outputContains(output3)

        where:
        expression                                                                                      | output1                     | output2                            | output3

                void myAction() {
                    def output = outputFile.get().asFile
                    output << launcher1.get().executablePath
                    output << launcher2.get().executablePath
                }
            }

            tasks.register("myToolchainTask", ToolchainTask) {
                outputFile = layout.buildDirectory.file("output.txt")
                launcher1 = javaToolchains.launcherFor {

John Howard <******@****.***> 1717524306 -0700

                @Override
                void transform(TransformOutputs outputs) {
                    // Simulate transform leaving file open
                    def output = outputs.file("output.txt")
                    output.createNewFile()
                    TestState.fileKeptOpen = output.newOutputStream()
                    TestState.fileKeptOpen << "output"
                    TestState.fileKeptOpen.flush()
                }

    @get:InputArtifact
    @get:Classpath
    abstract val inputArtifact: Provider<FileSystemLocation>

    override fun transform(outputs: TransformOutputs) {
        val jarFile = inputArtifact.get().asFile
        val zipFile = ZipFile(jarFile)
        val outputRoot = outputs.dir("public-api")
        zipFile.stream().forEach { entry ->
            if (entry.shouldInclude()) {

          TAG="quay.io/minio/minio:${{ steps.vars.outputs.sha_short }}" make docker

      - name: multipart uploads test
        run: |
          ${GITHUB_WORKSPACE}/.github/workflows/multipart/migrate.sh "${{ steps.vars.outputs.sha_short }}"

      - name: compress and encrypt
        run: |
          ${GITHUB_WORKSPACE}/.github/workflows/run-mint.sh "compress-encrypt" "minio" "minio123" "${{ steps.vars.outputs.sha_short }}"

  // Check that we have two inputs and one output.
  ASSERT_THAT(op->inputs, SizeIs(2));
  ASSERT_THAT(op->outputs, SizeIs(1));

  // Check that all is quantized.
  auto output = subgraph->tensors[op->outputs[0]].get();
  auto input1 = subgraph->tensors[op->inputs[0]].get();
  auto input2 = subgraph->tensors[op->inputs[1]].get();

  EXPECT_THAT(output->type, Eq(TensorType_INT8));

  let summary = [{While loop}];

  let description = [{
    output = input; while (cond(output)) { output = body(output) }

    While loop where all values are passes through arguments with implicit
    capture.

    input: A list of input tensors whose types are T.
    output: A list of output tensors whose types are T.
    cond: A region that takes 'input' and returns a boolean scalar tensor.

        // TODO - should just write this as a bean field of the outputs object, and also do this for the registered properties above
        if (task.outputs.upToDateSpec.isEmpty) {
            writeBoolean(false)
        } else {
            writeBoolean(true)
            write(task.outputs.upToDateSpec)
        }
    }

    private

}

def ExecutorConvertControlToDataOutputsPass : Pass<"tf-executor-convert-control-to-data-outputs", "ModuleOp"> {
  let summary = "Chain control outputs of while loop body";

  let description = [{
    This pass converts the control outputs of a while loop body function to data
    outputs. Thus, inter iteration control dependencies are transformed to