}

    def "include paths include component headers"() {
        final inputs = new DefaultDomainObjectSet(LanguageSourceSet, CollectionCallbackActionDecorator.NOOP)

        when:
        exeBinary.inputs >> inputs
        exeBinary.libs >> []

        then:
        targetBinary.includePaths == [] as Set

        when:

}

}  // anonymous namespace

std::vector<const Tensor*> InputsFromContext(OpKernelContext* ctx) {
  std::vector<const Tensor*> inputs;
  inputs.reserve(ctx->num_inputs());
  for (int input_idx = 0; input_idx < ctx->num_inputs(); input_idx++) {
    inputs.push_back(&ctx->input(input_idx));
  }
  return inputs;
}

absl::StatusOr<std::vector<int>> GetConstantInputIndicesFromContext(
    OpKernelContext* ctx) {

    @TaskAction fun action() { println(inputValue.get()) }
}

// tag::gradle-properties-task-inputs[]
tasks.register<PrintValue>("printProperty") {
    // Using the API, provides a lazy Provider<String> wired to a task input
    inputValue = providers.gradleProperty("gradlePropertiesProp")
}

// CHECK: "tf.LookupTableSizeV2"(%arg1)
// CHECK: "tf.LookupTableFindV2"(%arg1

// RUN: odml-to-stablehlo-opt %s -tfl-parse-stablehlo-ops | FileCheck %s

module {
func.func @main(%arg0: tensor<2xi32>) -> tensor<2xi32> attributes {tf.entry_function = {inputs = "arg0", outputs = "tfl.custom1"}} {
  %0 = "tfl.custom"(%arg0, %arg0) {custom_code = "stablehlo.add", custom_option = #tfl<const_bytes : "0x00000100002401">} : (tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32>
  func.return %0 : tensor<2xi32>
}
}

// CHECK:       module {

// CHECK-NEXT:       quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:       },
// CHECK-NEXT:       has_rank: true
// CHECK-NEXT:     } ],
// CHECK-NEXT:     inputs: [ 0 ],
// CHECK-NEXT:     outputs: [ 4 ],
// CHECK-NEXT:     operators: [ {
// CHECK-NEXT:       inputs: [ 0, 1 ],
// CHECK-NEXT:       outputs: [ 2 ],
// CHECK-NEXT:       builtin_options_type: SubOptions,
// CHECK-NEXT:       builtin_options: {

LogicalResult XlaVariadicSortOp::verify() {
  XlaVariadicSortOp op = *this;
  const auto &inputs_ty = op.getInputs().getType();
  int n_inputs = inputs_ty.size();
  auto input_ty_0 = inputs_ty[0].cast<ShapedType>();
  if (input_ty_0.hasStaticShape()) {
    for (int i = 1; i < n_inputs; ++i) {
      auto input_ty_i = inputs_ty[i].cast<ShapedType>();
      if (input_ty_i.hasStaticShape() &&

        super(taskDependencyFactory);
        this.taskPath = taskPath;
        this.calculatedFiles = calculatedFiles;
        targets = new ArrayList<>(1 + inputs.length);
        for (Object input : inputs) {
            if (input instanceof LifecycleAwareValue) {
                targets.add((LifecycleAwareValue) input);

[`tf_executor.Merge`](https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/merge):
takes a variadic number of inputs, and returns a single output. The output is
defined as a non-dead input (selected in a non-defined way if multiple inputs
are non-dead). If all inputs are dead, the output is also dead.

### NextIteration: `tf_executor.NextIteration.Source` and `tf_executor.NextIteration.Sink` Operation

The TensorFlow

tasks.register("showTestClasspath") {
    val testCompileClasspath: FileCollection = configurations.testCompileClasspath.get()
    val testRuntimeClasspath: FileCollection = configurations.testRuntimeClasspath.get()
    inputs.files(testCompileClasspath)
    inputs.files(testRuntimeClasspath)
    doLast {
        println(testCompileClasspath.files.map(File::getName))
        println(testRuntimeClasspath.files.map(File::getName))
    }