*/
    public String[] getNewInputs() {
        return newInputs == null ? null : newInputs.clone();
    }

    /**
     * Sets the array of new input character sequences for update operations.
     *
     * @param newInputs array of new input sequences to set
     */
    public void setNewInputs(final String[] newInputs) {
        this.newInputs = newInputs;
    }

    /**

     * @param inputs  The input words.
     * @param outputs The output synonyms.
     */
    public SynonymItem(final long id, final String[] inputs, final String[] outputs) {
        this.id = id;
        this.inputs = inputs;
        this.outputs = outputs;

        if (id == 0) {
            // create
            newInputs = inputs;
            newOutputs = outputs;
        }
    }

     * @return the input value
     */
    public String getInput() {
        return input;
    }

    /**
     * Gets the input value or empty string if null.
     * @return the input value or empty string
     */
    public String getInputValue() {
        if (input == null) {
            return StringUtil.EMPTY;
        }
        return input;
    }

    /**

    private final String input;

    /** The new stopword, if updated. */
    private String newInput;

    /**
     * Constructs a new stopword item.
     *
     * @param id    The unique identifier of the item.
     * @param input The stopword.
     */
    public StopwordsItem(final long id, final String input) {
        this.id = id;
        this.input = input;

        if (id == 0) {

jobs:
  cherrypick:
    name: Cherrypick to ${{ github.event.inputs.release_branch}} - ${{ github.event.inputs.git_commit }}
    runs-on: ubuntu-latest
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    steps:
    - name: Checkout code
      uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
      with:
        ref: ${{ github.event.inputs.release_branch }}

TF_Operation* RandomUniform(TF_Operation* shape, TF_DataType dtype,
                            TF_Graph* graph, TF_Status* s);

// Split `input` along the first dimension into 3 tensors
TF_Operation* Split3(TF_Operation* input, TF_Graph* graph, TF_Status* s,
                     const char* name = "split3");

bool IsPlaceholder(const tensorflow::NodeDef& node_def);

          A result(Collector<T, A, R> collector, Iterable<T> inputs) {
        List<A> stack = new ArrayList<>();
        for (T input : inputs) {
          A newAccum = collector.supplier().get();
          collector.accumulator().accept(newAccum, input);
          push(stack, newAccum);
        }
        push(stack, collector.supplier().get());

		var err error
		inputs, err = filepathx.Glob(flag.Args()[0])
		fatalErr(err)
		if len(inputs) == 0 {
			fmt.Println("Usage: No input found")
		}
	default:
		flag.Usage()
		fatalIf(true, "Only 1 file can be decrypted")
		os.Exit(1)
	}
	for _, input := range inputs {
		processFile(input, privateKeys)
	}
}

func processFile(inputFileName string, privateKeys [][]byte) {

        with:
          limit-access-to-actor: true
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
      - name: Notify Translations
        run: python ./scripts/notify_translations.py
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          NUMBER: ${{ github.event.inputs.number || null }}

    inputs.files(acceptedViolationsFiles)
    inputs.property("baseline.version", compatibilityBaselineVersion)
    inputs.property("currentVersion", baseVersion)
    def apiSourceFolders = configurations.currentSources.incoming.artifactView { lenient(true) }.files
    inputs.files("apiSourceFolders", apiSourceFolders)
    inputs.files(currentClasspath)
    inputs.files(extractGradleApiInfo)