tf-gnn-samples | TensorFlow implementations of Graph Neural Networks | Machine Learning library

by microsoft Python Version: Current License: MIT

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

kandi X-RAY | tf-gnn-samples Summary

tf-gnn-samples is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras applications. tf-gnn-samples 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.

TensorFlow implementations of Graph Neural Networks

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Quality

Security

License

Reuse

Support

tf-gnn-samples has a medium active ecosystem.

It has 871 star(s) with 229 fork(s). There are 35 watchers for this library.

It had no major release in the last 6 months.

There are 5 open issues and 16 have been closed. On average issues are closed in 23 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of tf-gnn-samples is current.

Quality

tf-gnn-samples has 0 bugs and 0 code smells.

Security

tf-gnn-samples has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

tf-gnn-samples code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

tf-gnn-samples 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

tf-gnn-samples 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.

tf-gnn-samples saves you 1205 person hours of effort in developing the same functionality from scratch.

It has 2714 lines of code, 165 functions and 33 files.

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

Top functions reviewed by kandi - BETA

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

Run the command line interface
Convert a GNNX model name to a generic model class
Restore model from saved_model_path
Convert a task type to a task class
Make a task output model
Implements the micro - f1 function
A worker for the data loading
Load a single sample
Add per - subtoken nodes to the graph
Creates a tf TensorInput model
Get embeddings for a single node
Implements a graph layer
Creates sparse edge mlp layer
Get the activation function
Get the aggregation function
Creates a graph layer
Creates a sparse layer
Creates a network layer
Create a GNN layer
Apply the graph representation of the graph
Loads the training data
Load training data
Load eval data from a path
Preprocess adjacency matrix
Load eval data from path
Load data

Get all kandi verified functions for this library.

tf-gnn-samples Key Features

No Key Features are available at this moment for tf-gnn-samples.

tf-gnn-samples Examples and Code Snippets

No Code Snippets are available at this moment for tf-gnn-samples.

Community Discussions

Trending Discussions on tf-gnn-samples

How can I run a .py file with its options in Python console?

QUESTION

How can I run a .py file with its options in Python console?

Asked 2020-Feb-24 at 18:16

I am trying to run this GitHub project in python, but I could only run it using the Terminal of Pycharm IDE.

According to the guide from the GitHub repository, I removed the $ sign from the beginning of $ python train.py RGCN PPI and could run it there. What does $ mean here and how can I run a file like this in Python Console (for example after >>> sign)?

...

ANSWER

Answered 2020-Feb-24 at 18:16

The '$' isn't part of Python's syntax, it's a visual cue in the documentation representing the command prompt.

To answer the question from the title of this post, I'll provide some instructions first on how to load scripts into the Python console. However, for your specific case, you don't need this. Scroll down to the part about debugging in PyCharm.

There's two ways you can get your script into the console. One is to simply load it using the right version of the two lines I give right below, or you can load it as a module - even if it wasn't intended to be one.

In general, to execute a script in the Python shell on Python 2 you can do

Source https://stackoverflow.com/questions/60359375

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

Vulnerabilities

No vulnerabilities reported

Install tf-gnn-samples

You can download it from GitHub.
You can use tf-gnn-samples 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

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com. When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA. This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.

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