share a link to Colab/Jupyter/any notebook. placeholder: Tell us what you
    see! value: render: shell validations: required: true

-   type: textarea id: logs attributes: label: Relevant log output description:
    Please copy and paste any relevant log output. This will be automatically

        with:
          github-token: ${{secrets.GITHUB_TOKEN}}
          script: |
            const script = require('./.github/workflows/create_issue.js')

# > target platform.
# See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation
build --distinct_host_configuration=false

# Store performance profiling log in the mounted artifact directory.
# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include "absl/log/log.h"
#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"
#include "tensorflow/c/experimental/filesystem/modular_filesystem_registration.h"

# offset of in the current version of ubp.
# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.
build --copt=-Wno-gnu-offsetof-extensions

# Store performance profiling log in the mounted artifact directory.
# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling

//     auto fp_cleaner = gtl::MakeCleanup([fp] { fclose(fp); });
//     // No matter what, fclose(fp) will happen.
//     DataObject d;
//     while (ReadDataObject(fp, &d)) {
//       if (d.IsBad()) {
//         LOG(ERROR) << "Bad Data";
//         return;
//       }
//       PushGoodData(d);
//     }
//   }
//
// You can use Cleanup<F> directly, instead of using MakeCleanup and auto,
// but there's rarely a reason to do that.

  for (int i = 0; i < num_tasks; i++) {
    int port = tensorflow::testing::PickUnusedPortOrDie();
    job_def->mutable_tasks()->insert(
        {i, tensorflow::strings::StrCat("localhost", ":", port)});
    LOG(INFO) << "Picked test port: " << port << " for job: " << job_name
              << ", task: " << i;
  }
  return server_def;
}

namespace tensorflow {
namespace parallel_device {

  local \
    XML_PATH="$TFCI_OUTPUT_DIR/Bazel_Test_and_Build_Results/sponge_log.xml"

  python3 \
    "$TFCI_GIT_DIR/ci/official/utilities/extract_resultstore_links.py" \
    "$TFCI_OUTPUT_DIR/script.log" \
    --print \
    --xml-out-path "$XML_PATH" || resultstore_extract_fallback
}

if grep -q "Streaming build results to" "$TFCI_OUTPUT_DIR/script.log"; then
  resultstore_extract || resultstore_extract_fallback

          git fetch origin master
          git cherry-pick ${{ github.event.inputs.git_commit }}
          echo "SHORTSHA=$(git log -1 ${{ github.event.inputs.git_commit }} --format="%h")" >> "$GITHUB_OUTPUT"
          echo "TITLE=$(git log -1 ${{ github.event.inputs.git_commit }} --format="%s")" >> "$GITHUB_OUTPUT"
    - name: Create Pull Request with changes

# TF_ANY_TARGETS=":your/target" TF_ANY_MODE="test" ci/official/any.sh

# Afterwards: Examine the results, which will include: The bazel cache,
# generated artifacts like .whl files, and "script.log", from the script.
# Note that files created under Docker will be owned by "root".
ls build_output
```

## Contribution & Maintenance

The TensorFlow team does not yet have guidelines in place for contributing to