disabled. It also listens on the IP address `0.0.0.0`, which means all the available IP addresses, this way it will be publicly accessible to anyone that can communicate with the machine. This is how you would normally run it in production, for example, in a container.

In most cases you would (and should) have a "termination proxy" handling HTTPS for you on top, this will depend on how you deploy your application, your provider might do this for you, or you might need to set it up yourself....

including tensorflow-io should be sandboxed if used to process untrusted data.

For example, if an attacker were to upload a malicious video file, they could
potentially exploit a vulnerability in the TensorFlow code that handles videos,
which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches

 *  Fix: Don't crash if a TLS tunnel's response body is truncated.
 *  Fix: Don't track unusable routes beyond their usefulness. We had a bug where we could track
    certain bad routes indefinitely; now we only track the ones that could be necessary.
 *  Fix: Defer proxy selection until a proxy is required. This saves calls to `ProxySelector` on
    calls that use a pooled connection.


## Version 4.3.1

            //
            // If we were to cancel taskFuture, that would let the next task start while the old
            // one is still running.
            //
            // Now, maybe we could tweak our implementation to not start the next task until the
            // callable actually completes. (We could detect completion in our wrapper
            // `AsyncCallable task`.) However, our contract also promises:

@ruy//
EOF

  license_query "attr('licenses', 'notice', deps($BUILD_TARGET))" > $BATS_TEST_TMPDIR/expected_licenses
  license_query "deps($LICENSES_TARGET)" > $BATS_TEST_TMPDIR/actual_licenses

  # Column 1 is left only, Column 2 is right only, Column 3 is shared lines
  # Select lines unique to actual_licenses, i.e. extra licenses.

     *  The implementation of this is a little slow, since it creates
     *  a number of objects each time it is called.  This could be optimized
     *  to keep the same objects around, but then thread-safety issues would arise.
     *
     *  @param contextNode The node to start searching from.
     *  @param expression A valid XPath string.

In Pydantic version 1, you would use an internal class `Config` and `schema_extra`, as described in <a href="https://docs.pydantic.dev/1.10/usage/schema/#schema-customization" class="external-link" target="_blank">Pydantic's docs: Schema customization</a>.

You can set `schema_extra` with a `dict` containing any additional data you would like to show up in the generated JSON Schema, including `examples`.

////

/// tip

        "it.unimi.dsi.fastutil.objects.ReferenceOpenHashSet",
    )
)
plugins.withId("java-base") {
    dependencies {
        attributesSchema {
            attribute(minified)
        }
        // It would be nice if we could be more selective about which variants to apply this to.
        // TODO https://github.com/gradle/gradle/issues/11831#issuecomment-580686994
        artifactTypes.getByName("jar") {

public class ExecutionError extends Error {
  /*
   * Ideally, this class would have exposed only constructors that require a non-null cause. See
   * https://github.com/jspecify/jspecify-reference-checker/blob/61aafa4ae52594830cfc2d61c8b113009dbdb045/src/main/java/com/google/jspecify/nullness/NullSpecTransfer.java#L789
   * and https://github.com/jspecify/jspecify/issues/490.
   *

import gradlebuild.docs.dsl.source.ExtractDslMetaDataTask;

/**
 * Generates DSL reference material using Docbook and some homegrown class parsing.
 *
 * TODO: It would be nice to replace the Docbook portion of this with Asciidoc so that it could be
 * generated in the same way as the user manual with cross-links between them.
 */
public class GradleDslReferencePlugin implements Plugin<Project> {
    @Override