1 # Contributing guidelines 2 3 ## How to become a contributor and submit your own code 4 5 ### Contributor License Agreements 6 7 We'd love to accept your patches! Before we can take them, we have to jump a couple of legal hurdles. 8 9 Please fill out either the individual or corporate Contributor License Agreement (CLA). 10 11 * If you are an individual writing original source code and you're sure you own the intellectual property, then you'll need to sign an [individual CLA](https://code.google.com/legal/individual-cla-v1.0.html). 12 * If you work for a company that wants to allow you to contribute your work, then you'll need to sign a [corporate CLA](https://code.google.com/legal/corporate-cla-v1.0.html). 13 14 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. 15 16 ***NOTE***: Only original source code from you and other people that have signed the CLA can be accepted into the main repository. 17 18 ### Contributing code 19 20 If you have improvements to TensorFlow, send us your pull requests! For those 21 just getting started, Github has a [howto](https://help.github.com/articles/using-pull-requests/). 22 23 TensorFlow team members will be assigned to review your pull requests. Once the pull requests are approved and pass continuous integration checks, we will merge the pull requests. 24 For some pull requests, we will apply the patch for each pull request to our internal version control system first, and export the change out as a new commit later, at which point the original pull request will be closed. The commits in the pull request will be squashed into a single commit with the pull request creator as the author. These pull requests will be labeled as pending merge internally. 25 26 If you want to contribute but you're not sure where to start, take a look at the 27 [issues with the "contributions welcome" label](https://github.com/tensorflow/tensorflow/labels/stat%3Acontributions%20welcome). 28 These are issues that we believe are particularly well suited for outside 29 contributions, often because we probably won't get to them right now. If you 30 decide to start on an issue, leave a comment so that other people know that 31 you're working on it. If you want to help out, but not alone, use the issue 32 comment thread to coordinate. 33 34 ### Contribution guidelines and standards 35 36 Before sending your pull request for 37 [review](https://github.com/tensorflow/tensorflow/pulls), 38 make sure your changes are consistent with the guidelines and follow the 39 TensorFlow coding style. 40 41 #### General guidelines and philosophy for contribution 42 43 * Include unit tests when you contribute new features, as they help to 44 a) prove that your code works correctly, and b) guard against future breaking 45 changes to lower the maintenance cost. 46 * Bug fixes also generally require unit tests, because the presence of bugs 47 usually indicates insufficient test coverage. 48 * Keep API compatibility in mind when you change code in core TensorFlow, 49 e.g., code in [tensorflow/core](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core) and [tensorflow/python](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python). 50 TensorFlow has reached version 1 and hence cannot make 51 non-backward-compatible API changes without a major release. Reviewers of your 52 pull request will comment on any API compatibility issues. 53 * When you contribute a new feature to TensorFlow, the maintenance burden is (by 54 default) transferred to the TensorFlow team. This means that benefit of the 55 contribution must be compared against the cost of maintaining the feature. 56 * Full new features (e.g., a new op implementing a cutting-edge algorithm) 57 typically will live in 58 [tensorflow/contrib](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib) 59 to get some airtime before decision is made regarding whether they are to be 60 migrated to the core. 61 62 #### License 63 64 Include a license at the top of new files. 65 66 * [C/C++ license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op.cc#L1) 67 * [Python license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/nn.py#L1) 68 * [Java license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/java/src/main/java/org/tensorflow/Graph.java#L1) 69 * [Go license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/go/operation.go#L1) 70 * [Bash license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/ci_build/ci_sanity.sh#L2) 71 * [HTML license example](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/components/tf_backend/tf-backend.html#L2) 72 * [JavaScript/TypeScript license example](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/components/tf_backend/backend.ts#L1) 73 74 Bazel BUILD files also need to include a license section, e.g., 75 [BUILD example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/BUILD#L61). 76 77 #### C++ coding style 78 79 Changes to TensorFlow C++ code should conform to 80 [Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html). 81 82 Use `clang-tidy` to check your C/C++ changes. To install clang-tidy on ubuntu:16.04, do: 83 84 ```bash 85 apt-get install -y clang-tidy 86 ``` 87 88 You can check a C/C++ file by doing: 89 90 91 ```bash 92 clang-format <my_cc_file> --style=google > /tmp/my_cc_file.cc 93 diff <my_cc_file> /tmp/my_cc_file.cc 94 ``` 95 96 #### Python coding style 97 98 Changes to TensorFlow Python code should conform to 99 [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html) 100 101 Use `pylint` to check your Python changes. To install `pylint` and 102 retrieve TensorFlow's custom style definition: 103 104 ```bash 105 pip install pylint 106 wget -O /tmp/pylintrc https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/tools/ci_build/pylintrc 107 ``` 108 109 To check a file with `pylint`: 110 111 ```bash 112 pylint --rcfile=/tmp/pylintrc myfile.py 113 ``` 114 115 #### Coding style for other languages 116 117 * [Google Java Style Guide](https://google.github.io/styleguide/javaguide.html) 118 * [Google JavaScript Style Guide](https://google.github.io/styleguide/jsguide.html) 119 * [Google Shell Style Guide](https://google.github.io/styleguide/shell.xml) 120 * [Google Objective-C Style Guide](https://google.github.io/styleguide/objcguide.html) 121 122 #### Running sanity check 123 124 If you have Docker installed on your system, you can perform a sanity check on 125 your changes by running the command: 126 127 ```bash 128 tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh 129 ``` 130 131 This will catch most license, Python coding style and BUILD file issues that 132 may exist in your changes. 133 134 #### Running unit tests 135 136 There are two ways to run TensorFlow unit tests. 137 138 1. Using tools and libraries installed directly on your system. 139 140 Refer to the 141 [CPU-only developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/docker/Dockerfile.devel) and 142 [GPU developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/docker/Dockerfile.devel-gpu) 143 for the required packages. Alternatively, use the said 144 [Docker images](https://hub.docker.com/r/tensorflow/tensorflow/tags/), e.g., 145 `tensorflow/tensorflow:nightly-devel` and `tensorflow/tensorflow:nightly-devel-gpu` 146 for development to avoid installing the packages directly on your system. 147 148 Once you have the packages installed, you can run a specific unit test in 149 bazel by doing as follows: 150 151 If the tests are to be run on GPU, add CUDA paths to LD_LIBRARY_PATH and add 152 the `cuda` option flag 153 154 ```bash 155 export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH" 156 157 export flags="--config=opt --config=cuda -k" 158 ``` 159 160 For example, to run all tests under tensorflow/python, do: 161 162 ```bash 163 bazel test ${flags} //tensorflow/python/... 164 ``` 165 166 2. Using [Docker](https://www.docker.com) and TensorFlow's CI scripts. 167 168 ```bash 169 # Install Docker first, then this will build and run cpu tests 170 tensorflow/tools/ci_build/ci_build.sh CPU bazel test //tensorflow/... 171 ``` 172 173 See 174 [TensorFlow Builds](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/tools/ci_build) for details. 175 176
