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Please read the contribution guidelines at
https://github.com/google/guava/wiki/HowToContribute#code-contributions
and
https://github.com/google/guava/blob/master/CONTRIBUTING.md
before sending a pull request.

We generally welcome PRs for fixing trivial bugs or typos, but please refrain
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[issues with the "good first issue" label](https://github.com/tensorflow/tensorflow/labels/good%20first%20issue)
and then take a look at the
[issues with the "contributions welcome" label](https://github.com/tensorflow/tensorflow/labels/stat%3Acontributions%20welcome).
These are issues that we believe are particularly well suited for outside
contributions, often because we probably won't get to them right now. If you

          close-issue-reason: completed
          # List of labels to remove when issues/PRs unstale. 
          labels-to-remove-when-unstale: "stat:contribution welcome,stat:good first issue"
          any-of-labels: "stat:contribution welcome,stat:good first issue"
          stale-issue-message: > 
            This issue is stale because it has been open for 180 days with no activity.

This is normally the best way to contribute to the project.

## External Contributions

External contributions are very welcome and appreciated, including answering questions, submitting PRs, etc. 🙇‍♂️

You can download the release source from our [download page][maven-download].

Contributing
------------

If you are interested in the development of Maven, please consult the
documentation first and afterward you are welcome to join the developers
mailing list to ask questions or discuss new ideas/features/bugs etc.

Take a look into the [contribution guidelines](CONTRIBUTING.md).

License
-------

``MinIO`` community welcomes your contribution. To make the process as seamless as possible, we recommend you read this contribution guide.

## Development Workflow

    <glob pattern="*.xmap"/>
    <glob pattern="*.xroles"/>
    <glob pattern="*.xsamples"/>
    <glob pattern="*.xsp"/>
    <glob pattern="*.xtest"/>
    <glob pattern="*.xweb"/>
    <glob pattern="*.xwelcome"/>
  </mime-type>

  <mime-type type="text/prs.fallenstein.rst"/>
  <mime-type type="text/prs.lines.tag">
    <glob pattern="*.dsc"/>
  </mime-type>
  <mime-type type="text/red"/>

   
      * Try Google Colab to use TensorFlow.
         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.

- **Authentication**: NTLM, Kerberos, SPNEGO unified subsystem
- **Network Layer**: Transport abstraction, NetBIOS name resolution, session management

### Contributing

We welcome contributions! Please:
1. Fork the repository
2. Create a feature branch
3. Make your changes with appropriate tests
4. Run `mvn clean test` to ensure all tests pass
5. Submit a pull request

### License