/*
   * We override the toArray methods for two reasons:
   *
   * 1. Both superclass toArray methods assume that size() gives a correct answer, while our size()
   * might not (and the answer might change while we're building the array).
   *
   * TODO: cpovirk - Is this an issue anywhere anymore? It looks to have been fixed for Java 8
   * (https://bugs.openjdk.org/browse/JDK-7121314) and before Lollipop

            int totalProblems = toolchainsResult.getProblems().totalProblemsReported();
            context.logger.info("");
            context.logger.info(String.format(
                    "%s %s encountered while building the effective toolchains (use -e to see details)",
                    totalProblems, (totalProblems == 1) ? "problem was" : "problems were"));

            if (context.options().showErrors().orElse(false)) {

 * For 4.0.0 models: applies limited inference (parent-related only).
 * For 4.1.0+ models: applies full inference optimizations.
 * Removes redundant information that can be inferred by Maven during model building.
 */
@Named
@Singleton
@Priority(30)
public class InferenceStrategy extends AbstractUpgradeStrategy {

    @Override
    public boolean isApplicable(UpgradeContext context) {

  /*
   * We override the toArray methods for two reasons:
   *
   * 1. Both superclass toArray methods assume that size() gives a correct answer, while our size()
   * might not (and the answer might change while we're building the array).
   *
   * TODO: cpovirk - Is this an issue anywhere anymore? It looks to have been fixed for Java 8
   * (https://bugs.openjdk.org/browse/JDK-7121314) and before Lollipop

## Highlights

*   TF 2.0 delivers Keras as the central high level API used to build and train
    models. Keras provides several model-building APIs such as Sequential,
    Functional, and Subclassing along with eager execution, for immediate
    iteration and intuitive debugging, and `tf.data`, for building scalable
    input pipelines. Checkout
    [guide](https://www.tensorflow.org/beta/guide/keras/overview) for additional
    details.

   *         .add(new Color(0, 191, 255))
   *         .build();
   * }
   *
   * <p>Elements appear in the resulting set in the same order they were first added to the builder.
   *
   * <p>Building does not change the state of the builder, so it is still possible to add more
   * elements and to build again.
   *
   * @since 2.0
   */

./gradlew :distribution:archives:darwin-tar:assemble
./gradlew :distribution:archives:windows-zip:assemble
-----------------------------

=== Running Elasticsearch from a checkout

In order to run Elasticsearch from source without building a package, you can
run it using Gradle:

-------------------------------------
./gradlew run
-------------------------------------

==== Launching and debugging from an IDE

    or

    ```bash
    bazel run //tensorflow/tools/docs:tf_doctest -- --module=ops.array_ops
    ```

    The `--module` is relative to `tensorflow.python`.

#### Debug builds

When [building Tensorflow](https://www.tensorflow.org/install/source), passing
`--config=dbg` to Bazel will build with debugging information and without
optimizations, allowing you to use GDB or other debuggers to debug C++ code. For

        .name("a")
        .value("b")
        .domain("example.com")
        .sameSite(sameSite)
        .build()
    assertThat(cookie.sameSite).isEqualTo(sameSite)
  }

  /** Note that we permit building a cookie that doesn’t follow the rules. */
  @Test fun builderSameSiteNoneDoesNotRequireSecure() {
    val cookieBuilder =
      Cookie
        .Builder()
        .name("a")
        .value("b")

 * {@code 0x7F}), and to strings containing such characters.
 *
 * <p>ASCII utilities also exist in other classes of this package:
 *
 * <ul>
 *   <!-- TODO(kevinb): how can we make this not produce a warning when building gwt javadoc? -->
 *   <li>{@link StandardCharsets#US_ASCII} specifies the {@code Charset} of ASCII characters.
 *   <li>{@link CharMatcher#ascii} matches ASCII characters and provides text processing methods