// output related parameters
                /*outputs*/ &output, /*output_values*/ &ret,
                /*noutputs*/ 1,
                /*targets*/ nullptr, /*ntargets*/ 0,
                /*run_metadata*/ nullptr, status);
  if (VLOG_IS_ON(1) && status->status.ok()) {
    tensorflow::Tensor tensor;
    if (tensorflow::TF_TensorToTensor(ret, &tensor).ok()) {

build --config=v2

# Precompiling results in some action conflicts. Disable it for now until
# the problematic targets are fixed.
build --@rules_python//python/config_settings:precompile=force_disabled

# TF now has `cc_shared_library` targets, so it needs the experimental flag
# TODO(rostam): Remove when `cc_shared_library` is enabled by default
common --experimental_cc_shared_library

- Admin UI: http://localhost:8080/admin/ (default username/password is admin/admin)

![Admin UI](https://fess.codelibs.org/_images/fess_admin_dashboard.png)

You can register crawling targets in the Admin UI on the (Web, File, Data Store) crawler configuration pages, and then start the Crawler manually on the [Scheduler page](https://fess.codelibs.org/15.0/admin/scheduler-guide.html).

//     affects read from source, block, file, dedup, and object storage backup targets for a specific Veeam Job. When customers
//     create a new backup job and select the object storage or a SOBR as a backup target with this setting, the job default
//     setting will be set to this value. This setting will be only applied to newly created jobs (manual changes with Active Full

	o.DeleteReplication = ReplicationState{
		ReplicateDecisionStr: dsc.String(),
	}
	switch o.VersionID {
	case "":
		o.DeleteReplication.ReplicationStatusInternal = dsc.PendingStatus()
		o.DeleteReplication.Targets = replicationStatusesMap(o.DeleteReplication.ReplicationStatusInternal)
	default:
		o.DeleteReplication.VersionPurgeStatusInternal = dsc.PendingStatus()

Replication from a source bucket to multiple destination buckets is supported. For each of the targets, repeat the steps to configure a remote target ARN and add replication rules to the source bucket's replication config.

your code interacts with the filesystem, network, etc. and uses checkpointed
variables as part of those interactions (ex: using a string variable to build a
filesystem path), a maliciously created checkpoint might be able to change the
targets of those operations, which could result in arbitrary
read/write/executions.

### Running a TensorFlow server

TensorFlow is a platform for distributed computing, and as such there is a

import org.jetbrains.dokka.gradle.DokkaTaskPartial
import org.jetbrains.kotlin.gradle.dsl.JvmTarget
import org.jetbrains.kotlin.gradle.dsl.kotlinExtension
import org.jetbrains.kotlin.gradle.targets.jvm.tasks.KotlinJvmTest
import org.jetbrains.kotlin.gradle.tasks.KotlinCompile
import ru.vyarus.gradle.plugin.animalsniffer.AnimalSnifferExtension
import java.net.URI

buildscript {
  dependencies {

Bucket events can be published to the following targets:

| Supported Notification Targets    |                             |                                 |
| :-------------------------------- | --------------------------- | ------------------------------- |

                       'matching the invocation, inside the log. '
                       'Please look for it in the build log.\n\n')
      failure_msg += (
          f'See the ResultStore link for a detailed view of failed targets:\n'
          f'{url}\n\n')
      failure_msg += (
          f'Here\'s a fragment of the log containing the failure:\n\n'
          f'[ ... TRUNCATED ... ]\n\n'
          f'{invocation_results["log_fragment"]}\n'