}

        List<Object> inputs = new ArrayList<>(inputTypes.size());
        for (Class<?> inputType : inputTypes) {
            if (inputType == ComponentMetadata.class) {
                inputs.add(metadataProvider.getComponentMetadata());
                continue;
            }
            if (inputType == IvyModuleDescriptor.class) {
                inputs.add(metadataProvider.getIvyModuleDescriptor());

// 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: {

    inputs.property('acceptedViolations', acceptedViolations.toAcceptedChangesMap())
    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)

// end::gradle-properties[]

abstract class PrintValue extends DefaultTask {
    @Input abstract Property<String> getInputValue()
    @TaskAction void action() { println(inputValue.get()) }
}

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

// CHECK-NEXT:       quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:       },
// CHECK-NEXT:       has_rank: true
// CHECK-NEXT:     } ],
// CHECK-NEXT:     inputs: [ 0, 1 ],
// CHECK-NEXT:     outputs: [ 3 ],
// CHECK-NEXT:     operators: [ {
// CHECK-NEXT:       inputs: [ 0, 1 ],
// CHECK-NEXT:       outputs: [ 2, 3 ],
// CHECK-NEXT:       builtin_options_type: WhileOptions,
// CHECK-NEXT:       builtin_options: {

            3
          ],
          "name": "output1",
          "quantization": {
          }
        }
      ],
      "inputs": [
        0,
        1
      ],
      "outputs": [
        2,
        3
      ],
      "operators": [
        {
          "inputs": [
            0,
            1
          ],
          "outputs": [
            2,
            3
          ],

// 2. A tf.function can take arbitrary python inputs, whereas the FunctionDef
// only accepts tensors.
// 3. A tf.function is a closure that can contain captured inputs, whereas
// FunctionDefs loaded from SavedModels are "functional" (all inputs are
// explicitly passed as arguments).
// The SavedModelAPI only supports loading tf.functions annotated with input

      tf_executor.fetch %ctl_3 : !tf_executor.control
    }
    return
  }

  func.func @main(%arg: tensor<!tf_type.string> {tf_saved_model.index_path = ["__tf_file_prefix"]}) -> ()
      attributes {tf.entry_function = {inputs = "tf_file_prefix:0", outputs = ""}, tf_saved_model.exported_names = ["main"]} {
    tf_executor.graph {
      tf_executor.fetch
    }
    return
  }
}
// Save function should be erased.

        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);
            }
        }

    }

    /**
     * The hashes of the inputs.
     * <p>
     * If the inputs were not snapshotted, all fields are null.
     * This may occur if the task had no outputs.
     */
    public interface Result {

        /**
         * The overall hash value for the inputs.
         * <p>
         * Null if the overall key was not calculated because the inputs were invalid.
         */
        @Nullable