Struct gapi_grpc::google::cloud::aiplatform::v1::BatchPredictionJob

[+] Show declaration

pub struct BatchPredictionJob {
    pub name: String,
    pub display_name: String,
    pub model: String,
    pub input_config: Option<InputConfig>,
    pub model_parameters: Option<Value>,
    pub output_config: Option<OutputConfig>,
    pub dedicated_resources: Option<BatchDedicatedResources>,
    pub manual_batch_tuning_parameters: Option<ManualBatchTuningParameters>,
    pub output_info: Option<OutputInfo>,
    pub state: i32,
    pub error: Option<Status>,
    pub partial_failures: Vec<Status>,
    pub resources_consumed: Option<ResourcesConsumed>,
    pub completion_stats: Option<CompletionStats>,
    pub create_time: Option<Timestamp>,
    pub start_time: Option<Timestamp>,
    pub end_time: Option<Timestamp>,
    pub update_time: Option<Timestamp>,
    pub labels: HashMap<String, String>,
    pub encryption_spec: Option<EncryptionSpec>,
}

[−] Expand description

A job that uses a [Model][google.cloud.aiplatform.v1.BatchPredictionJob.model] to produce predictions on multiple [input instances][google.cloud.aiplatform.v1.BatchPredictionJob.input_config]. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.

Fields

name: String

[−] Expand description

Output only. Resource name of the BatchPredictionJob.

display_name: String

[−] Expand description

Required. The user-defined name of this BatchPredictionJob.

model: String

[−] Expand description

Required. The name of the Model that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources.

input_config: Option<InputConfig>

[−] Expand description

Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the [Model’s][google.cloud.aiplatform.v1.BatchPredictionJob.model] [PredictSchemata’s][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

model_parameters: Option<Value>

[−] Expand description

The parameters that govern the predictions. The schema of the parameters may be specified via the [Model’s][google.cloud.aiplatform.v1.BatchPredictionJob.model] [PredictSchemata’s][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].

output_config: Option<OutputConfig>

[−] Expand description

Required. The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of [Model’s][google.cloud.aiplatform.v1.BatchPredictionJob.model] [PredictSchemata’s][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri] and [prediction_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.prediction_schema_uri].

dedicated_resources: Option<BatchDedicatedResources>

[−] Expand description

The config of resources used by the Model during the batch prediction. If the Model [supports][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types] DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn’t support AUTOMATIC_RESOURCES, this config must be provided.

manual_batch_tuning_parameters: Option<ManualBatchTuningParameters>

[−] Expand description

Immutable. Parameters configuring the batch behavior. Currently only applicable when [dedicated_resources][google.cloud.aiplatform.v1.BatchPredictionJob.dedicated_resources] are used (in other cases Vertex AI does the tuning itself).

output_info: Option<OutputInfo>

[−] Expand description

Output only. Information further describing the output of this job.

state: i32

[−] Expand description

Output only. The detailed state of the job.

error: Option<Status>

[−] Expand description

Output only. Only populated when the job’s state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

partial_failures: Vec<Status>

[−] Expand description

Output only. Partial failures encountered. For example, single files that can’t be read. This field never exceeds 20 entries. Status details fields contain standard GCP error details.

resources_consumed: Option<ResourcesConsumed>

[−] Expand description

Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes.

Note: This field currently may be not populated for batch predictions that use AutoML Models.

completion_stats: Option<CompletionStats>

[−] Expand description

Output only. Statistics on completed and failed prediction instances.

create_time: Option<Timestamp>

[−] Expand description

Output only. Time when the BatchPredictionJob was created.

start_time: Option<Timestamp>

[−] Expand description

Output only. Time when the BatchPredictionJob for the first time entered the JOB_STATE_RUNNING state.

end_time: Option<Timestamp>

[−] Expand description

Output only. Time when the BatchPredictionJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.

update_time: Option<Timestamp>

[−] Expand description

Output only. Time when the BatchPredictionJob was most recently updated.

labels: HashMap<String, String>

[−] Expand description

The labels with user-defined metadata to organize BatchPredictionJobs.

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.

encryption_spec: Option<EncryptionSpec>

[−] Expand description

Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.

Implementations

impl BatchPredictionJob[−]

pub fn state(&self) -> JobState[−]

Returns the enum value of state, or the default if the field is set to an invalid enum value.

pub fn set_state(&mut self, value: JobState)[−]

Sets state to the provided enum value.

Trait Implementations

impl Clone for BatchPredictionJob[+]

[+] Show hidden undocumented items

fn clone(&self) -> BatchPredictionJob[−]

Returns a copy of the value.

pub fn clone_from(&mut self, source: &Self)[−]

Performs copy-assignment from source.

impl Debug for BatchPredictionJob[+]

[+] Show hidden undocumented items

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

Formats the value using the given formatter.

impl Default for BatchPredictionJob[+]

[+] Show hidden undocumented items

fn default() -> BatchPredictionJob[−]

Returns the “default value” for a type.

impl Message for BatchPredictionJob[+]

[+] Show hidden undocumented items

fn encode_raw<B>(&self, buf: &mut B) where
    B: BufMut, 

fn merge_field<B>(
    &mut self,
    tag: u32,
    wire_type: WireType,
    buf: &mut B,
    ctx: DecodeContext
) -> Result<(), DecodeError> where
    B: Buf, 

fn encoded_len(&self) -> usize[−]

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)[−]

Clears the message, resetting all fields to their default.

pub fn encode<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
    B: BufMut, [−]

Encodes the message to a buffer.

pub fn encode_length_delimited<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
    B: BufMut, [−]

Encodes the message with a length-delimiter to a buffer.

pub fn decode<B>(buf: B) -> Result<Self, DecodeError> where
    Self: Default,
    B: Buf, [−]

Decodes an instance of the message from a buffer.

pub fn decode_length_delimited<B>(buf: B) -> Result<Self, DecodeError> where
    Self: Default,
    B: Buf, [−]

Decodes a length-delimited instance of the message from the buffer.

pub fn merge<B>(&mut self, buf: B) -> Result<(), DecodeError> where
    B: Buf, [−]

Decodes an instance of the message from a buffer, and merges it into self.

pub fn merge_length_delimited<B>(&mut self, buf: B) -> Result<(), DecodeError> where
    B: Buf, [−]

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq<BatchPredictionJob> for BatchPredictionJob[+]

[+] Show hidden undocumented items

fn eq(&self, other: &BatchPredictionJob) -> bool[−]

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &BatchPredictionJob) -> bool[−]

This method tests for !=.

impl StructuralPartialEq for BatchPredictionJob