143

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

Vulnerabilities

No vulnerabilities reported

Install tfgo

The core data structure of the TensorFlow's Go bindings is the op.Scope struct. tfgo allows creating new *op.Scope that solves the scoping issue mentioned above. Since we're defining a graph, let's start from its root (empty graph). We can now place nodes into this graphs and connect them. Let's say we want to multiply a matrix for a column vector and then add another column vector to the result. Here's the complete source code. The list of the available methods is available on GoDoc: http://godoc.org/github.com/galeone/tfgo.

Support

I love contributions. Seriously. Having people that share your same interests and want to face your same challenges it's something awesome. If you'd like to contribute, just dig in the code and see what can be added or improved. Start a discussion opening an issue and let's talk about it. Just follow the same design I use into the image package ("override" the same Tensor methods, document the methods, test your changes, ...).

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