}
        }
    }
}

plugins {
    id("org.gradle.toolchains.foojay-resolver-convention").version("1.0.0")
}

includeBuild("../build-logic-settings")

// Shared basics for all
include("basics")

// Platform: defines shared dependency versions
include("build-platform")

// Compute the identity/version we are building and related details (like current git commit)
include("module-identity")

            // Both wrappers should read the same initial value
            assertEquals("initial.value", wrapper1.getProperty("shared.key"));
            assertEquals("initial.value", wrapper2.getProperty("shared.key"));

            // Write through wrapper1
            wrapper1.setProperty("from.wrapper1", "value1");

            // wrapper2 should see the changes immediately (no caching)

    /**
     * Creates a new request to enumerate shares on a server.
     *
     * @param server the server name to enumerate shares from
     */
    public MsrpcShareEnum(final String server) {
        super("\\\\" + server, 1, new srvsvc.ShareInfoCtr1(), -1, 0, 0);
        this.ptype = 0;
        this.flags = DCERPC_FIRST_FRAG | DCERPC_LAST_FRAG;
    }

    /**
     * Returns the share entries retrieved from the enumeration.
     *

    }),
    tags = [
        "no_cuda_asan",  # TODO(b/181771536)
        "no_windows",  # TODO(b/155444728)
    ],
    # We must ensure that the dependencies can be dynamically linked since
    # the shared library must be able to use core:framework.
    deps = [
        ":c_api",
        ":c_api_internal",
        ":c_test_util",
        ":test_op_kernel",
        ":tf_buffer",
        ":tf_buffer_internal",

        assertNotEquals(a, c);

        // Same subject instance -> equal
        Subject shared = new Subject();
        Kerb5Authenticator d1 = new Kerb5Authenticator(shared);
        Kerb5Authenticator d2 = new Kerb5Authenticator(shared);
        assertEquals(d1, d2);

        // Different type -> false
        assertFalse(a.equals("not-an-auth"));
    }

    @Test

title: TensorFlow, Large-scale machine learning on heterogeneous systems

   * the internal list.
   */
  @JvmStatic
  fun fragmentBuffer(buffer: Buffer): Buffer {
    // Write each byte into a new buffer, then clone it so that the segments are shared.
    // Shared segments cannot be compacted so we'll get a long chain of short segments.
    val result = Buffer()
    while (!buffer.exhausted()) {
      val box = Buffer()
      box.write(buffer, 1)

This can be very useful for setting up **resources** that you need to use for the whole app, and that are **shared** among requests, and/or that you need to **clean up** afterwards. For example, a database connection pool, or loading a shared machine learning model.

## Use Case { #use-case }

Let's start with an example **use case** and then see how to solve it with this.

                  <project path="$PROJECT_DIR$/build-logic/jvm" />
                  <project path="$PROJECT_DIR$/build-logic/kotlin-dsl" />
                  <project path="$PROJECT_DIR$/build-logic/kotlin-dsl-shared-runtime" />
                  <project path="$PROJECT_DIR$/build-logic/lifecycle" />
                  <project path="$PROJECT_DIR$/build-logic/packaging" />

 * SMB1 COM_TREE_DISCONNECT command implementation.
 *
 * This command disconnects from a tree connection (share) on the server.
 * It releases the tree ID and terminates access to the share.
 */
public class SmbComTreeDisconnect extends ServerMessageBlock {

    /**
     * Constructs a tree disconnect request to close a connection to a shared resource.
     *
     * @param config the configuration to use
     */