* penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,
   * and accesses that were performed on the map. The queue is drained on writes and when it exceeds

pkg go/build/constraint, type AndExpr struct, Y Expr
pkg go/build/constraint, type Expr interface, Eval(func(string) bool) bool
pkg go/build/constraint, type Expr interface, String() string
pkg go/build/constraint, type Expr interface, unexported methods
pkg go/build/constraint, type NotExpr struct
pkg go/build/constraint, type NotExpr struct, X Expr
pkg go/build/constraint, type OrExpr struct

   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,
   * and accesses that were performed on the map. The queue is drained on writes and when it exceeds

*   TensorFlow 1.15 is built using devtoolset7 (GCC7) on Ubuntu 16. This may
    lead to ABI incompatibilities with extensions built against earlier versions
    of TensorFlow.
*   Deprecated the use of `constraint=` and `.constraint` with ResourceVariable.
*   `tf.keras`:
    *   `OMP_NUM_THREADS` is no longer used by the default Keras config. To
        configure the number of threads, use `tf.config.threading` APIs.

   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,
   * and accesses that were performed on the map. The queue is drained on writes and when it exceeds

   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,
   * and accesses that were performed on the map. The queue is drained on writes and when it exceeds

  - Added an additional identifier to `ResourceClaim.Status` for the device supports multiple allocations.

plugins {
    `java-platform`
}

group = "gradlebuild"

description = "Provides a platform that constrains versions of external dependencies used by Gradle"

// To try out newer kotlin versions
val kotlinVersion = providers.gradleProperty("buildKotlinVersion")
    .getOrElse(embeddedKotlinVersion)

dependencies {
    constraints {
        val distributionDependencies = versionCatalogs.named("buildLibs")

     * this file is open. This constant may be logically OR'd with other share
     * access flags.
     */
    int FILE_SHARE_READ = 0x01;
    /**
     * When specified as the <code>shareAccess</code> constructor parameter,
     * other SMB clients will be permitted to write to the target file while
     * this file is open. This constant may be logically OR'd with other share
     * access flags.

        // This is yet another reason we need configuration factory methods.
        // workaround for https://github.com/gradle/gradle/issues/12459
        // note: constraints can't be used here because they end up in gradle module metadata
        val attributesFactory = gradle.serviceOf<AttributesFactory>()
        configurations.all {
            if (isCanBeResolved && !isCanBeConsumed) {