# limitations under the License.
# ==============================================================================


# This Workflow updates tensorflow/tools/toolchains/remote_config/configs.bzl
# to reference the most recent versions of the SIG Build Docker images.
name: Update RBE Configs
on:
  workflow_dispatch:

permissions:
  contents: read

jobs:
  rbe:
    name: Update RBE Configs
    runs-on: ubuntu-latest

          exempt-pr-labels: "from:contributor"
          stale-pr-label: stale
          stale-pr-message: >
            This pull request has been automatically marked as stale because it has not had recent activity.
            It will be closed in 14 days if no further activity occurs.
            If you don't want the stale bot to close it, then set a milestone for it.
          days-before-pr-close: 14

///

```Python hl_lines="8-9"
{!> ../../docs_src/dependencies/tutorial005.py!}
```

////

Diese deklariert einen optionalen Abfrageparameter `q` vom Typ `str` und gibt ihn dann einfach zurück.

Das ist recht einfach (nicht sehr nützlich), hilft uns aber dabei, uns auf die Funktionsweise der Unterabhängigkeiten zu konzentrieren.

## Zweite Abhängigkeit, „Dependable“ und „Dependant“

         * which repository provides which version so the metadata manager must not restrict the artifact resolution to
         * the repository with the most recent updates.
         */
    }

    return forwardOrder.max(a, b);
  }

  @Override
  public <E extends T> E min(
      @ParametricNullness E a, @ParametricNullness E b, @ParametricNullness E c, E... rest) {
    return forwardOrder.max(a, b, c, rest);
  }

  @Override
  public <E extends T> E min(Iterator<E> iterator) {
    return forwardOrder.max(iterator);
  }

  @Override
  public <E extends T> E min(Iterable<E> iterable) {

/** Extracts PR from commit message and creates a GitHub Issue on Rollback of PR
  Created issue is assigned to original PR owner and reviewer.

  @param {!object}
    github enables querying for PR and also create issue using rest endpoint
    context has the commit message details in the payload
  @return {string} Returns the issue number and title
*/
module.exports = async ({github, context}) => {

      implements Serializable, RandomAccess {
    @ParametricNullness final E first;
    final E[] rest;

    OnePlusArrayList(@ParametricNullness E first, E[] rest) {
      this.first = first;
      this.rest = checkNotNull(rest);
    }

    @Override
    public int size() {
      return IntMath.saturatedAdd(rest.length, 1);
    }

    @Override
    @ParametricNullness
    public E get(int index) {

		switch v := txedRec.(type) {
		case jstream.KVS:
			kvs = v

		case []interface{}:
			recs := make([]*Record, len(v))
			for i, val := range v {
				tmpRec := input.Clone(nil)
				if err = tmpRec.Replace(val); err != nil {
					return nil, err
				}
				recs[i] = &tmpRec
			}
			return recs, nil

		default:
			kvs = jstream.KVS{jstream.KV{Key: "_1", Value: v}}
		}

	exit_1
fi

if [ "${enabled_minio1}" != "Enabled" ]; then
	echo "expected bucket to be mirrored with object-lock enabled, exiting..."
	exit_1
fi

# "Test if most recent tag update is replicated"
./mc tag set minio2/newbucket "key=val1"
if [ $? -ne 0 ]; then
	echo "expecting tag set to be successful. exiting.."
	exit_1
fi

sleep 10

   
      * Try Google Colab to use TensorFlow.
         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.