}];
}

def AsyncOp: Mlrt_Op<"async", []> {
  let summary = "Launches a function asynchronously.";

  let description = [{
    Launch a function asynchronously.

    $args: a list of arguments to be passed.
    $callee: The function to be launched. Its return op must not have operands.

   // CHECK: _TPUCompileMlir
   // CHECK-SAME: Z
   // CHECK: tf_device.launch
   // CHECK-NEXT: _TPUCompileMlir
   // CHECK-SAME: X
   // CHECK: tf_device.launch
   // CHECK-NEXT: _TPUCompileMlir
   // CHECK-SAME: Y
   // CHECK: OpA
   // CHECK: OpB
   // CHECK: OpC
   "tf.OpA"() : () -> ()
   "tf_device.launch"() ({

          %b1 = "tf.AddV2"(%barg0, %0) {T = i32, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
          // CHECK: %[[COMPILE:.*]]:2 = "tf_device.launch"
          // CHECK-NEXT: "tf._TPUCompileMlir"()
          %compile:2 = "tf_device.launch"() ({
            %b2:2 = "tf._TPUCompileMlir"() {
              NumDynamicShapes = 0 : i64,
              // The metadata encodes 2 parameter and 2 return values.

import common.VersionedSettingsBranch
import vcsroots.gradlePromotionBranches

class PublishNightlySnapshotFromQuickFeedback(branch: VersionedSettingsBranch) : PublishGradleDistributionFullBuild(
    promotedBranch = branch.branchName,
    prepTask = branch.prepNightlyTaskName(),
    promoteTask = branch.promoteNightlyTaskName(),
    triggerName = "QuickFeedback",
    vcsRootId = gradlePromotionBranches
) {
    init {

    after a _TPUCompileMlir op if there is no predecessor _TPUCompileMlir op.
    Both the embedding op and compile op are assumed to be wrapped in separate
    tf_device.launch() ops. This is because the embedding op is head outside
    compiled and the compile op is wrapped in launch to execute on host
    during TPURewritePass.

    For example, the tf.OpA with the `mini_batch_splits` attribute will be

cmp stdout $WORK/gopath/src/want_list.txt
-- tree/go.mod --
module example.com/tree

go 1.20
-- tree/tree.go --
package tree
-- tree/branch/branch.go --
package branch
-- dir2/squirrel.go --
package squirrel
-- want_list.txt --
example.com/tree

        failure.assertHasCause(message)

        where:
        metadata        | message
        "branch ''"     | "Invalid publication 'ivy': branch cannot be an empty string. Use null instead"
        "branch 'a\tb'" | "Invalid publication 'ivy': branch cannot contain ISO control character '\\u0009'"
        "status ''"     | "Invalid publication 'ivy': status cannot be an empty string. Use null instead"

plugins {
    id 'cpp'
}

// tag::flavors[]
model {
    flavors {
        english
        french
    }
    components {
        hello(NativeLibrarySpec) {
            binaries.all {
                if (flavor == flavors.french) {
                    cppCompiler.define "FRENCH"
                }
            }
        }
    }
}
// end::flavors[]

model {
    binaries {

based on a specific branch. Currently, we have two pipelines: `master` and `release`, but you can easily create
and test another isolated pipeline from any branch. 

We'll explain everything via an example. Let's say you make some changes on your branch `myTestBranch`
(we highly recommend to name this branch without prefix and hyphen (`-`) because it's used to generate build type ID) and want to

name: Set nightly branch to master HEAD

permissions: {}

jobs:
  master-to-nightly:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: ubuntu-latest
    permissions:
      contents: write
    steps:
    - uses: zofrex/mirror-branch@a8809f0b42f9dfe9b2c5c2162a46327c23d15266 # v1.0.3
      name: Set nightly branch to master HEAD
      with: