Struct CustomJobSpec

#[non_exhaustive]
pub struct CustomJobSpec {

    pub persistent_resource_id: String,
    pub worker_pool_specs: Vec<WorkerPoolSpec>,
    pub scheduling: Option<Scheduling>,
    pub service_account: String,
    pub network: String,
    pub reserved_ip_ranges: Vec<String>,
    pub base_output_directory: Option<GcsDestination>,
    pub protected_artifact_location_id: String,
    pub tensorboard: String,
    pub enable_web_access: bool,
    pub enable_dashboard_access: bool,
    pub experiment: String,
    pub experiment_run: String,
    pub models: Vec<String>,
    /* private fields */
}

Represents the spec of a CustomJob.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

persistent_resource_id: String

Optional. The ID of the PersistentResource in the same Project and Location which to run

If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected.

worker_pool_specs: Vec<WorkerPoolSpec>

Required. 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.

scheduling: Option<Scheduling>

Scheduling options for a CustomJob.

service_account: 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.

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.

reserved_ip_ranges: Vec<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’].

base_output_directory: Option<GcsDestination>

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 = <base_output_directory>/model/
• AIP_CHECKPOINT_DIR = <base_output_directory>/checkpoints/
• AIP_TENSORBOARD_LOG_DIR = <base_output_directory>/logs/

For CustomJob backing a Trial of HyperparameterTuningJob:

• AIP_MODEL_DIR = <base_output_directory>/<trial_id>/model/
• AIP_CHECKPOINT_DIR = <base_output_directory>/<trial_id>/checkpoints/
• AIP_TENSORBOARD_LOG_DIR = <base_output_directory>/<trial_id>/logs/

protected_artifact_location_id: 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

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}

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).

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).

experiment: String

Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}

experiment_run: String

Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}

models: Vec<String>

Optional. The name of the Model resources for which to generate a mapping to artifact URIs. Applicable only to some of the Google-provided custom jobs. Format: projects/{project}/locations/{location}/models/{model}

In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: projects/{project}/locations/{location}/models/{model}@2 or projects/{project}/locations/{location}/models/{model}@golden If no version ID or alias is specified, the “default” version will be returned. The “default” version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version.

Implementations

impl CustomJobSpec

pub fn new() -> Self

pub fn set_persistent_resource_id<T: Into<String>>(self, v: T) -> Self

Sets the value of persistent_resource_id.

pub fn set_worker_pool_specs<T, V>(self, v: T) -> Self

where T: IntoIterator<Item = V>, V: Into<WorkerPoolSpec>,

Sets the value of worker_pool_specs.

pub fn set_scheduling<T: Into<Option<Scheduling>>>(self, v: T) -> Self

Sets the value of scheduling.

pub fn set_service_account<T: Into<String>>(self, v: T) -> Self

Sets the value of service_account.

pub fn set_network<T: Into<String>>(self, v: T) -> Self

Sets the value of network.

pub fn set_reserved_ip_ranges<T, V>(self, v: T) -> Self

where T: IntoIterator<Item = V>, V: Into<String>,

Sets the value of reserved_ip_ranges.

pub fn set_base_output_directory<T: Into<Option<GcsDestination>>>( self, v: T, ) -> Self

Sets the value of base_output_directory.

pub fn set_protected_artifact_location_id<T: Into<String>>(self, v: T) -> Self

Sets the value of protected_artifact_location_id.

pub fn set_tensorboard<T: Into<String>>(self, v: T) -> Self

Sets the value of tensorboard.

pub fn set_enable_web_access<T: Into<bool>>(self, v: T) -> Self

Sets the value of enable_web_access.

pub fn set_enable_dashboard_access<T: Into<bool>>(self, v: T) -> Self

Sets the value of enable_dashboard_access.

pub fn set_experiment<T: Into<String>>(self, v: T) -> Self

Sets the value of experiment.

pub fn set_experiment_run<T: Into<String>>(self, v: T) -> Self

Sets the value of experiment_run.

pub fn set_models<T, V>(self, v: T) -> Self

where T: IntoIterator<Item = V>, V: Into<String>,

Sets the value of models.

Trait Implementations

impl Clone for CustomJobSpec

fn clone(&self) -> CustomJobSpec

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CustomJobSpec

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for CustomJobSpec

fn default() -> CustomJobSpec

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for CustomJobSpec

where CustomJobSpec: Default,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Message for CustomJobSpec

fn typename() -> &'static str

The typename of this message.

impl PartialEq for CustomJobSpec

fn eq(&self, other: &CustomJobSpec) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for CustomJobSpec

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for CustomJobSpec