@@ -38,41 +38,45 @@ click F "https://github.com/tensorflow/tensorflow/blob/master/CONTRIBUTING.md#4-
click I "https://github.com/tensorflow/tensorflow/blob/master/CONTRIBUTING.md#5-copy-to-g3" _blank
```
## Typical Pull Request Workflow
### 1. New PR
- As a contributor, you submit a New PR on GitHub.
- We inspect every incoming PR and add certain labels to the PR such as `size:`, `comp:` etc. At this stage we check if the PR is valid and meets certain quality requirements.
- For example: We check if the CLA is signed, PR has sufficient description, if applicable unit tests are added and if it is a reasonable contribution, i.e., it is not a single liner cosmetic PR.
### 2. Valid?
- If the PR passes all the quality checks then we go ahead and assign a reviewer.
- If the PR does not meet the validation criteria, we request for additional changes to be made to the PR to pass quality checks and send it back or on a rare occassion, we may reject it.
### 3. Review
- For a valid PR, the reviewer (person familiar with the code/functionality) checks if the PR looks good or needs additional changes.
- If all looks good, the reviewer will approve the PR.
- If a change is needed, you (the contributor) are requested to make the suggested change.
- You make the change and submit for the review again. This cycle repeats itself till the PR gets approved.
> Note: As a friendly reminder we may reach out to you if the PR is awaiting your response for more than 2 weeks.
### 4. Approved
- Once the PR is approved, it gets the `kokoro:force-run` label applied and it initiates CI/CD tests.
- We can't move forward if these tests fail.
- If the tests fail, we may request you to make further changes to your PR for the tests to pass.
- Once the tests pass, we now bring all the code in the internal code base, using a job called "copybara".
### 5. Copy to G3
- Once the PR is in Google codebase, we make sure it integrates well with its dependencies and the rest of the system.
- Rarely, the tests might fail at this stage. If they do fail, we cannot merge the code.
- If needed, we may ask you to make some changes.
- At times, it may not be you, it may be us who may have hit a snag. Please be patient while we work to fix this.
- Once the internal tests pass, we go ahead and merge the code internally as well as externally on GitHub.
## Contributor License Agreements
We love to accept your patches! But before we can take them, we have to jump a couple of legal hurdles.
### Typical Pull Request Workflow -
**1. New PR** - As a contributor, you submit a New PR on GitHub. - We inspect
every incoming PR and add certain labels to the PR such as `size:`, `comp:` etc.
At this stage we check if the PR is valid and meets certain quality
requirements. - For example - We check if the CLA is signed, PR has sufficient
description, if applicable unit tests are added, if it is a reasonable
contribution meaning it is not a single liner cosmetic PR.
**2. Valid?** - If the PR passes all the quality checks then we go ahead and
assign a reviewer. - If the PR didn't meet the validation criteria, we request
for additional changes to be made to PR to pass quality checks and send it back
or on a rare occassion we may reject it.
**3. Review** - For Valid PR, reviewer (person familiar with the
code/functionality) checks if the PR looks good or needs additional changes. -
If all looks good, reviewer would approve the PR. - If a change is needed, the
contributor is requested to make suggested change. - You make the change and
submit for the review again. - This cycle repeats itself till the PR gets
approved. - Note: As a friendly reminder we may reach out to you if the PR is
awaiting your response for more than 2 weeks.
**4. Approved** - Once the PR is approved, it gets `kokoro:force-run` label
applied and it initiates CI/CD tests. - We can't move forward if these tests
fail. - In such situations, we may request you to make further changes to your
PR for the tests to pass. - Once the tests pass, we now bring all the code in
the internal code base, using a job called "copybara".
**5. Copy to G3** - Once the PR is in Google codebase, we make sure it
integrates well with its dependencies and the rest of the system. - Rarely, but
If the tests fail at this stage, we cannot merge the code. - If needed, we may
come to you to make some changes. - At times, it may not be you, it may be us
who may have hit a snag. - Please be patient while we work to fix this. - Once
the internal tests pass, we go ahead and merge the code internally as well as
externally on GitHub.
### Contributor License Agreements
We'd love to accept your patches! Before we can take them, we have to jump a couple of legal hurdles.
Please fill out either the individual or corporate Contributor License Agreement (CLA).
...
...
@@ -81,15 +85,34 @@ Please fill out either the individual or corporate Contributor License Agreement
Follow either of the two links above to access the appropriate CLA and instructions for how to sign and return it. Once we receive it, we'll be able to accept your pull requests.
> NOTE: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.
***NOTE***: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.
### Contributing code
If you have improvements to TensorFlow, send us your pull requests! For those just getting started, Github has a [how to](https://help.github.com/articles/using-pull-requests/).
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.
If you want to contribute, start working through the TensorFlow codebase, navigate to the Github ["issues"](https://github.com/tensorflow/tensorflow/issues) tab and start looking through interesting issues. If you are not sure of where to start, then start by trying one of the smaller/easier issues here i.e. issues with the ["good first issue"](https://github.com/tensorflow/tensorflow/labels/good%20first%20issue) label and then take a look at the issues with the ["contributions welcome"](https://github.com/tensorflow/tensorflow/labels/stat%3Acontributions%20welcome) label. 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 decide to start working on an issue, leave a comment so that other people know that you're working on it. If you want to help out, but not alone, use the issue comment thread to coordinate.
If you have improvements to TensorFlow, send us your pull requests! For those
@@ -312,7 +335,9 @@ There are two ways to test the code in the docstring locally:
#### Debug builds
When [building Tensorflow](https://www.tensorflow.org/install/source) from source, if `--config=dbg` is passed to Bazel, it will build *with* debugging information and *without* optimizations, allowing you to use GDB or other debuggers to debug C++ code. For
When [building Tensorflow](https://www.tensorflow.org/install/source), passing
`--config=dbg` to Bazel will build with debugging information and without
optimizations, allowing you to use GDB or other debuggers to debug C++ code. For
example, you can build the pip package with debugging information by running:
```bash
...
...
@@ -331,4 +356,4 @@ op, which are in files starting with `identity_op`, you can run
