custom: GradleBuildStep.() -> Unit,
): GradleBuildStep =
    GradleBuildStep(init)
        .apply(custom)
        .also {
            step(it)
        }

/**
 * Adds a [Gradle build step](https://confluence.jetbrains.com/display/TCDL/Gradle)
 * that runs with the Gradle wrapper.
 *
 * @see GradleBuildStep
 */
fun BuildSteps.gradleWrapper(
    buildType: BuildType? = null,
    init: GradleBuildStep.() -> Unit,

   * use the {@code HashMap} constructor directly, taking advantage of <a
   * href="https://docs.oracle.com/javase/tutorial/java/generics/genTypeInference.html#type-inference-instantiation">"diamond"
   * syntax</a>.
   *
   * @return a new, empty {@code HashMap}
   */
  @SuppressWarnings("NonApiType") // acts as a direct substitute for a constructor call

   * use the {@code HashMap} constructor directly, taking advantage of <a
   * href="https://docs.oracle.com/javase/tutorial/java/generics/genTypeInference.html#type-inference-instantiation">"diamond"
   * syntax</a>.
   *
   * @return a new, empty {@code HashMap}
   */
  @SuppressWarnings("NonApiType") // acts as a direct substitute for a constructor call

*   Added a `model.export(filepath)` API to create a lightweight SavedModel artifact that can be used for inference (e.g. with TF-Serving).

## 他の検索プロバイダーからの移行

[MIGRATION.md](MIGRATION.md)を参照してください。

## データストア

現在、Fessは以下の[ストレージロケーションとAPI](https://fess.codelibs.org/15.3/admin/dataconfig-guide.html)のクロールをサポートしています：

 - [Confluence/Jira](https://github.com/codelibs/fess-ds-atlassian)
 - [Box](https://github.com/codelibs/fess-ds-box)
 - [CSV](https://github.com/codelibs/fess-ds-csv)
 - [Database](https://github.com/codelibs/fess-ds-db)

  }

  TF_Output output_;

  // For LLVM style RTTI.
  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  TF_Graph* graph_;  // For shape inference.
};

// GraphOperation wraps and populates a TF_OperationDescription.
class GraphOperation : public TracingOperation {
 public:
  explicit GraphOperation(TF_Graph* g) : TracingOperation(kGraph), g_(g) {}

    }
    status->status = desc->node_builder.Finalize(&desc->graph->graph, &ret,
                                                 /*consume=*/true);

    if (status->status.ok()) {
      // Run shape inference function for newly added node.
      status->status = desc->graph->refiner.AddNode(ret);
    }
    if (status->status.ok()) {
      // Add the node to the name-to-node mapping.

  }

  @SuppressWarnings("JUnitIncompatibleType")
  public void testWhere() {
    assertEquals(new TypeToken<Map<String, Integer>>() {}, mapOf(String.class, Integer.class));
    // Type inference is doomed here: int.class is the same as Integer.class, so this is comparing
    // TypeToken<int[]> and TypeToken<Integer[]>.
    assertEquals(new TypeToken<int[]>() {}, arrayOf(int.class));

TF_CAPI_EXPORT extern void TF_RemoveAllControlInputs(TF_Graph* graph,
                                                     TF_Operation* op);

// Set if `graph` requires shape inference functions.
TF_CAPI_EXPORT extern void TF_SetRequireShapeInferenceFns(TF_Graph* graph,
                                                          bool require);

  }

  @SuppressWarnings("JUnitIncompatibleType")
  public void testWhere() {
    assertEquals(new TypeToken<Map<String, Integer>>() {}, mapOf(String.class, Integer.class));
    // Type inference is doomed here: int.class is the same as Integer.class, so this is comparing
    // TypeToken<int[]> and TypeToken<Integer[]>.
    assertEquals(new TypeToken<int[]>() {}, arrayOf(int.class));