// capturing the return value in an 'auto' local variable. Most users will not
// need more sophisticated syntax than that.
//
// Example:
//   void func() {
//     FILE* fp = fopen("data.txt", "r");
//     if (fp == nullptr) return;
//     auto fp_cleaner = gtl::MakeCleanup([fp] { fclose(fp); });
//     // No matter what, fclose(fp) will happen.
//     DataObject d;

If you open a GitHub Issue, here is our policy:

1.  It must be a bug/performance issue or a feature request or a build issue or
    a documentation issue (for small doc fixes please send a PR instead).
1.  Make sure the Issue Template is filled out.
1.  The issue should be related to the repo it is created in.

**Here's why we have this policy:** We want to focus on the work that benefits
the whole community, e.g., fixing bugs and adding features. Individual support

                         off_t size) {
  int src_fd = open(src, O_RDONLY);
  if (src_fd < 0) return -1;

  // When creating file, use the same permissions as original
  mode_t open_mode = mode & (S_IRWXU | S_IRWXG | S_IRWXO);

  // O_WRONLY | O_CREAT | O_TRUNC:
  //   Open file for write and if file does not exist, create the file.
  //   If file exists, truncate its size to 0.
  int dst_fd = open(dst, O_WRONLY | O_CREAT | O_TRUNC, open_mode);

  std::remove(name_.c_str());
}

const std::string TempFile::getName() const { return name_; }

bool TempFile::truncate() {
  std::fstream::close();
  std::fstream::open(name_, std::ios::binary | std::ios::out);
  return std::fstream::is_open();

# TensorFlow Code of Conduct

In the interest of fostering an open and welcoming environment, we as
contributors and maintainers pledge to make participation in our project and our
community a harassment-free experience for everyone, regardless of age, body
size, disability, ethnicity, gender identity and expression, level of
experience, nationality, personal appearance, race, religion, or sexual identity
and orientation.

## Our Standards

{
    "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.",
    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }

          labels-to-remove-when-unstale: 'stat:awaiting response'
          only-labels: "stat:awaiting response"
          stale-issue-message: > 
            This issue is stale because it has been open for 7 days with no activity.
            It will be closed if no further activity occurs. Thank you.
          close-issue-message: >

authors:...

      api_packages_path = pkg_resources.resource_filename(
          "tensorflow", "_api/v2/api_packages.txt"
      )

      logging.info("Load api packages file: %s", api_packages_path)
      with open(api_packages_path) as file:
        return set(file.read().splitlines())

    super().setUp()
    self.api_packages_v2 = _get_api_packages_v2()
    # Some paths in the api_packages_path file cannot be directly imported.