Guava, the best approach is to create an [issue][] (or comment on an existing
issue if there is one) requesting the feature and describing specific use cases
for it.

If the feature has merit, it will go through a thorough process of API design
and review. Any code should come after this.

[APIs]: https://en.wikipedia.org/wiki/Application_programming_interface
[issue]: https://github.com/google/guava/issues

  + Make sure you fill in the earliest version that you know has the issue.
+ Fork the repository on GitHub.

Making and Submitting Changes
--------------

We accept Pull Requests via GitHub. The [developer mailing list][dev-ml-list] is the
main channel of communication for contributors.  
There are some guidelines which will make applying PRs easier for us:

For any non-trivial change, we need to be able to answer these questions:

* Why is this change done? What's the use case?
* For user facing features, what will the API look like?
* What test cases should it have? What could go wrong?
* How will it roughly be implemented? We'll happily provide code pointers to save you time.

### Setup your MinIO GitHub Repository

Fork [MinIO upstream](https://github.com/minio/minio/fork) source repository to your own personal repository. Copy the URL of your MinIO fork (you will need it for the `git clone` command below).

```sh
git clone https://github.com/minio/minio
go install -v
ls /go/bin/minio
```

### Set up git remote as ``upstream``

```sh
$ cd minio

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After
the change has been submitted internally, your pull request will be merged
automatically on GitHub.