Docs Packages
  1. Packages
  2. Google Cloud Native
  3. API Docs
  4. aiplatform
  5. aiplatform/v1
  6. NasJob

Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

google-native.aiplatform/v1.NasJob

Explore with Pulumi AI

google-native logo

Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

    Creates a NasJob Auto-naming is currently not supported for this resource.

    Create NasJob Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new NasJob(name: string, args: NasJobArgs, opts?: CustomResourceOptions);
    @overload
def NasJob(resource_name: str,
           args: NasJobArgs,
           opts: Optional[ResourceOptions] = None)

@overload
def NasJob(resource_name: str,
           opts: Optional[ResourceOptions] = None,
           display_name: Optional[str] = None,
           nas_job_spec: Optional[GoogleCloudAiplatformV1NasJobSpecArgs] = None,
           enable_restricted_image_training: Optional[bool] = None,
           encryption_spec: Optional[GoogleCloudAiplatformV1EncryptionSpecArgs] = None,
           labels: Optional[Mapping[str, str]] = None,
           location: Optional[str] = None,
           project: Optional[str] = None)
    func NewNasJob(ctx *Context, name string, args NasJobArgs, opts ...ResourceOption) (*NasJob, error)
    public NasJob(string name, NasJobArgs args, CustomResourceOptions? opts = null)
    public NasJob(String name, NasJobArgs args)
public NasJob(String name, NasJobArgs args, CustomResourceOptions options)

    type: google-native:aiplatform/v1:NasJob
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args NasJobArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args NasJobArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args NasJobArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args NasJobArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args NasJobArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Example

    The following reference example uses placeholder values for all input properties.

    var nasJobResource = new GoogleNative.Aiplatform.V1.NasJob("nasJobResource", new()
{
    DisplayName = "string",
    NasJobSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecArgs
    {
        MultiTrialAlgorithmSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs
        {
            SearchTrialSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs
            {
                MaxParallelTrialCount = 0,
                MaxTrialCount = 0,
                SearchTrialJobSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1CustomJobSpecArgs
                {
                    WorkerPoolSpecs = new[]
                    {
                        new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1WorkerPoolSpecArgs
                        {
                            ContainerSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1ContainerSpecArgs
                            {
                                ImageUri = "string",
                                Args = new[]
                                {
                                    "string",
                                },
                                Command = new[]
                                {
                                    "string",
                                },
                                Env = new[]
                                {
                                    new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EnvVarArgs
                                    {
                                        Name = "string",
                                        Value = "string",
                                    },
                                },
                            },
                            DiskSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1DiskSpecArgs
                            {
                                BootDiskSizeGb = 0,
                                BootDiskType = "string",
                            },
                            MachineSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1MachineSpecArgs
                            {
                                AcceleratorCount = 0,
                                AcceleratorType = GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1MachineSpecAcceleratorType.AcceleratorTypeUnspecified,
                                MachineType = "string",
                                TpuTopology = "string",
                            },
                            NfsMounts = new[]
                            {
                                new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NfsMountArgs
                                {
                                    MountPoint = "string",
                                    Path = "string",
                                    Server = "string",
                                },
                            },
                            PythonPackageSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PythonPackageSpecArgs
                            {
                                ExecutorImageUri = "string",
                                PackageUris = new[]
                                {
                                    "string",
                                },
                                PythonModule = "string",
                                Args = new[]
                                {
                                    "string",
                                },
                                Env = new[]
                                {
                                    new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EnvVarArgs
                                    {
                                        Name = "string",
                                        Value = "string",
                                    },
                                },
                            },
                            ReplicaCount = "string",
                        },
                    },
                    BaseOutputDirectory = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1GcsDestinationArgs
                    {
                        OutputUriPrefix = "string",
                    },
                    EnableDashboardAccess = false,
                    EnableWebAccess = false,
                    Experiment = "string",
                    ExperimentRun = "string",
                    Network = "string",
                    ProtectedArtifactLocationId = "string",
                    ReservedIpRanges = new[]
                    {
                        "string",
                    },
                    Scheduling = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1SchedulingArgs
                    {
                        DisableRetries = false,
                        RestartJobOnWorkerRestart = false,
                        Timeout = "string",
                    },
                    ServiceAccount = "string",
                    Tensorboard = "string",
                },
                MaxFailedTrialCount = 0,
            },
            Metric = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs
            {
                Goal = GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal.GoalTypeUnspecified,
                MetricId = "string",
            },
            MultiTrialAlgorithm = GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm.MultiTrialAlgorithmUnspecified,
            TrainTrialSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs
            {
                Frequency = 0,
                MaxParallelTrialCount = 0,
                TrainTrialJobSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1CustomJobSpecArgs
                {
                    WorkerPoolSpecs = new[]
                    {
                        new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1WorkerPoolSpecArgs
                        {
                            ContainerSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1ContainerSpecArgs
                            {
                                ImageUri = "string",
                                Args = new[]
                                {
                                    "string",
                                },
                                Command = new[]
                                {
                                    "string",
                                },
                                Env = new[]
                                {
                                    new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EnvVarArgs
                                    {
                                        Name = "string",
                                        Value = "string",
                                    },
                                },
                            },
                            DiskSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1DiskSpecArgs
                            {
                                BootDiskSizeGb = 0,
                                BootDiskType = "string",
                            },
                            MachineSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1MachineSpecArgs
                            {
                                AcceleratorCount = 0,
                                AcceleratorType = GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1MachineSpecAcceleratorType.AcceleratorTypeUnspecified,
                                MachineType = "string",
                                TpuTopology = "string",
                            },
                            NfsMounts = new[]
                            {
                                new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NfsMountArgs
                                {
                                    MountPoint = "string",
                                    Path = "string",
                                    Server = "string",
                                },
                            },
                            PythonPackageSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PythonPackageSpecArgs
                            {
                                ExecutorImageUri = "string",
                                PackageUris = new[]
                                {
                                    "string",
                                },
                                PythonModule = "string",
                                Args = new[]
                                {
                                    "string",
                                },
                                Env = new[]
                                {
                                    new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EnvVarArgs
                                    {
                                        Name = "string",
                                        Value = "string",
                                    },
                                },
                            },
                            ReplicaCount = "string",
                        },
                    },
                    BaseOutputDirectory = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1GcsDestinationArgs
                    {
                        OutputUriPrefix = "string",
                    },
                    EnableDashboardAccess = false,
                    EnableWebAccess = false,
                    Experiment = "string",
                    ExperimentRun = "string",
                    Network = "string",
                    ProtectedArtifactLocationId = "string",
                    ReservedIpRanges = new[]
                    {
                        "string",
                    },
                    Scheduling = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1SchedulingArgs
                    {
                        DisableRetries = false,
                        RestartJobOnWorkerRestart = false,
                        Timeout = "string",
                    },
                    ServiceAccount = "string",
                    Tensorboard = "string",
                },
            },
        },
        ResumeNasJobId = "string",
        SearchSpaceSpec = "string",
    },
    EnableRestrictedImageTraining = false,
    EncryptionSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EncryptionSpecArgs
    {
        KmsKeyName = "string",
    },
    Labels = 
    {
        { "string", "string" },
    },
    Location = "string",
    Project = "string",
});

    example, err := aiplatform.NewNasJob(ctx, "nasJobResource", &aiplatform.NasJobArgs{
DisplayName: pulumi.String("string"),
NasJobSpec: &aiplatform.GoogleCloudAiplatformV1NasJobSpecArgs{
MultiTrialAlgorithmSpec: &aiplatform.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs{
SearchTrialSpec: &aiplatform.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs{
MaxParallelTrialCount: pulumi.Int(0),
MaxTrialCount: pulumi.Int(0),
SearchTrialJobSpec: &aiplatform.GoogleCloudAiplatformV1CustomJobSpecArgs{
WorkerPoolSpecs: aiplatform.GoogleCloudAiplatformV1WorkerPoolSpecArray{
&aiplatform.GoogleCloudAiplatformV1WorkerPoolSpecArgs{
ContainerSpec: &aiplatform.GoogleCloudAiplatformV1ContainerSpecArgs{
ImageUri: pulumi.String("string"),
Args: pulumi.StringArray{
pulumi.String("string"),
},
Command: pulumi.StringArray{
pulumi.String("string"),
},
Env: aiplatform.GoogleCloudAiplatformV1EnvVarArray{
&aiplatform.GoogleCloudAiplatformV1EnvVarArgs{
Name: pulumi.String("string"),
Value: pulumi.String("string"),
},
},
},
DiskSpec: &aiplatform.GoogleCloudAiplatformV1DiskSpecArgs{
BootDiskSizeGb: pulumi.Int(0),
BootDiskType: pulumi.String("string"),
},
MachineSpec: &aiplatform.GoogleCloudAiplatformV1MachineSpecArgs{
AcceleratorCount: pulumi.Int(0),
AcceleratorType: aiplatform.GoogleCloudAiplatformV1MachineSpecAcceleratorTypeAcceleratorTypeUnspecified,
MachineType: pulumi.String("string"),
TpuTopology: pulumi.String("string"),
},
NfsMounts: aiplatform.GoogleCloudAiplatformV1NfsMountArray{
&aiplatform.GoogleCloudAiplatformV1NfsMountArgs{
MountPoint: pulumi.String("string"),
Path: pulumi.String("string"),
Server: pulumi.String("string"),
},
},
PythonPackageSpec: &aiplatform.GoogleCloudAiplatformV1PythonPackageSpecArgs{
ExecutorImageUri: pulumi.String("string"),
PackageUris: pulumi.StringArray{
pulumi.String("string"),
},
PythonModule: pulumi.String("string"),
Args: pulumi.StringArray{
pulumi.String("string"),
},
Env: aiplatform.GoogleCloudAiplatformV1EnvVarArray{
&aiplatform.GoogleCloudAiplatformV1EnvVarArgs{
Name: pulumi.String("string"),
Value: pulumi.String("string"),
},
},
},
ReplicaCount: pulumi.String("string"),
},
},
BaseOutputDirectory: &aiplatform.GoogleCloudAiplatformV1GcsDestinationArgs{
OutputUriPrefix: pulumi.String("string"),
},
EnableDashboardAccess: pulumi.Bool(false),
EnableWebAccess: pulumi.Bool(false),
Experiment: pulumi.String("string"),
ExperimentRun: pulumi.String("string"),
Network: pulumi.String("string"),
ProtectedArtifactLocationId: pulumi.String("string"),
ReservedIpRanges: pulumi.StringArray{
pulumi.String("string"),
},
Scheduling: &aiplatform.GoogleCloudAiplatformV1SchedulingArgs{
DisableRetries: pulumi.Bool(false),
RestartJobOnWorkerRestart: pulumi.Bool(false),
Timeout: pulumi.String("string"),
},
ServiceAccount: pulumi.String("string"),
Tensorboard: pulumi.String("string"),
},
MaxFailedTrialCount: pulumi.Int(0),
},
Metric: &aiplatform.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs{
Goal: aiplatform.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalGoalTypeUnspecified,
MetricId: pulumi.String("string"),
},
MultiTrialAlgorithm: aiplatform.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmMultiTrialAlgorithmUnspecified,
TrainTrialSpec: &aiplatform.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs{
Frequency: pulumi.Int(0),
MaxParallelTrialCount: pulumi.Int(0),
TrainTrialJobSpec: &aiplatform.GoogleCloudAiplatformV1CustomJobSpecArgs{
WorkerPoolSpecs: aiplatform.GoogleCloudAiplatformV1WorkerPoolSpecArray{
&aiplatform.GoogleCloudAiplatformV1WorkerPoolSpecArgs{
ContainerSpec: &aiplatform.GoogleCloudAiplatformV1ContainerSpecArgs{
ImageUri: pulumi.String("string"),
Args: pulumi.StringArray{
pulumi.String("string"),
},
Command: pulumi.StringArray{
pulumi.String("string"),
},
Env: aiplatform.GoogleCloudAiplatformV1EnvVarArray{
&aiplatform.GoogleCloudAiplatformV1EnvVarArgs{
Name: pulumi.String("string"),
Value: pulumi.String("string"),
},
},
},
DiskSpec: &aiplatform.GoogleCloudAiplatformV1DiskSpecArgs{
BootDiskSizeGb: pulumi.Int(0),
BootDiskType: pulumi.String("string"),
},
MachineSpec: &aiplatform.GoogleCloudAiplatformV1MachineSpecArgs{
AcceleratorCount: pulumi.Int(0),
AcceleratorType: aiplatform.GoogleCloudAiplatformV1MachineSpecAcceleratorTypeAcceleratorTypeUnspecified,
MachineType: pulumi.String("string"),
TpuTopology: pulumi.String("string"),
},
NfsMounts: aiplatform.GoogleCloudAiplatformV1NfsMountArray{
&aiplatform.GoogleCloudAiplatformV1NfsMountArgs{
MountPoint: pulumi.String("string"),
Path: pulumi.String("string"),
Server: pulumi.String("string"),
},
},
PythonPackageSpec: &aiplatform.GoogleCloudAiplatformV1PythonPackageSpecArgs{
ExecutorImageUri: pulumi.String("string"),
PackageUris: pulumi.StringArray{
pulumi.String("string"),
},
PythonModule: pulumi.String("string"),
Args: pulumi.StringArray{
pulumi.String("string"),
},
Env: aiplatform.GoogleCloudAiplatformV1EnvVarArray{
&aiplatform.GoogleCloudAiplatformV1EnvVarArgs{
Name: pulumi.String("string"),
Value: pulumi.String("string"),
},
},
},
ReplicaCount: pulumi.String("string"),
},
},
BaseOutputDirectory: &aiplatform.GoogleCloudAiplatformV1GcsDestinationArgs{
OutputUriPrefix: pulumi.String("string"),
},
EnableDashboardAccess: pulumi.Bool(false),
EnableWebAccess: pulumi.Bool(false),
Experiment: pulumi.String("string"),
ExperimentRun: pulumi.String("string"),
Network: pulumi.String("string"),
ProtectedArtifactLocationId: pulumi.String("string"),
ReservedIpRanges: pulumi.StringArray{
pulumi.String("string"),
},
Scheduling: &aiplatform.GoogleCloudAiplatformV1SchedulingArgs{
DisableRetries: pulumi.Bool(false),
RestartJobOnWorkerRestart: pulumi.Bool(false),
Timeout: pulumi.String("string"),
},
ServiceAccount: pulumi.String("string"),
Tensorboard: pulumi.String("string"),
},
},
},
ResumeNasJobId: pulumi.String("string"),
SearchSpaceSpec: pulumi.String("string"),
},
EnableRestrictedImageTraining: pulumi.Bool(false),
EncryptionSpec: &aiplatform.GoogleCloudAiplatformV1EncryptionSpecArgs{
KmsKeyName: pulumi.String("string"),
},
Labels: pulumi.StringMap{
"string": pulumi.String("string"),
},
Location: pulumi.String("string"),
Project: pulumi.String("string"),
})

    var nasJobResource = new NasJob("nasJobResource", NasJobArgs.builder()        
    .displayName("string")
    .nasJobSpec(GoogleCloudAiplatformV1NasJobSpecArgs.builder()
        .multiTrialAlgorithmSpec(GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs.builder()
            .searchTrialSpec(GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs.builder()
                .maxParallelTrialCount(0)
                .maxTrialCount(0)
                .searchTrialJobSpec(GoogleCloudAiplatformV1CustomJobSpecArgs.builder()
                    .workerPoolSpecs(GoogleCloudAiplatformV1WorkerPoolSpecArgs.builder()
                        .containerSpec(GoogleCloudAiplatformV1ContainerSpecArgs.builder()
                            .imageUri("string")
                            .args("string")
                            .command("string")
                            .env(GoogleCloudAiplatformV1EnvVarArgs.builder()
                                .name("string")
                                .value("string")
                                .build())
                            .build())
                        .diskSpec(GoogleCloudAiplatformV1DiskSpecArgs.builder()
                            .bootDiskSizeGb(0)
                            .bootDiskType("string")
                            .build())
                        .machineSpec(GoogleCloudAiplatformV1MachineSpecArgs.builder()
                            .acceleratorCount(0)
                            .acceleratorType("ACCELERATOR_TYPE_UNSPECIFIED")
                            .machineType("string")
                            .tpuTopology("string")
                            .build())
                        .nfsMounts(GoogleCloudAiplatformV1NfsMountArgs.builder()
                            .mountPoint("string")
                            .path("string")
                            .server("string")
                            .build())
                        .pythonPackageSpec(GoogleCloudAiplatformV1PythonPackageSpecArgs.builder()
                            .executorImageUri("string")
                            .packageUris("string")
                            .pythonModule("string")
                            .args("string")
                            .env(GoogleCloudAiplatformV1EnvVarArgs.builder()
                                .name("string")
                                .value("string")
                                .build())
                            .build())
                        .replicaCount("string")
                        .build())
                    .baseOutputDirectory(GoogleCloudAiplatformV1GcsDestinationArgs.builder()
                        .outputUriPrefix("string")
                        .build())
                    .enableDashboardAccess(false)
                    .enableWebAccess(false)
                    .experiment("string")
                    .experimentRun("string")
                    .network("string")
                    .protectedArtifactLocationId("string")
                    .reservedIpRanges("string")
                    .scheduling(GoogleCloudAiplatformV1SchedulingArgs.builder()
                        .disableRetries(false)
                        .restartJobOnWorkerRestart(false)
                        .timeout("string")
                        .build())
                    .serviceAccount("string")
                    .tensorboard("string")
                    .build())
                .maxFailedTrialCount(0)
                .build())
            .metric(GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs.builder()
                .goal("GOAL_TYPE_UNSPECIFIED")
                .metricId("string")
                .build())
            .multiTrialAlgorithm("MULTI_TRIAL_ALGORITHM_UNSPECIFIED")
            .trainTrialSpec(GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs.builder()
                .frequency(0)
                .maxParallelTrialCount(0)
                .trainTrialJobSpec(GoogleCloudAiplatformV1CustomJobSpecArgs.builder()
                    .workerPoolSpecs(GoogleCloudAiplatformV1WorkerPoolSpecArgs.builder()
                        .containerSpec(GoogleCloudAiplatformV1ContainerSpecArgs.builder()
                            .imageUri("string")
                            .args("string")
                            .command("string")
                            .env(GoogleCloudAiplatformV1EnvVarArgs.builder()
                                .name("string")
                                .value("string")
                                .build())
                            .build())
                        .diskSpec(GoogleCloudAiplatformV1DiskSpecArgs.builder()
                            .bootDiskSizeGb(0)
                            .bootDiskType("string")
                            .build())
                        .machineSpec(GoogleCloudAiplatformV1MachineSpecArgs.builder()
                            .acceleratorCount(0)
                            .acceleratorType("ACCELERATOR_TYPE_UNSPECIFIED")
                            .machineType("string")
                            .tpuTopology("string")
                            .build())
                        .nfsMounts(GoogleCloudAiplatformV1NfsMountArgs.builder()
                            .mountPoint("string")
                            .path("string")
                            .server("string")
                            .build())
                        .pythonPackageSpec(GoogleCloudAiplatformV1PythonPackageSpecArgs.builder()
                            .executorImageUri("string")
                            .packageUris("string")
                            .pythonModule("string")
                            .args("string")
                            .env(GoogleCloudAiplatformV1EnvVarArgs.builder()
                                .name("string")
                                .value("string")
                                .build())
                            .build())
                        .replicaCount("string")
                        .build())
                    .baseOutputDirectory(GoogleCloudAiplatformV1GcsDestinationArgs.builder()
                        .outputUriPrefix("string")
                        .build())
                    .enableDashboardAccess(false)
                    .enableWebAccess(false)
                    .experiment("string")
                    .experimentRun("string")
                    .network("string")
                    .protectedArtifactLocationId("string")
                    .reservedIpRanges("string")
                    .scheduling(GoogleCloudAiplatformV1SchedulingArgs.builder()
                        .disableRetries(false)
                        .restartJobOnWorkerRestart(false)
                        .timeout("string")
                        .build())
                    .serviceAccount("string")
                    .tensorboard("string")
                    .build())
                .build())
            .build())
        .resumeNasJobId("string")
        .searchSpaceSpec("string")
        .build())
    .enableRestrictedImageTraining(false)
    .encryptionSpec(GoogleCloudAiplatformV1EncryptionSpecArgs.builder()
        .kmsKeyName("string")
        .build())
    .labels(Map.of("string", "string"))
    .location("string")
    .project("string")
    .build());

    nas_job_resource = google_native.aiplatform.v1.NasJob("nasJobResource",
    display_name="string",
    nas_job_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1NasJobSpecArgs(
        multi_trial_algorithm_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs(
            search_trial_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs(
                max_parallel_trial_count=0,
                max_trial_count=0,
                search_trial_job_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1CustomJobSpecArgs(
                    worker_pool_specs=[google_native.aiplatform.v1.GoogleCloudAiplatformV1WorkerPoolSpecArgs(
                        container_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1ContainerSpecArgs(
                            image_uri="string",
                            args=["string"],
                            command=["string"],
                            env=[google_native.aiplatform.v1.GoogleCloudAiplatformV1EnvVarArgs(
                                name="string",
                                value="string",
                            )],
                        ),
                        disk_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1DiskSpecArgs(
                            boot_disk_size_gb=0,
                            boot_disk_type="string",
                        ),
                        machine_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1MachineSpecArgs(
                            accelerator_count=0,
                            accelerator_type=google_native.aiplatform.v1.GoogleCloudAiplatformV1MachineSpecAcceleratorType.ACCELERATOR_TYPE_UNSPECIFIED,
                            machine_type="string",
                            tpu_topology="string",
                        ),
                        nfs_mounts=[google_native.aiplatform.v1.GoogleCloudAiplatformV1NfsMountArgs(
                            mount_point="string",
                            path="string",
                            server="string",
                        )],
                        python_package_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1PythonPackageSpecArgs(
                            executor_image_uri="string",
                            package_uris=["string"],
                            python_module="string",
                            args=["string"],
                            env=[google_native.aiplatform.v1.GoogleCloudAiplatformV1EnvVarArgs(
                                name="string",
                                value="string",
                            )],
                        ),
                        replica_count="string",
                    )],
                    base_output_directory=google_native.aiplatform.v1.GoogleCloudAiplatformV1GcsDestinationArgs(
                        output_uri_prefix="string",
                    ),
                    enable_dashboard_access=False,
                    enable_web_access=False,
                    experiment="string",
                    experiment_run="string",
                    network="string",
                    protected_artifact_location_id="string",
                    reserved_ip_ranges=["string"],
                    scheduling=google_native.aiplatform.v1.GoogleCloudAiplatformV1SchedulingArgs(
                        disable_retries=False,
                        restart_job_on_worker_restart=False,
                        timeout="string",
                    ),
                    service_account="string",
                    tensorboard="string",
                ),
                max_failed_trial_count=0,
            ),
            metric=google_native.aiplatform.v1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs(
                goal=google_native.aiplatform.v1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal.GOAL_TYPE_UNSPECIFIED,
                metric_id="string",
            ),
            multi_trial_algorithm=google_native.aiplatform.v1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm.MULTI_TRIAL_ALGORITHM_UNSPECIFIED,
            train_trial_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs(
                frequency=0,
                max_parallel_trial_count=0,
                train_trial_job_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1CustomJobSpecArgs(
                    worker_pool_specs=[google_native.aiplatform.v1.GoogleCloudAiplatformV1WorkerPoolSpecArgs(
                        container_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1ContainerSpecArgs(
                            image_uri="string",
                            args=["string"],
                            command=["string"],
                            env=[google_native.aiplatform.v1.GoogleCloudAiplatformV1EnvVarArgs(
                                name="string",
                                value="string",
                            )],
                        ),
                        disk_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1DiskSpecArgs(
                            boot_disk_size_gb=0,
                            boot_disk_type="string",
                        ),
                        machine_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1MachineSpecArgs(
                            accelerator_count=0,
                            accelerator_type=google_native.aiplatform.v1.GoogleCloudAiplatformV1MachineSpecAcceleratorType.ACCELERATOR_TYPE_UNSPECIFIED,
                            machine_type="string",
                            tpu_topology="string",
                        ),
                        nfs_mounts=[google_native.aiplatform.v1.GoogleCloudAiplatformV1NfsMountArgs(
                            mount_point="string",
                            path="string",
                            server="string",
                        )],
                        python_package_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1PythonPackageSpecArgs(
                            executor_image_uri="string",
                            package_uris=["string"],
                            python_module="string",
                            args=["string"],
                            env=[google_native.aiplatform.v1.GoogleCloudAiplatformV1EnvVarArgs(
                                name="string",
                                value="string",
                            )],
                        ),
                        replica_count="string",
                    )],
                    base_output_directory=google_native.aiplatform.v1.GoogleCloudAiplatformV1GcsDestinationArgs(
                        output_uri_prefix="string",
                    ),
                    enable_dashboard_access=False,
                    enable_web_access=False,
                    experiment="string",
                    experiment_run="string",
                    network="string",
                    protected_artifact_location_id="string",
                    reserved_ip_ranges=["string"],
                    scheduling=google_native.aiplatform.v1.GoogleCloudAiplatformV1SchedulingArgs(
                        disable_retries=False,
                        restart_job_on_worker_restart=False,
                        timeout="string",
                    ),
                    service_account="string",
                    tensorboard="string",
                ),
            ),
        ),
        resume_nas_job_id="string",
        search_space_spec="string",
    ),
    enable_restricted_image_training=False,
    encryption_spec=google_native.aiplatform.v1.GoogleCloudAiplatformV1EncryptionSpecArgs(
        kms_key_name="string",
    ),
    labels={
        "string": "string",
    },
    location="string",
    project="string")

    const nasJobResource = new google_native.aiplatform.v1.NasJob("nasJobResource", {
    displayName: "string",
    nasJobSpec: {
        multiTrialAlgorithmSpec: {
            searchTrialSpec: {
                maxParallelTrialCount: 0,
                maxTrialCount: 0,
                searchTrialJobSpec: {
                    workerPoolSpecs: [{
                        containerSpec: {
                            imageUri: "string",
                            args: ["string"],
                            command: ["string"],
                            env: [{
                                name: "string",
                                value: "string",
                            }],
                        },
                        diskSpec: {
                            bootDiskSizeGb: 0,
                            bootDiskType: "string",
                        },
                        machineSpec: {
                            acceleratorCount: 0,
                            acceleratorType: google_native.aiplatform.v1.GoogleCloudAiplatformV1MachineSpecAcceleratorType.AcceleratorTypeUnspecified,
                            machineType: "string",
                            tpuTopology: "string",
                        },
                        nfsMounts: [{
                            mountPoint: "string",
                            path: "string",
                            server: "string",
                        }],
                        pythonPackageSpec: {
                            executorImageUri: "string",
                            packageUris: ["string"],
                            pythonModule: "string",
                            args: ["string"],
                            env: [{
                                name: "string",
                                value: "string",
                            }],
                        },
                        replicaCount: "string",
                    }],
                    baseOutputDirectory: {
                        outputUriPrefix: "string",
                    },
                    enableDashboardAccess: false,
                    enableWebAccess: false,
                    experiment: "string",
                    experimentRun: "string",
                    network: "string",
                    protectedArtifactLocationId: "string",
                    reservedIpRanges: ["string"],
                    scheduling: {
                        disableRetries: false,
                        restartJobOnWorkerRestart: false,
                        timeout: "string",
                    },
                    serviceAccount: "string",
                    tensorboard: "string",
                },
                maxFailedTrialCount: 0,
            },
            metric: {
                goal: google_native.aiplatform.v1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal.GoalTypeUnspecified,
                metricId: "string",
            },
            multiTrialAlgorithm: google_native.aiplatform.v1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm.MultiTrialAlgorithmUnspecified,
            trainTrialSpec: {
                frequency: 0,
                maxParallelTrialCount: 0,
                trainTrialJobSpec: {
                    workerPoolSpecs: [{
                        containerSpec: {
                            imageUri: "string",
                            args: ["string"],
                            command: ["string"],
                            env: [{
                                name: "string",
                                value: "string",
                            }],
                        },
                        diskSpec: {
                            bootDiskSizeGb: 0,
                            bootDiskType: "string",
                        },
                        machineSpec: {
                            acceleratorCount: 0,
                            acceleratorType: google_native.aiplatform.v1.GoogleCloudAiplatformV1MachineSpecAcceleratorType.AcceleratorTypeUnspecified,
                            machineType: "string",
                            tpuTopology: "string",
                        },
                        nfsMounts: [{
                            mountPoint: "string",
                            path: "string",
                            server: "string",
                        }],
                        pythonPackageSpec: {
                            executorImageUri: "string",
                            packageUris: ["string"],
                            pythonModule: "string",
                            args: ["string"],
                            env: [{
                                name: "string",
                                value: "string",
                            }],
                        },
                        replicaCount: "string",
                    }],
                    baseOutputDirectory: {
                        outputUriPrefix: "string",
                    },
                    enableDashboardAccess: false,
                    enableWebAccess: false,
                    experiment: "string",
                    experimentRun: "string",
                    network: "string",
                    protectedArtifactLocationId: "string",
                    reservedIpRanges: ["string"],
                    scheduling: {
                        disableRetries: false,
                        restartJobOnWorkerRestart: false,
                        timeout: "string",
                    },
                    serviceAccount: "string",
                    tensorboard: "string",
                },
            },
        },
        resumeNasJobId: "string",
        searchSpaceSpec: "string",
    },
    enableRestrictedImageTraining: false,
    encryptionSpec: {
        kmsKeyName: "string",
    },
    labels: {
        string: "string",
    },
    location: "string",
    project: "string",
});

    type: google-native:aiplatform/v1:NasJob
properties:
    displayName: string
    enableRestrictedImageTraining: false
    encryptionSpec:
        kmsKeyName: string
    labels:
        string: string
    location: string
    nasJobSpec:
        multiTrialAlgorithmSpec:
            metric:
                goal: GOAL_TYPE_UNSPECIFIED
                metricId: string
            multiTrialAlgorithm: MULTI_TRIAL_ALGORITHM_UNSPECIFIED
            searchTrialSpec:
                maxFailedTrialCount: 0
                maxParallelTrialCount: 0
                maxTrialCount: 0
                searchTrialJobSpec:
                    baseOutputDirectory:
                        outputUriPrefix: string
                    enableDashboardAccess: false
                    enableWebAccess: false
                    experiment: string
                    experimentRun: string
                    network: string
                    protectedArtifactLocationId: string
                    reservedIpRanges:
                        - string
                    scheduling:
                        disableRetries: false
                        restartJobOnWorkerRestart: false
                        timeout: string
                    serviceAccount: string
                    tensorboard: string
                    workerPoolSpecs:
                        - containerSpec:
                            args:
                                - string
                            command:
                                - string
                            env:
                                - name: string
                                  value: string
                            imageUri: string
                          diskSpec:
                            bootDiskSizeGb: 0
                            bootDiskType: string
                          machineSpec:
                            acceleratorCount: 0
                            acceleratorType: ACCELERATOR_TYPE_UNSPECIFIED
                            machineType: string
                            tpuTopology: string
                          nfsMounts:
                            - mountPoint: string
                              path: string
                              server: string
                          pythonPackageSpec:
                            args:
                                - string
                            env:
                                - name: string
                                  value: string
                            executorImageUri: string
                            packageUris:
                                - string
                            pythonModule: string
                          replicaCount: string
            trainTrialSpec:
                frequency: 0
                maxParallelTrialCount: 0
                trainTrialJobSpec:
                    baseOutputDirectory:
                        outputUriPrefix: string
                    enableDashboardAccess: false
                    enableWebAccess: false
                    experiment: string
                    experimentRun: string
                    network: string
                    protectedArtifactLocationId: string
                    reservedIpRanges:
                        - string
                    scheduling:
                        disableRetries: false
                        restartJobOnWorkerRestart: false
                        timeout: string
                    serviceAccount: string
                    tensorboard: string
                    workerPoolSpecs:
                        - containerSpec:
                            args:
                                - string
                            command:
                                - string
                            env:
                                - name: string
                                  value: string
                            imageUri: string
                          diskSpec:
                            bootDiskSizeGb: 0
                            bootDiskType: string
                          machineSpec:
                            acceleratorCount: 0
                            acceleratorType: ACCELERATOR_TYPE_UNSPECIFIED
                            machineType: string
                            tpuTopology: string
                          nfsMounts:
                            - mountPoint: string
                              path: string
                              server: string
                          pythonPackageSpec:
                            args:
                                - string
                            env:
                                - name: string
                                  value: string
                            executorImageUri: string
                            packageUris:
                                - string
                            pythonModule: string
                          replicaCount: string
        resumeNasJobId: string
        searchSpaceSpec: string
    project: string

    NasJob Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    The NasJob resource accepts the following input properties:

    DisplayName string
    The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    NasJobSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpec
    The specification of a NasJob.
    EnableRestrictedImageTraining bool
    Optional. Enable a separation of Custom model training and restricted image training for tenant project.
    EncryptionSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EncryptionSpec
    Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.
    Labels Dictionary<string, string>
    The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
    Location string
    Project string
    DisplayName string
    The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    NasJobSpec GoogleCloudAiplatformV1NasJobSpecArgs
    The specification of a NasJob.
    EnableRestrictedImageTraining bool
    Optional. Enable a separation of Custom model training and restricted image training for tenant project.
    EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecArgs
    Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.
    Labels map[string]string
    The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
    Location string
    Project string
    displayName String
    The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    nasJobSpec GoogleCloudAiplatformV1NasJobSpec
    The specification of a NasJob.
    enableRestrictedImageTraining Boolean
    Optional. Enable a separation of Custom model training and restricted image training for tenant project.
    encryptionSpec GoogleCloudAiplatformV1EncryptionSpec
    Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.
    labels Map<String,String>
    The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
    location String
    project String
    displayName string
    The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    nasJobSpec GoogleCloudAiplatformV1NasJobSpec
    The specification of a NasJob.
    enableRestrictedImageTraining boolean
    Optional. Enable a separation of Custom model training and restricted image training for tenant project.
    encryptionSpec GoogleCloudAiplatformV1EncryptionSpec
    Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.
    labels {[key: string]: string}
    The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
    location string
    project string
    display_name str
    The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    nas_job_spec GoogleCloudAiplatformV1NasJobSpecArgs
    The specification of a NasJob.
    enable_restricted_image_training bool
    Optional. Enable a separation of Custom model training and restricted image training for tenant project.
    encryption_spec GoogleCloudAiplatformV1EncryptionSpecArgs
    Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.
    labels Mapping[str, str]
    The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
    location str
    project str
    displayName String
    The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    nasJobSpec Property Map
    The specification of a NasJob.
    enableRestrictedImageTraining Boolean
    Optional. Enable a separation of Custom model training and restricted image training for tenant project.
    encryptionSpec Property Map
    Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.
    labels Map<String>
    The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
    location String
    project String

    Outputs

    All input properties are implicitly available as output properties. Additionally, the NasJob resource produces the following output properties:

    CreateTime string
    Time when the NasJob was created.
    EndTime string
    Time when the NasJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.
    Error Pulumi.GoogleNative.Aiplatform.V1.Outputs.GoogleRpcStatusResponse
    Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    Resource name of the NasJob.
    NasJobOutput Pulumi.GoogleNative.Aiplatform.V1.Outputs.GoogleCloudAiplatformV1NasJobOutputResponse
    Output of the NasJob.
    StartTime string
    Time when the NasJob for the first time entered the JOB_STATE_RUNNING state.
    State string
    The detailed state of the job.
    UpdateTime string
    Time when the NasJob was most recently updated.
    CreateTime string
    Time when the NasJob was created.
    EndTime string
    Time when the NasJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.
    Error GoogleRpcStatusResponse
    Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    Resource name of the NasJob.
    NasJobOutput GoogleCloudAiplatformV1NasJobOutputResponse
    Output of the NasJob.
    StartTime string
    Time when the NasJob for the first time entered the JOB_STATE_RUNNING state.
    State string
    The detailed state of the job.
    UpdateTime string
    Time when the NasJob was most recently updated.
    createTime String
    Time when the NasJob was created.
    endTime String
    Time when the NasJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.
    error GoogleRpcStatusResponse
    Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    Resource name of the NasJob.
    nasJobOutput GoogleCloudAiplatformV1NasJobOutputResponse
    Output of the NasJob.
    startTime String
    Time when the NasJob for the first time entered the JOB_STATE_RUNNING state.
    state String
    The detailed state of the job.
    updateTime String
    Time when the NasJob was most recently updated.
    createTime string
    Time when the NasJob was created.
    endTime string
    Time when the NasJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.
    error GoogleRpcStatusResponse
    Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    id string
    The provider-assigned unique ID for this managed resource.
    name string
    Resource name of the NasJob.
    nasJobOutput GoogleCloudAiplatformV1NasJobOutputResponse
    Output of the NasJob.
    startTime string
    Time when the NasJob for the first time entered the JOB_STATE_RUNNING state.
    state string
    The detailed state of the job.
    updateTime string
    Time when the NasJob was most recently updated.
    create_time str
    Time when the NasJob was created.
    end_time str
    Time when the NasJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.
    error GoogleRpcStatusResponse
    Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    id str
    The provider-assigned unique ID for this managed resource.
    name str
    Resource name of the NasJob.
    nas_job_output GoogleCloudAiplatformV1NasJobOutputResponse
    Output of the NasJob.
    start_time str
    Time when the NasJob for the first time entered the JOB_STATE_RUNNING state.
    state str
    The detailed state of the job.
    update_time str
    Time when the NasJob was most recently updated.
    createTime String
    Time when the NasJob was created.
    endTime String
    Time when the NasJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.
    error Property Map
    Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    Resource name of the NasJob.
    nasJobOutput Property Map
    Output of the NasJob.
    startTime String
    Time when the NasJob for the first time entered the JOB_STATE_RUNNING state.
    state String
    The detailed state of the job.
    updateTime String
    Time when the NasJob was most recently updated.

    Supporting Types

    GoogleCloudAiplatformV1ContainerSpec, GoogleCloudAiplatformV1ContainerSpecArgs

    ImageUri string
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    Args List<string>
    The arguments to be passed when starting the container.
    Command List<string>
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    Env List<Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EnvVar>
    Environment variables to be passed to the container. Maximum limit is 100.
    ImageUri string
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    Args []string
    The arguments to be passed when starting the container.
    Command []string
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    Env []GoogleCloudAiplatformV1EnvVar
    Environment variables to be passed to the container. Maximum limit is 100.
    imageUri String
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    args List<String>
    The arguments to be passed when starting the container.
    command List<String>
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    env List<GoogleCloudAiplatformV1EnvVar>
    Environment variables to be passed to the container. Maximum limit is 100.
    imageUri string
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    args string[]
    The arguments to be passed when starting the container.
    command string[]
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    env GoogleCloudAiplatformV1EnvVar[]
    Environment variables to be passed to the container. Maximum limit is 100.
    image_uri str
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    args Sequence[str]
    The arguments to be passed when starting the container.
    command Sequence[str]
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    env Sequence[GoogleCloudAiplatformV1EnvVar]
    Environment variables to be passed to the container. Maximum limit is 100.
    imageUri String
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    args List<String>
    The arguments to be passed when starting the container.
    command List<String>
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    env List<Property Map>
    Environment variables to be passed to the container. Maximum limit is 100.

    GoogleCloudAiplatformV1ContainerSpecResponse, GoogleCloudAiplatformV1ContainerSpecResponseArgs

    Args List<string>
    The arguments to be passed when starting the container.
    Command List<string>
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    Env List<Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EnvVarResponse>
    Environment variables to be passed to the container. Maximum limit is 100.
    ImageUri string
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    Args []string
    The arguments to be passed when starting the container.
    Command []string
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    Env []GoogleCloudAiplatformV1EnvVarResponse
    Environment variables to be passed to the container. Maximum limit is 100.
    ImageUri string
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    args List<String>
    The arguments to be passed when starting the container.
    command List<String>
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    env List<GoogleCloudAiplatformV1EnvVarResponse>
    Environment variables to be passed to the container. Maximum limit is 100.
    imageUri String
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    args string[]
    The arguments to be passed when starting the container.
    command string[]
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    env GoogleCloudAiplatformV1EnvVarResponse[]
    Environment variables to be passed to the container. Maximum limit is 100.
    imageUri string
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    args Sequence[str]
    The arguments to be passed when starting the container.
    command Sequence[str]
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    env Sequence[GoogleCloudAiplatformV1EnvVarResponse]
    Environment variables to be passed to the container. Maximum limit is 100.
    image_uri str
    The URI of a container image in the Container Registry that is to be run on each worker replica.
    args List<String>
    The arguments to be passed when starting the container.
    command List<String>
    The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
    env List<Property Map>
    Environment variables to be passed to the container. Maximum limit is 100.
    imageUri String
    The URI of a container image in the Container Registry that is to be run on each worker replica.

    GoogleCloudAiplatformV1CustomJobSpec, GoogleCloudAiplatformV1CustomJobSpecArgs

    WorkerPoolSpecs List<Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1WorkerPoolSpec>
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    BaseOutputDirectory Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1GcsDestination
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    EnableDashboardAccess bool
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    EnableWebAccess bool
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    Experiment string
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    ExperimentRun string
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    Network string
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    ProtectedArtifactLocationId string
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    ReservedIpRanges List<string>
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    Scheduling Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1Scheduling
    Scheduling options for a CustomJob.
    ServiceAccount string
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    Tensorboard string
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    WorkerPoolSpecs []GoogleCloudAiplatformV1WorkerPoolSpec
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    BaseOutputDirectory GoogleCloudAiplatformV1GcsDestination
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    EnableDashboardAccess bool
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    EnableWebAccess bool
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    Experiment string
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    ExperimentRun string
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    Network string
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    ProtectedArtifactLocationId string
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    ReservedIpRanges []string
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    Scheduling GoogleCloudAiplatformV1Scheduling
    Scheduling options for a CustomJob.
    ServiceAccount string
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    Tensorboard string
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    workerPoolSpecs List<GoogleCloudAiplatformV1WorkerPoolSpec>
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    baseOutputDirectory GoogleCloudAiplatformV1GcsDestination
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    enableDashboardAccess Boolean
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    enableWebAccess Boolean
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    experiment String
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    experimentRun String
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    network String
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    protectedArtifactLocationId String
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    reservedIpRanges List<String>
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    scheduling GoogleCloudAiplatformV1Scheduling
    Scheduling options for a CustomJob.
    serviceAccount String
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    tensorboard String
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    workerPoolSpecs GoogleCloudAiplatformV1WorkerPoolSpec[]
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    baseOutputDirectory GoogleCloudAiplatformV1GcsDestination
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    enableDashboardAccess boolean
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    enableWebAccess boolean
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    experiment string
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    experimentRun string
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    network string
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    protectedArtifactLocationId string
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    reservedIpRanges string[]
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    scheduling GoogleCloudAiplatformV1Scheduling
    Scheduling options for a CustomJob.
    serviceAccount string
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    tensorboard string
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    worker_pool_specs Sequence[GoogleCloudAiplatformV1WorkerPoolSpec]
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    base_output_directory GoogleCloudAiplatformV1GcsDestination
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    enable_dashboard_access bool
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    enable_web_access bool
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    experiment str
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    experiment_run str
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    network str
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    protected_artifact_location_id str
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    reserved_ip_ranges Sequence[str]
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    scheduling GoogleCloudAiplatformV1Scheduling
    Scheduling options for a CustomJob.
    service_account str
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    tensorboard str
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    workerPoolSpecs List<Property Map>
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    baseOutputDirectory Property Map
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    enableDashboardAccess Boolean
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    enableWebAccess Boolean
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    experiment String
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    experimentRun String
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    network String
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    protectedArtifactLocationId String
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    reservedIpRanges List<String>
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    scheduling Property Map
    Scheduling options for a CustomJob.
    serviceAccount String
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    tensorboard String
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}

    GoogleCloudAiplatformV1CustomJobSpecResponse, GoogleCloudAiplatformV1CustomJobSpecResponseArgs

    BaseOutputDirectory Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1GcsDestinationResponse
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    EnableDashboardAccess bool
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    EnableWebAccess bool
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    Experiment string
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    ExperimentRun string
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    Network string
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    ProtectedArtifactLocationId string
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    ReservedIpRanges List<string>
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    Scheduling Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1SchedulingResponse
    Scheduling options for a CustomJob.
    ServiceAccount string
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    Tensorboard string
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    WorkerPoolSpecs List<Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1WorkerPoolSpecResponse>
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    BaseOutputDirectory GoogleCloudAiplatformV1GcsDestinationResponse
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    EnableDashboardAccess bool
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    EnableWebAccess bool
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    Experiment string
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    ExperimentRun string
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    Network string
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    ProtectedArtifactLocationId string
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    ReservedIpRanges []string
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    Scheduling GoogleCloudAiplatformV1SchedulingResponse
    Scheduling options for a CustomJob.
    ServiceAccount string
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    Tensorboard string
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    WorkerPoolSpecs []GoogleCloudAiplatformV1WorkerPoolSpecResponse
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    baseOutputDirectory GoogleCloudAiplatformV1GcsDestinationResponse
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    enableDashboardAccess Boolean
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    enableWebAccess Boolean
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    experiment String
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    experimentRun String
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    network String
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    protectedArtifactLocationId String
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    reservedIpRanges List<String>
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    scheduling GoogleCloudAiplatformV1SchedulingResponse
    Scheduling options for a CustomJob.
    serviceAccount String
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    tensorboard String
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    workerPoolSpecs List<GoogleCloudAiplatformV1WorkerPoolSpecResponse>
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    baseOutputDirectory GoogleCloudAiplatformV1GcsDestinationResponse
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    enableDashboardAccess boolean
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    enableWebAccess boolean
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    experiment string
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    experimentRun string
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    network string
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    protectedArtifactLocationId string
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    reservedIpRanges string[]
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    scheduling GoogleCloudAiplatformV1SchedulingResponse
    Scheduling options for a CustomJob.
    serviceAccount string
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    tensorboard string
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    workerPoolSpecs GoogleCloudAiplatformV1WorkerPoolSpecResponse[]
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    base_output_directory GoogleCloudAiplatformV1GcsDestinationResponse
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    enable_dashboard_access bool
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    enable_web_access bool
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    experiment str
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    experiment_run str
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    network str
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    protected_artifact_location_id str
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    reserved_ip_ranges Sequence[str]
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    scheduling GoogleCloudAiplatformV1SchedulingResponse
    Scheduling options for a CustomJob.
    service_account str
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    tensorboard str
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    worker_pool_specs Sequence[GoogleCloudAiplatformV1WorkerPoolSpecResponse]
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
    baseOutputDirectory Property Map
    The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = /model/ * AIP_CHECKPOINT_DIR = /checkpoints/ * AIP_TENSORBOARD_LOG_DIR = /logs/ For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = //model/ * AIP_CHECKPOINT_DIR = //checkpoints/ * AIP_TENSORBOARD_LOG_DIR = //logs/
    enableDashboardAccess Boolean
    Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    enableWebAccess Boolean
    Optional. Whether you want Vertex AI to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
    experiment String
    Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
    experimentRun String
    Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
    network String
    Optional. The full name of the Compute Engine network to which the Job should be peered. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the job is not peered with any network.
    protectedArtifactLocationId String
    The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
    reservedIpRanges List<String>
    Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
    scheduling Property Map
    Scheduling options for a CustomJob.
    serviceAccount String
    Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
    tensorboard String
    Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
    workerPoolSpecs List<Property Map>
    The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.

    GoogleCloudAiplatformV1DiskSpec, GoogleCloudAiplatformV1DiskSpecArgs

    BootDiskSizeGb int
    Size in GB of the boot disk (default is 100GB).
    BootDiskType string
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    BootDiskSizeGb int
    Size in GB of the boot disk (default is 100GB).
    BootDiskType string
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    bootDiskSizeGb Integer
    Size in GB of the boot disk (default is 100GB).
    bootDiskType String
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    bootDiskSizeGb number
    Size in GB of the boot disk (default is 100GB).
    bootDiskType string
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    boot_disk_size_gb int
    Size in GB of the boot disk (default is 100GB).
    boot_disk_type str
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    bootDiskSizeGb Number
    Size in GB of the boot disk (default is 100GB).
    bootDiskType String
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

    GoogleCloudAiplatformV1DiskSpecResponse, GoogleCloudAiplatformV1DiskSpecResponseArgs

    BootDiskSizeGb int
    Size in GB of the boot disk (default is 100GB).
    BootDiskType string
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    BootDiskSizeGb int
    Size in GB of the boot disk (default is 100GB).
    BootDiskType string
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    bootDiskSizeGb Integer
    Size in GB of the boot disk (default is 100GB).
    bootDiskType String
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    bootDiskSizeGb number
    Size in GB of the boot disk (default is 100GB).
    bootDiskType string
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    boot_disk_size_gb int
    Size in GB of the boot disk (default is 100GB).
    boot_disk_type str
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
    bootDiskSizeGb Number
    Size in GB of the boot disk (default is 100GB).
    bootDiskType String
    Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

    GoogleCloudAiplatformV1EncryptionSpec, GoogleCloudAiplatformV1EncryptionSpecArgs

    KmsKeyName string
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    KmsKeyName string
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kmsKeyName String
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kmsKeyName string
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kms_key_name str
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kmsKeyName String
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

    GoogleCloudAiplatformV1EncryptionSpecResponse, GoogleCloudAiplatformV1EncryptionSpecResponseArgs

    KmsKeyName string
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    KmsKeyName string
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kmsKeyName String
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kmsKeyName string
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kms_key_name str
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kmsKeyName String
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

    GoogleCloudAiplatformV1EnvVar, GoogleCloudAiplatformV1EnvVarArgs

    Name string
    Name of the environment variable. Must be a valid C identifier.
    Value string
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    Name string
    Name of the environment variable. Must be a valid C identifier.
    Value string
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    name String
    Name of the environment variable. Must be a valid C identifier.
    value String
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    name string
    Name of the environment variable. Must be a valid C identifier.
    value string
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    name str
    Name of the environment variable. Must be a valid C identifier.
    value str
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    name String
    Name of the environment variable. Must be a valid C identifier.
    value String
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.

    GoogleCloudAiplatformV1EnvVarResponse, GoogleCloudAiplatformV1EnvVarResponseArgs

    Name string
    Name of the environment variable. Must be a valid C identifier.
    Value string
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    Name string
    Name of the environment variable. Must be a valid C identifier.
    Value string
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    name String
    Name of the environment variable. Must be a valid C identifier.
    value String
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    name string
    Name of the environment variable. Must be a valid C identifier.
    value string
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    name str
    Name of the environment variable. Must be a valid C identifier.
    value str
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
    name String
    Name of the environment variable. Must be a valid C identifier.
    value String
    Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.

    GoogleCloudAiplatformV1GcsDestination, GoogleCloudAiplatformV1GcsDestinationArgs

    OutputUriPrefix string
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    OutputUriPrefix string
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    outputUriPrefix String
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    outputUriPrefix string
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    output_uri_prefix str
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    outputUriPrefix String
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.

    GoogleCloudAiplatformV1GcsDestinationResponse, GoogleCloudAiplatformV1GcsDestinationResponseArgs

    OutputUriPrefix string
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    OutputUriPrefix string
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    outputUriPrefix String
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    outputUriPrefix string
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    output_uri_prefix str
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
    outputUriPrefix String
    Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.

    GoogleCloudAiplatformV1MachineSpec, GoogleCloudAiplatformV1MachineSpecArgs

    AcceleratorCount int
    The number of accelerators to attach to the machine.
    AcceleratorType Pulumi.GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1MachineSpecAcceleratorType
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    MachineType string
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    TpuTopology string
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    AcceleratorCount int
    The number of accelerators to attach to the machine.
    AcceleratorType GoogleCloudAiplatformV1MachineSpecAcceleratorType
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    MachineType string
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    TpuTopology string
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    acceleratorCount Integer
    The number of accelerators to attach to the machine.
    acceleratorType GoogleCloudAiplatformV1MachineSpecAcceleratorType
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    machineType String
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    tpuTopology String
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    acceleratorCount number
    The number of accelerators to attach to the machine.
    acceleratorType GoogleCloudAiplatformV1MachineSpecAcceleratorType
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    machineType string
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    tpuTopology string
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    accelerator_count int
    The number of accelerators to attach to the machine.
    accelerator_type GoogleCloudAiplatformV1MachineSpecAcceleratorType
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    machine_type str
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    tpu_topology str
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    acceleratorCount Number
    The number of accelerators to attach to the machine.
    acceleratorType "ACCELERATOR_TYPE_UNSPECIFIED" | "NVIDIA_TESLA_K80" | "NVIDIA_TESLA_P100" | "NVIDIA_TESLA_V100" | "NVIDIA_TESLA_P4" | "NVIDIA_TESLA_T4" | "NVIDIA_TESLA_A100" | "NVIDIA_A100_80GB" | "NVIDIA_L4" | "TPU_V2" | "TPU_V3" | "TPU_V4_POD"
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    machineType String
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    tpuTopology String
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

    GoogleCloudAiplatformV1MachineSpecAcceleratorType, GoogleCloudAiplatformV1MachineSpecAcceleratorTypeArgs

    AcceleratorTypeUnspecified
    ACCELERATOR_TYPE_UNSPECIFIEDUnspecified accelerator type, which means no accelerator.
    NvidiaTeslaK80
    NVIDIA_TESLA_K80Nvidia Tesla K80 GPU.
    NvidiaTeslaP100
    NVIDIA_TESLA_P100Nvidia Tesla P100 GPU.
    NvidiaTeslaV100
    NVIDIA_TESLA_V100Nvidia Tesla V100 GPU.
    NvidiaTeslaP4
    NVIDIA_TESLA_P4Nvidia Tesla P4 GPU.
    NvidiaTeslaT4
    NVIDIA_TESLA_T4Nvidia Tesla T4 GPU.
    NvidiaTeslaA100
    NVIDIA_TESLA_A100Nvidia Tesla A100 GPU.
    NvidiaA10080gb
    NVIDIA_A100_80GBNvidia A100 80GB GPU.
    NvidiaL4
    NVIDIA_L4Nvidia L4 GPU.
    TpuV2
    TPU_V2TPU v2.
    TpuV3
    TPU_V3TPU v3.
    TpuV4Pod
    TPU_V4_PODTPU v4.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeAcceleratorTypeUnspecified
    ACCELERATOR_TYPE_UNSPECIFIEDUnspecified accelerator type, which means no accelerator.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaK80
    NVIDIA_TESLA_K80Nvidia Tesla K80 GPU.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaP100
    NVIDIA_TESLA_P100Nvidia Tesla P100 GPU.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaV100
    NVIDIA_TESLA_V100Nvidia Tesla V100 GPU.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaP4
    NVIDIA_TESLA_P4Nvidia Tesla P4 GPU.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaT4
    NVIDIA_TESLA_T4Nvidia Tesla T4 GPU.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaA100
    NVIDIA_TESLA_A100Nvidia Tesla A100 GPU.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaA10080gb
    NVIDIA_A100_80GBNvidia A100 80GB GPU.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaL4
    NVIDIA_L4Nvidia L4 GPU.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeTpuV2
    TPU_V2TPU v2.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeTpuV3
    TPU_V3TPU v3.
    GoogleCloudAiplatformV1MachineSpecAcceleratorTypeTpuV4Pod
    TPU_V4_PODTPU v4.
    AcceleratorTypeUnspecified
    ACCELERATOR_TYPE_UNSPECIFIEDUnspecified accelerator type, which means no accelerator.
    NvidiaTeslaK80
    NVIDIA_TESLA_K80Nvidia Tesla K80 GPU.
    NvidiaTeslaP100
    NVIDIA_TESLA_P100Nvidia Tesla P100 GPU.
    NvidiaTeslaV100
    NVIDIA_TESLA_V100Nvidia Tesla V100 GPU.
    NvidiaTeslaP4
    NVIDIA_TESLA_P4Nvidia Tesla P4 GPU.
    NvidiaTeslaT4
    NVIDIA_TESLA_T4Nvidia Tesla T4 GPU.
    NvidiaTeslaA100
    NVIDIA_TESLA_A100Nvidia Tesla A100 GPU.
    NvidiaA10080gb
    NVIDIA_A100_80GBNvidia A100 80GB GPU.
    NvidiaL4
    NVIDIA_L4Nvidia L4 GPU.
    TpuV2
    TPU_V2TPU v2.
    TpuV3
    TPU_V3TPU v3.
    TpuV4Pod
    TPU_V4_PODTPU v4.
    AcceleratorTypeUnspecified
    ACCELERATOR_TYPE_UNSPECIFIEDUnspecified accelerator type, which means no accelerator.
    NvidiaTeslaK80
    NVIDIA_TESLA_K80Nvidia Tesla K80 GPU.
    NvidiaTeslaP100
    NVIDIA_TESLA_P100Nvidia Tesla P100 GPU.
    NvidiaTeslaV100
    NVIDIA_TESLA_V100Nvidia Tesla V100 GPU.
    NvidiaTeslaP4
    NVIDIA_TESLA_P4Nvidia Tesla P4 GPU.
    NvidiaTeslaT4
    NVIDIA_TESLA_T4Nvidia Tesla T4 GPU.
    NvidiaTeslaA100
    NVIDIA_TESLA_A100Nvidia Tesla A100 GPU.
    NvidiaA10080gb
    NVIDIA_A100_80GBNvidia A100 80GB GPU.
    NvidiaL4
    NVIDIA_L4Nvidia L4 GPU.
    TpuV2
    TPU_V2TPU v2.
    TpuV3
    TPU_V3TPU v3.
    TpuV4Pod
    TPU_V4_PODTPU v4.
    ACCELERATOR_TYPE_UNSPECIFIED
    ACCELERATOR_TYPE_UNSPECIFIEDUnspecified accelerator type, which means no accelerator.
    NVIDIA_TESLA_K80
    NVIDIA_TESLA_K80Nvidia Tesla K80 GPU.
    NVIDIA_TESLA_P100
    NVIDIA_TESLA_P100Nvidia Tesla P100 GPU.
    NVIDIA_TESLA_V100
    NVIDIA_TESLA_V100Nvidia Tesla V100 GPU.
    NVIDIA_TESLA_P4
    NVIDIA_TESLA_P4Nvidia Tesla P4 GPU.
    NVIDIA_TESLA_T4
    NVIDIA_TESLA_T4Nvidia Tesla T4 GPU.
    NVIDIA_TESLA_A100
    NVIDIA_TESLA_A100Nvidia Tesla A100 GPU.
    NVIDIA_A10080GB
    NVIDIA_A100_80GBNvidia A100 80GB GPU.
    NVIDIA_L4
    NVIDIA_L4Nvidia L4 GPU.
    TPU_V2
    TPU_V2TPU v2.
    TPU_V3
    TPU_V3TPU v3.
    TPU_V4_POD
    TPU_V4_PODTPU v4.
    "ACCELERATOR_TYPE_UNSPECIFIED"
    ACCELERATOR_TYPE_UNSPECIFIEDUnspecified accelerator type, which means no accelerator.
    "NVIDIA_TESLA_K80"
    NVIDIA_TESLA_K80Nvidia Tesla K80 GPU.
    "NVIDIA_TESLA_P100"
    NVIDIA_TESLA_P100Nvidia Tesla P100 GPU.
    "NVIDIA_TESLA_V100"
    NVIDIA_TESLA_V100Nvidia Tesla V100 GPU.
    "NVIDIA_TESLA_P4"
    NVIDIA_TESLA_P4Nvidia Tesla P4 GPU.
    "NVIDIA_TESLA_T4"
    NVIDIA_TESLA_T4Nvidia Tesla T4 GPU.
    "NVIDIA_TESLA_A100"
    NVIDIA_TESLA_A100Nvidia Tesla A100 GPU.
    "NVIDIA_A100_80GB"
    NVIDIA_A100_80GBNvidia A100 80GB GPU.
    "NVIDIA_L4"
    NVIDIA_L4Nvidia L4 GPU.
    "TPU_V2"
    TPU_V2TPU v2.
    "TPU_V3"
    TPU_V3TPU v3.
    "TPU_V4_POD"
    TPU_V4_PODTPU v4.

    GoogleCloudAiplatformV1MachineSpecResponse, GoogleCloudAiplatformV1MachineSpecResponseArgs

    AcceleratorCount int
    The number of accelerators to attach to the machine.
    AcceleratorType string
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    MachineType string
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    TpuTopology string
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    AcceleratorCount int
    The number of accelerators to attach to the machine.
    AcceleratorType string
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    MachineType string
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    TpuTopology string
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    acceleratorCount Integer
    The number of accelerators to attach to the machine.
    acceleratorType String
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    machineType String
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    tpuTopology String
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    acceleratorCount number
    The number of accelerators to attach to the machine.
    acceleratorType string
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    machineType string
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    tpuTopology string
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    accelerator_count int
    The number of accelerators to attach to the machine.
    accelerator_type str
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    machine_type str
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    tpu_topology str
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
    acceleratorCount Number
    The number of accelerators to attach to the machine.
    acceleratorType String
    Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
    machineType String
    Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
    tpuTopology String
    Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

    GoogleCloudAiplatformV1MeasurementMetricResponse, GoogleCloudAiplatformV1MeasurementMetricResponseArgs

    MetricId string
    The ID of the Metric. The Metric should be defined in StudySpec's Metrics.
    Value double
    The value for this metric.
    MetricId string
    The ID of the Metric. The Metric should be defined in StudySpec's Metrics.
    Value float64
    The value for this metric.
    metricId String
    The ID of the Metric. The Metric should be defined in StudySpec's Metrics.
    value Double
    The value for this metric.
    metricId string
    The ID of the Metric. The Metric should be defined in StudySpec's Metrics.
    value number
    The value for this metric.
    metric_id str
    The ID of the Metric. The Metric should be defined in StudySpec's Metrics.
    value float
    The value for this metric.
    metricId String
    The ID of the Metric. The Metric should be defined in StudySpec's Metrics.
    value Number
    The value for this metric.

    GoogleCloudAiplatformV1MeasurementResponse, GoogleCloudAiplatformV1MeasurementResponseArgs

    ElapsedDuration string
    Time that the Trial has been running at the point of this Measurement.
    Metrics List<Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1MeasurementMetricResponse>
    A list of metrics got by evaluating the objective functions using suggested Parameter values.
    StepCount string
    The number of steps the machine learning model has been trained for. Must be non-negative.
    ElapsedDuration string
    Time that the Trial has been running at the point of this Measurement.
    Metrics []GoogleCloudAiplatformV1MeasurementMetricResponse
    A list of metrics got by evaluating the objective functions using suggested Parameter values.
    StepCount string
    The number of steps the machine learning model has been trained for. Must be non-negative.
    elapsedDuration String
    Time that the Trial has been running at the point of this Measurement.
    metrics List<GoogleCloudAiplatformV1MeasurementMetricResponse>
    A list of metrics got by evaluating the objective functions using suggested Parameter values.
    stepCount String
    The number of steps the machine learning model has been trained for. Must be non-negative.
    elapsedDuration string
    Time that the Trial has been running at the point of this Measurement.
    metrics GoogleCloudAiplatformV1MeasurementMetricResponse[]
    A list of metrics got by evaluating the objective functions using suggested Parameter values.
    stepCount string
    The number of steps the machine learning model has been trained for. Must be non-negative.
    elapsed_duration str
    Time that the Trial has been running at the point of this Measurement.
    metrics Sequence[GoogleCloudAiplatformV1MeasurementMetricResponse]
    A list of metrics got by evaluating the objective functions using suggested Parameter values.
    step_count str
    The number of steps the machine learning model has been trained for. Must be non-negative.
    elapsedDuration String
    Time that the Trial has been running at the point of this Measurement.
    metrics List<Property Map>
    A list of metrics got by evaluating the objective functions using suggested Parameter values.
    stepCount String
    The number of steps the machine learning model has been trained for. Must be non-negative.

    GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponse, GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseArgs

    SearchTrials []GoogleCloudAiplatformV1NasTrialResponse
    List of NasTrials that were started as part of search stage.
    TrainTrials []GoogleCloudAiplatformV1NasTrialResponse
    List of NasTrials that were started as part of train stage.
    searchTrials List<GoogleCloudAiplatformV1NasTrialResponse>
    List of NasTrials that were started as part of search stage.
    trainTrials List<GoogleCloudAiplatformV1NasTrialResponse>
    List of NasTrials that were started as part of train stage.
    searchTrials GoogleCloudAiplatformV1NasTrialResponse[]
    List of NasTrials that were started as part of search stage.
    trainTrials GoogleCloudAiplatformV1NasTrialResponse[]
    List of NasTrials that were started as part of train stage.
    search_trials Sequence[GoogleCloudAiplatformV1NasTrialResponse]
    List of NasTrials that were started as part of search stage.
    train_trials Sequence[GoogleCloudAiplatformV1NasTrialResponse]
    List of NasTrials that were started as part of train stage.
    searchTrials List<Property Map>
    List of NasTrials that were started as part of search stage.
    trainTrials List<Property Map>
    List of NasTrials that were started as part of train stage.

    GoogleCloudAiplatformV1NasJobOutputResponse, GoogleCloudAiplatformV1NasJobOutputResponseArgs

    MultiTrialJobOutput GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponse
    The output of this multi-trial Neural Architecture Search (NAS) job.
    multiTrialJobOutput GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponse
    The output of this multi-trial Neural Architecture Search (NAS) job.
    multiTrialJobOutput GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponse
    The output of this multi-trial Neural Architecture Search (NAS) job.
    multi_trial_job_output GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponse
    The output of this multi-trial Neural Architecture Search (NAS) job.
    multiTrialJobOutput Property Map
    The output of this multi-trial Neural Architecture Search (NAS) job.

    GoogleCloudAiplatformV1NasJobSpec, GoogleCloudAiplatformV1NasJobSpecArgs

    MultiTrialAlgorithmSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec
    The spec of multi-trial algorithms.
    ResumeNasJobId string
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    SearchSpaceSpec string
    It defines the search space for Neural Architecture Search (NAS).
    MultiTrialAlgorithmSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec
    The spec of multi-trial algorithms.
    ResumeNasJobId string
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    SearchSpaceSpec string
    It defines the search space for Neural Architecture Search (NAS).
    multiTrialAlgorithmSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec
    The spec of multi-trial algorithms.
    resumeNasJobId String
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    searchSpaceSpec String
    It defines the search space for Neural Architecture Search (NAS).
    multiTrialAlgorithmSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec
    The spec of multi-trial algorithms.
    resumeNasJobId string
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    searchSpaceSpec string
    It defines the search space for Neural Architecture Search (NAS).
    multi_trial_algorithm_spec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec
    The spec of multi-trial algorithms.
    resume_nas_job_id str
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    search_space_spec str
    It defines the search space for Neural Architecture Search (NAS).
    multiTrialAlgorithmSpec Property Map
    The spec of multi-trial algorithms.
    resumeNasJobId String
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    searchSpaceSpec String
    It defines the search space for Neural Architecture Search (NAS).

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs

    SearchTrialSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec
    Spec for search trials.
    Metric Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    MultiTrialAlgorithm Pulumi.GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    TrainTrialSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    SearchTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec
    Spec for search trials.
    Metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    MultiTrialAlgorithm GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    TrainTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    searchTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec
    Spec for search trials.
    metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    multiTrialAlgorithm GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    trainTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    searchTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec
    Spec for search trials.
    metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    multiTrialAlgorithm GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    trainTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    search_trial_spec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec
    Spec for search trials.
    metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    multi_trial_algorithm GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    train_trial_spec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    searchTrialSpec Property Map
    Spec for search trials.
    metric Property Map
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    multiTrialAlgorithm "MULTI_TRIAL_ALGORITHM_UNSPECIFIED" | "REINFORCEMENT_LEARNING" | "GRID_SEARCH"
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    trainTrialSpec Property Map
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs

    Goal Pulumi.GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal
    The optimization goal of the metric.
    MetricId string
    The ID of the metric. Must not contain whitespaces.
    Goal GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal
    The optimization goal of the metric.
    MetricId string
    The ID of the metric. Must not contain whitespaces.
    goal GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal
    The optimization goal of the metric.
    metricId String
    The ID of the metric. Must not contain whitespaces.
    goal GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal
    The optimization goal of the metric.
    metricId string
    The ID of the metric. Must not contain whitespaces.
    goal GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal
    The optimization goal of the metric.
    metric_id str
    The ID of the metric. Must not contain whitespaces.
    goal "GOAL_TYPE_UNSPECIFIED" | "MAXIMIZE" | "MINIMIZE"
    The optimization goal of the metric.
    metricId String
    The ID of the metric. Must not contain whitespaces.

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalArgs

    GoalTypeUnspecified
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    Maximize
    MAXIMIZEMaximize the goal metric.
    Minimize
    MINIMIZEMinimize the goal metric.
    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalGoalTypeUnspecified
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalMaximize
    MAXIMIZEMaximize the goal metric.
    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalMinimize
    MINIMIZEMinimize the goal metric.
    GoalTypeUnspecified
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    Maximize
    MAXIMIZEMaximize the goal metric.
    Minimize
    MINIMIZEMinimize the goal metric.
    GoalTypeUnspecified
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    Maximize
    MAXIMIZEMaximize the goal metric.
    Minimize
    MINIMIZEMinimize the goal metric.
    GOAL_TYPE_UNSPECIFIED
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    MAXIMIZE
    MAXIMIZEMaximize the goal metric.
    MINIMIZE
    MINIMIZEMinimize the goal metric.
    "GOAL_TYPE_UNSPECIFIED"
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    "MAXIMIZE"
    MAXIMIZEMaximize the goal metric.
    "MINIMIZE"
    MINIMIZEMinimize the goal metric.

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponse, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseArgs

    Goal string
    The optimization goal of the metric.
    MetricId string
    The ID of the metric. Must not contain whitespaces.
    Goal string
    The optimization goal of the metric.
    MetricId string
    The ID of the metric. Must not contain whitespaces.
    goal String
    The optimization goal of the metric.
    metricId String
    The ID of the metric. Must not contain whitespaces.
    goal string
    The optimization goal of the metric.
    metricId string
    The ID of the metric. Must not contain whitespaces.
    goal str
    The optimization goal of the metric.
    metric_id str
    The ID of the metric. Must not contain whitespaces.
    goal String
    The optimization goal of the metric.
    metricId String
    The ID of the metric. Must not contain whitespaces.

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmArgs

    MultiTrialAlgorithmUnspecified
    MULTI_TRIAL_ALGORITHM_UNSPECIFIEDDefaults to REINFORCEMENT_LEARNING.
    ReinforcementLearning
    REINFORCEMENT_LEARNINGThe Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).
    GridSearch
    GRID_SEARCHThe Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS).
    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmMultiTrialAlgorithmUnspecified
    MULTI_TRIAL_ALGORITHM_UNSPECIFIEDDefaults to REINFORCEMENT_LEARNING.
    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmReinforcementLearning
    REINFORCEMENT_LEARNINGThe Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).
    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmGridSearch
    GRID_SEARCHThe Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS).
    MultiTrialAlgorithmUnspecified
    MULTI_TRIAL_ALGORITHM_UNSPECIFIEDDefaults to REINFORCEMENT_LEARNING.
    ReinforcementLearning
    REINFORCEMENT_LEARNINGThe Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).
    GridSearch
    GRID_SEARCHThe Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS).
    MultiTrialAlgorithmUnspecified
    MULTI_TRIAL_ALGORITHM_UNSPECIFIEDDefaults to REINFORCEMENT_LEARNING.
    ReinforcementLearning
    REINFORCEMENT_LEARNINGThe Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).
    GridSearch
    GRID_SEARCHThe Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS).
    MULTI_TRIAL_ALGORITHM_UNSPECIFIED
    MULTI_TRIAL_ALGORITHM_UNSPECIFIEDDefaults to REINFORCEMENT_LEARNING.
    REINFORCEMENT_LEARNING
    REINFORCEMENT_LEARNINGThe Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).
    GRID_SEARCH
    GRID_SEARCHThe Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS).
    "MULTI_TRIAL_ALGORITHM_UNSPECIFIED"
    MULTI_TRIAL_ALGORITHM_UNSPECIFIEDDefaults to REINFORCEMENT_LEARNING.
    "REINFORCEMENT_LEARNING"
    REINFORCEMENT_LEARNINGThe Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).
    "GRID_SEARCH"
    GRID_SEARCHThe Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS).

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponse, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseArgs

    Metric Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponse
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    MultiTrialAlgorithm string
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    SearchTrialSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponse
    Spec for search trials.
    TrainTrialSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponse
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    Metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponse
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    MultiTrialAlgorithm string
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    SearchTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponse
    Spec for search trials.
    TrainTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponse
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponse
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    multiTrialAlgorithm String
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    searchTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponse
    Spec for search trials.
    trainTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponse
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponse
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    multiTrialAlgorithm string
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    searchTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponse
    Spec for search trials.
    trainTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponse
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponse
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    multi_trial_algorithm str
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    search_trial_spec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponse
    Spec for search trials.
    train_trial_spec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponse
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    metric Property Map
    Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.
    multiTrialAlgorithm String
    The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.
    searchTrialSpec Property Map
    Spec for search trials.
    trainTrialSpec Property Map
    Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs

    MaxParallelTrialCount int
    The maximum number of trials to run in parallel.
    MaxTrialCount int
    The maximum number of Neural Architecture Search (NAS) trials to run.
    SearchTrialJobSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1CustomJobSpec
    The spec of a search trial job. The same spec applies to all search trials.
    MaxFailedTrialCount int
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    MaxParallelTrialCount int
    The maximum number of trials to run in parallel.
    MaxTrialCount int
    The maximum number of Neural Architecture Search (NAS) trials to run.
    SearchTrialJobSpec GoogleCloudAiplatformV1CustomJobSpec
    The spec of a search trial job. The same spec applies to all search trials.
    MaxFailedTrialCount int
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    maxParallelTrialCount Integer
    The maximum number of trials to run in parallel.
    maxTrialCount Integer
    The maximum number of Neural Architecture Search (NAS) trials to run.
    searchTrialJobSpec GoogleCloudAiplatformV1CustomJobSpec
    The spec of a search trial job. The same spec applies to all search trials.
    maxFailedTrialCount Integer
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    maxParallelTrialCount number
    The maximum number of trials to run in parallel.
    maxTrialCount number
    The maximum number of Neural Architecture Search (NAS) trials to run.
    searchTrialJobSpec GoogleCloudAiplatformV1CustomJobSpec
    The spec of a search trial job. The same spec applies to all search trials.
    maxFailedTrialCount number
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    max_parallel_trial_count int
    The maximum number of trials to run in parallel.
    max_trial_count int
    The maximum number of Neural Architecture Search (NAS) trials to run.
    search_trial_job_spec GoogleCloudAiplatformV1CustomJobSpec
    The spec of a search trial job. The same spec applies to all search trials.
    max_failed_trial_count int
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    maxParallelTrialCount Number
    The maximum number of trials to run in parallel.
    maxTrialCount Number
    The maximum number of Neural Architecture Search (NAS) trials to run.
    searchTrialJobSpec Property Map
    The spec of a search trial job. The same spec applies to all search trials.
    maxFailedTrialCount Number
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponse, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseArgs

    MaxFailedTrialCount int
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    MaxParallelTrialCount int
    The maximum number of trials to run in parallel.
    MaxTrialCount int
    The maximum number of Neural Architecture Search (NAS) trials to run.
    SearchTrialJobSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a search trial job. The same spec applies to all search trials.
    MaxFailedTrialCount int
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    MaxParallelTrialCount int
    The maximum number of trials to run in parallel.
    MaxTrialCount int
    The maximum number of Neural Architecture Search (NAS) trials to run.
    SearchTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a search trial job. The same spec applies to all search trials.
    maxFailedTrialCount Integer
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    maxParallelTrialCount Integer
    The maximum number of trials to run in parallel.
    maxTrialCount Integer
    The maximum number of Neural Architecture Search (NAS) trials to run.
    searchTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a search trial job. The same spec applies to all search trials.
    maxFailedTrialCount number
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    maxParallelTrialCount number
    The maximum number of trials to run in parallel.
    maxTrialCount number
    The maximum number of Neural Architecture Search (NAS) trials to run.
    searchTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a search trial job. The same spec applies to all search trials.
    max_failed_trial_count int
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    max_parallel_trial_count int
    The maximum number of trials to run in parallel.
    max_trial_count int
    The maximum number of Neural Architecture Search (NAS) trials to run.
    search_trial_job_spec GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a search trial job. The same spec applies to all search trials.
    maxFailedTrialCount Number
    The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
    maxParallelTrialCount Number
    The maximum number of trials to run in parallel.
    maxTrialCount Number
    The maximum number of Neural Architecture Search (NAS) trials to run.
    searchTrialJobSpec Property Map
    The spec of a search trial job. The same spec applies to all search trials.

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs

    Frequency int
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    MaxParallelTrialCount int
    The maximum number of trials to run in parallel.
    TrainTrialJobSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1CustomJobSpec
    The spec of a train trial job. The same spec applies to all train trials.
    Frequency int
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    MaxParallelTrialCount int
    The maximum number of trials to run in parallel.
    TrainTrialJobSpec GoogleCloudAiplatformV1CustomJobSpec
    The spec of a train trial job. The same spec applies to all train trials.
    frequency Integer
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    maxParallelTrialCount Integer
    The maximum number of trials to run in parallel.
    trainTrialJobSpec GoogleCloudAiplatformV1CustomJobSpec
    The spec of a train trial job. The same spec applies to all train trials.
    frequency number
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    maxParallelTrialCount number
    The maximum number of trials to run in parallel.
    trainTrialJobSpec GoogleCloudAiplatformV1CustomJobSpec
    The spec of a train trial job. The same spec applies to all train trials.
    frequency int
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    max_parallel_trial_count int
    The maximum number of trials to run in parallel.
    train_trial_job_spec GoogleCloudAiplatformV1CustomJobSpec
    The spec of a train trial job. The same spec applies to all train trials.
    frequency Number
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    maxParallelTrialCount Number
    The maximum number of trials to run in parallel.
    trainTrialJobSpec Property Map
    The spec of a train trial job. The same spec applies to all train trials.

    GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponse, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseArgs

    Frequency int
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    MaxParallelTrialCount int
    The maximum number of trials to run in parallel.
    TrainTrialJobSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a train trial job. The same spec applies to all train trials.
    Frequency int
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    MaxParallelTrialCount int
    The maximum number of trials to run in parallel.
    TrainTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a train trial job. The same spec applies to all train trials.
    frequency Integer
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    maxParallelTrialCount Integer
    The maximum number of trials to run in parallel.
    trainTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a train trial job. The same spec applies to all train trials.
    frequency number
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    maxParallelTrialCount number
    The maximum number of trials to run in parallel.
    trainTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a train trial job. The same spec applies to all train trials.
    frequency int
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    max_parallel_trial_count int
    The maximum number of trials to run in parallel.
    train_trial_job_spec GoogleCloudAiplatformV1CustomJobSpecResponse
    The spec of a train trial job. The same spec applies to all train trials.
    frequency Number
    Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
    maxParallelTrialCount Number
    The maximum number of trials to run in parallel.
    trainTrialJobSpec Property Map
    The spec of a train trial job. The same spec applies to all train trials.

    GoogleCloudAiplatformV1NasJobSpecResponse, GoogleCloudAiplatformV1NasJobSpecResponseArgs

    MultiTrialAlgorithmSpec Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponse
    The spec of multi-trial algorithms.
    ResumeNasJobId string
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    SearchSpaceSpec string
    It defines the search space for Neural Architecture Search (NAS).
    MultiTrialAlgorithmSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponse
    The spec of multi-trial algorithms.
    ResumeNasJobId string
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    SearchSpaceSpec string
    It defines the search space for Neural Architecture Search (NAS).
    multiTrialAlgorithmSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponse
    The spec of multi-trial algorithms.
    resumeNasJobId String
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    searchSpaceSpec String
    It defines the search space for Neural Architecture Search (NAS).
    multiTrialAlgorithmSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponse
    The spec of multi-trial algorithms.
    resumeNasJobId string
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    searchSpaceSpec string
    It defines the search space for Neural Architecture Search (NAS).
    multi_trial_algorithm_spec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponse
    The spec of multi-trial algorithms.
    resume_nas_job_id str
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    search_space_spec str
    It defines the search space for Neural Architecture Search (NAS).
    multiTrialAlgorithmSpec Property Map
    The spec of multi-trial algorithms.
    resumeNasJobId String
    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
    searchSpaceSpec String
    It defines the search space for Neural Architecture Search (NAS).

    GoogleCloudAiplatformV1NasTrialResponse, GoogleCloudAiplatformV1NasTrialResponseArgs

    EndTime string
    Time when the NasTrial's status changed to SUCCEEDED or INFEASIBLE.
    FinalMeasurement Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1MeasurementResponse
    The final measurement containing the objective value.
    StartTime string
    Time when the NasTrial was started.
    State string
    The detailed state of the NasTrial.
    EndTime string
    Time when the NasTrial's status changed to SUCCEEDED or INFEASIBLE.
    FinalMeasurement GoogleCloudAiplatformV1MeasurementResponse
    The final measurement containing the objective value.
    StartTime string
    Time when the NasTrial was started.
    State string
    The detailed state of the NasTrial.
    endTime String
    Time when the NasTrial's status changed to SUCCEEDED or INFEASIBLE.
    finalMeasurement GoogleCloudAiplatformV1MeasurementResponse
    The final measurement containing the objective value.
    startTime String
    Time when the NasTrial was started.
    state String
    The detailed state of the NasTrial.
    endTime string
    Time when the NasTrial's status changed to SUCCEEDED or INFEASIBLE.
    finalMeasurement GoogleCloudAiplatformV1MeasurementResponse
    The final measurement containing the objective value.
    startTime string
    Time when the NasTrial was started.
    state string
    The detailed state of the NasTrial.
    end_time str
    Time when the NasTrial's status changed to SUCCEEDED or INFEASIBLE.
    final_measurement GoogleCloudAiplatformV1MeasurementResponse
    The final measurement containing the objective value.
    start_time str
    Time when the NasTrial was started.
    state str
    The detailed state of the NasTrial.
    endTime String
    Time when the NasTrial's status changed to SUCCEEDED or INFEASIBLE.
    finalMeasurement Property Map
    The final measurement containing the objective value.
    startTime String
    Time when the NasTrial was started.
    state String
    The detailed state of the NasTrial.

    GoogleCloudAiplatformV1NfsMount, GoogleCloudAiplatformV1NfsMountArgs

    MountPoint string
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    Path string
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    Server string
    IP address of the NFS server.
    MountPoint string
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    Path string
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    Server string
    IP address of the NFS server.
    mountPoint String
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    path String
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    server String
    IP address of the NFS server.
    mountPoint string
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    path string
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    server string
    IP address of the NFS server.
    mount_point str
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    path str
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    server str
    IP address of the NFS server.
    mountPoint String
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    path String
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    server String
    IP address of the NFS server.

    GoogleCloudAiplatformV1NfsMountResponse, GoogleCloudAiplatformV1NfsMountResponseArgs

    MountPoint string
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    Path string
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    Server string
    IP address of the NFS server.
    MountPoint string
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    Path string
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    Server string
    IP address of the NFS server.
    mountPoint String
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    path String
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    server String
    IP address of the NFS server.
    mountPoint string
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    path string
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    server string
    IP address of the NFS server.
    mount_point str
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    path str
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    server str
    IP address of the NFS server.
    mountPoint String
    Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
    path String
    Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of server:path
    server String
    IP address of the NFS server.

    GoogleCloudAiplatformV1PythonPackageSpec, GoogleCloudAiplatformV1PythonPackageSpecArgs

    ExecutorImageUri string
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    PackageUris List<string>
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    PythonModule string
    The Python module name to run after installing the packages.
    Args List<string>
    Command line arguments to be passed to the Python task.
    Env List<Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EnvVar>
    Environment variables to be passed to the python module. Maximum limit is 100.
    ExecutorImageUri string
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    PackageUris []string
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    PythonModule string
    The Python module name to run after installing the packages.
    Args []string
    Command line arguments to be passed to the Python task.
    Env []GoogleCloudAiplatformV1EnvVar
    Environment variables to be passed to the python module. Maximum limit is 100.
    executorImageUri String
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    packageUris List<String>
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    pythonModule String
    The Python module name to run after installing the packages.
    args List<String>
    Command line arguments to be passed to the Python task.
    env List<GoogleCloudAiplatformV1EnvVar>
    Environment variables to be passed to the python module. Maximum limit is 100.
    executorImageUri string
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    packageUris string[]
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    pythonModule string
    The Python module name to run after installing the packages.
    args string[]
    Command line arguments to be passed to the Python task.
    env GoogleCloudAiplatformV1EnvVar[]
    Environment variables to be passed to the python module. Maximum limit is 100.
    executor_image_uri str
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    package_uris Sequence[str]
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    python_module str
    The Python module name to run after installing the packages.
    args Sequence[str]
    Command line arguments to be passed to the Python task.
    env Sequence[GoogleCloudAiplatformV1EnvVar]
    Environment variables to be passed to the python module. Maximum limit is 100.
    executorImageUri String
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    packageUris List<String>
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    pythonModule String
    The Python module name to run after installing the packages.
    args List<String>
    Command line arguments to be passed to the Python task.
    env List<Property Map>
    Environment variables to be passed to the python module. Maximum limit is 100.

    GoogleCloudAiplatformV1PythonPackageSpecResponse, GoogleCloudAiplatformV1PythonPackageSpecResponseArgs

    Args List<string>
    Command line arguments to be passed to the Python task.
    Env List<Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EnvVarResponse>
    Environment variables to be passed to the python module. Maximum limit is 100.
    ExecutorImageUri string
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    PackageUris List<string>
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    PythonModule string
    The Python module name to run after installing the packages.
    Args []string
    Command line arguments to be passed to the Python task.
    Env []GoogleCloudAiplatformV1EnvVarResponse
    Environment variables to be passed to the python module. Maximum limit is 100.
    ExecutorImageUri string
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    PackageUris []string
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    PythonModule string
    The Python module name to run after installing the packages.
    args List<String>
    Command line arguments to be passed to the Python task.
    env List<GoogleCloudAiplatformV1EnvVarResponse>
    Environment variables to be passed to the python module. Maximum limit is 100.
    executorImageUri String
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    packageUris List<String>
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    pythonModule String
    The Python module name to run after installing the packages.
    args string[]
    Command line arguments to be passed to the Python task.
    env GoogleCloudAiplatformV1EnvVarResponse[]
    Environment variables to be passed to the python module. Maximum limit is 100.
    executorImageUri string
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    packageUris string[]
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    pythonModule string
    The Python module name to run after installing the packages.
    args Sequence[str]
    Command line arguments to be passed to the Python task.
    env Sequence[GoogleCloudAiplatformV1EnvVarResponse]
    Environment variables to be passed to the python module. Maximum limit is 100.
    executor_image_uri str
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    package_uris Sequence[str]
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    python_module str
    The Python module name to run after installing the packages.
    args List<String>
    Command line arguments to be passed to the Python task.
    env List<Property Map>
    Environment variables to be passed to the python module. Maximum limit is 100.
    executorImageUri String
    The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of pre-built containers for training. You must use an image from this list.
    packageUris List<String>
    The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
    pythonModule String
    The Python module name to run after installing the packages.

    GoogleCloudAiplatformV1Scheduling, GoogleCloudAiplatformV1SchedulingArgs

    DisableRetries bool
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    RestartJobOnWorkerRestart bool
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    Timeout string
    The maximum job running time. The default is 7 days.
    DisableRetries bool
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    RestartJobOnWorkerRestart bool
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    Timeout string
    The maximum job running time. The default is 7 days.
    disableRetries Boolean
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    restartJobOnWorkerRestart Boolean
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    timeout String
    The maximum job running time. The default is 7 days.
    disableRetries boolean
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    restartJobOnWorkerRestart boolean
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    timeout string
    The maximum job running time. The default is 7 days.
    disable_retries bool
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    restart_job_on_worker_restart bool
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    timeout str
    The maximum job running time. The default is 7 days.
    disableRetries Boolean
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    restartJobOnWorkerRestart Boolean
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    timeout String
    The maximum job running time. The default is 7 days.

    GoogleCloudAiplatformV1SchedulingResponse, GoogleCloudAiplatformV1SchedulingResponseArgs

    DisableRetries bool
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    RestartJobOnWorkerRestart bool
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    Timeout string
    The maximum job running time. The default is 7 days.
    DisableRetries bool
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    RestartJobOnWorkerRestart bool
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    Timeout string
    The maximum job running time. The default is 7 days.
    disableRetries Boolean
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    restartJobOnWorkerRestart Boolean
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    timeout String
    The maximum job running time. The default is 7 days.
    disableRetries boolean
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    restartJobOnWorkerRestart boolean
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    timeout string
    The maximum job running time. The default is 7 days.
    disable_retries bool
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    restart_job_on_worker_restart bool
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    timeout str
    The maximum job running time. The default is 7 days.
    disableRetries Boolean
    Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides Scheduling.restart_job_on_worker_restart to false.
    restartJobOnWorkerRestart Boolean
    Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
    timeout String
    The maximum job running time. The default is 7 days.

    GoogleCloudAiplatformV1WorkerPoolSpec, GoogleCloudAiplatformV1WorkerPoolSpecArgs

    ContainerSpec GoogleCloudAiplatformV1ContainerSpec
    The custom container task.
    DiskSpec GoogleCloudAiplatformV1DiskSpec
    Disk spec.
    MachineSpec GoogleCloudAiplatformV1MachineSpec
    Optional. Immutable. The specification of a single machine.
    NfsMounts []GoogleCloudAiplatformV1NfsMount
    Optional. List of NFS mount spec.
    PythonPackageSpec GoogleCloudAiplatformV1PythonPackageSpec
    The Python packaged task.
    ReplicaCount string
    Optional. The number of worker replicas to use for this worker pool.
    containerSpec GoogleCloudAiplatformV1ContainerSpec
    The custom container task.
    diskSpec GoogleCloudAiplatformV1DiskSpec
    Disk spec.
    machineSpec GoogleCloudAiplatformV1MachineSpec
    Optional. Immutable. The specification of a single machine.
    nfsMounts List<GoogleCloudAiplatformV1NfsMount>
    Optional. List of NFS mount spec.
    pythonPackageSpec GoogleCloudAiplatformV1PythonPackageSpec
    The Python packaged task.
    replicaCount String
    Optional. The number of worker replicas to use for this worker pool.
    containerSpec GoogleCloudAiplatformV1ContainerSpec
    The custom container task.
    diskSpec GoogleCloudAiplatformV1DiskSpec
    Disk spec.
    machineSpec GoogleCloudAiplatformV1MachineSpec
    Optional. Immutable. The specification of a single machine.
    nfsMounts GoogleCloudAiplatformV1NfsMount[]
    Optional. List of NFS mount spec.
    pythonPackageSpec GoogleCloudAiplatformV1PythonPackageSpec
    The Python packaged task.
    replicaCount string
    Optional. The number of worker replicas to use for this worker pool.
    container_spec GoogleCloudAiplatformV1ContainerSpec
    The custom container task.
    disk_spec GoogleCloudAiplatformV1DiskSpec
    Disk spec.
    machine_spec GoogleCloudAiplatformV1MachineSpec
    Optional. Immutable. The specification of a single machine.
    nfs_mounts Sequence[GoogleCloudAiplatformV1NfsMount]
    Optional. List of NFS mount spec.
    python_package_spec GoogleCloudAiplatformV1PythonPackageSpec
    The Python packaged task.
    replica_count str
    Optional. The number of worker replicas to use for this worker pool.
    containerSpec Property Map
    The custom container task.
    diskSpec Property Map
    Disk spec.
    machineSpec Property Map
    Optional. Immutable. The specification of a single machine.
    nfsMounts List<Property Map>
    Optional. List of NFS mount spec.
    pythonPackageSpec Property Map
    The Python packaged task.
    replicaCount String
    Optional. The number of worker replicas to use for this worker pool.

    GoogleCloudAiplatformV1WorkerPoolSpecResponse, GoogleCloudAiplatformV1WorkerPoolSpecResponseArgs

    ContainerSpec GoogleCloudAiplatformV1ContainerSpecResponse
    The custom container task.
    DiskSpec GoogleCloudAiplatformV1DiskSpecResponse
    Disk spec.
    MachineSpec GoogleCloudAiplatformV1MachineSpecResponse
    Optional. Immutable. The specification of a single machine.
    NfsMounts []GoogleCloudAiplatformV1NfsMountResponse
    Optional. List of NFS mount spec.
    PythonPackageSpec GoogleCloudAiplatformV1PythonPackageSpecResponse
    The Python packaged task.
    ReplicaCount string
    Optional. The number of worker replicas to use for this worker pool.
    containerSpec GoogleCloudAiplatformV1ContainerSpecResponse
    The custom container task.
    diskSpec GoogleCloudAiplatformV1DiskSpecResponse
    Disk spec.
    machineSpec GoogleCloudAiplatformV1MachineSpecResponse
    Optional. Immutable. The specification of a single machine.
    nfsMounts List<GoogleCloudAiplatformV1NfsMountResponse>
    Optional. List of NFS mount spec.
    pythonPackageSpec GoogleCloudAiplatformV1PythonPackageSpecResponse
    The Python packaged task.
    replicaCount String
    Optional. The number of worker replicas to use for this worker pool.
    containerSpec GoogleCloudAiplatformV1ContainerSpecResponse
    The custom container task.
    diskSpec GoogleCloudAiplatformV1DiskSpecResponse
    Disk spec.
    machineSpec GoogleCloudAiplatformV1MachineSpecResponse
    Optional. Immutable. The specification of a single machine.
    nfsMounts GoogleCloudAiplatformV1NfsMountResponse[]
    Optional. List of NFS mount spec.
    pythonPackageSpec GoogleCloudAiplatformV1PythonPackageSpecResponse
    The Python packaged task.
    replicaCount string
    Optional. The number of worker replicas to use for this worker pool.
    container_spec GoogleCloudAiplatformV1ContainerSpecResponse
    The custom container task.
    disk_spec GoogleCloudAiplatformV1DiskSpecResponse
    Disk spec.
    machine_spec GoogleCloudAiplatformV1MachineSpecResponse
    Optional. Immutable. The specification of a single machine.
    nfs_mounts Sequence[GoogleCloudAiplatformV1NfsMountResponse]
    Optional. List of NFS mount spec.
    python_package_spec GoogleCloudAiplatformV1PythonPackageSpecResponse
    The Python packaged task.
    replica_count str
    Optional. The number of worker replicas to use for this worker pool.
    containerSpec Property Map
    The custom container task.
    diskSpec Property Map
    Disk spec.
    machineSpec Property Map
    Optional. Immutable. The specification of a single machine.
    nfsMounts List<Property Map>
    Optional. List of NFS mount spec.
    pythonPackageSpec Property Map
    The Python packaged task.
    replicaCount String
    Optional. The number of worker replicas to use for this worker pool.

    GoogleRpcStatusResponse, GoogleRpcStatusResponseArgs

    Code int
    The status code, which should be an enum value of google.rpc.Code.
    Details List<ImmutableDictionary<string, string>>
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    Message string
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    Code int
    The status code, which should be an enum value of google.rpc.Code.
    Details []map[string]string
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    Message string
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    code Integer
    The status code, which should be an enum value of google.rpc.Code.
    details List<Map<String,String>>
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message String
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    code number
    The status code, which should be an enum value of google.rpc.Code.
    details {[key: string]: string}[]
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message string
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    code int
    The status code, which should be an enum value of google.rpc.Code.
    details Sequence[Mapping[str, str]]
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message str
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    code Number
    The status code, which should be an enum value of google.rpc.Code.
    details List<Map<String>>
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message String
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

    Package Details

    Repository
    Google Cloud Native pulumi/pulumi-google-native
    License
    Apache-2.0
    google-native logo

    Google Cloud Native is in preview. Google Cloud Classic is fully supported.

    Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
    pulumi/pulumi-google-native