import * as pulumi from "@pulumi/pulumi";
import * as inputs from "../../types/input";
import * as outputs from "../../types/output";
/**
 * Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start.
 * Auto-naming is currently not supported for this resource.
 */
export declare class BatchPredictionJob extends pulumi.CustomResource {
    /**
     * Get an existing BatchPredictionJob resource's state with the given name, ID, and optional extra
     * properties used to qualify the lookup.
     *
     * @param name The _unique_ name of the resulting resource.
     * @param id The _unique_ provider ID of the resource to lookup.
     * @param opts Optional settings to control the behavior of the CustomResource.
     */
    static get(name: string, id: pulumi.Input<pulumi.ID>, opts?: pulumi.CustomResourceOptions): BatchPredictionJob;
    /**
     * Returns true if the given object is an instance of BatchPredictionJob.  This is designed to work even
     * when multiple copies of the Pulumi SDK have been loaded into the same process.
     */
    static isInstance(obj: any): obj is BatchPredictionJob;
    /**
     * Statistics on completed and failed prediction instances.
     */
    readonly completionStats: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1CompletionStatsResponse>;
    /**
     * Time when the BatchPredictionJob was created.
     */
    readonly createTime: pulumi.Output<string>;
    /**
     * The config of resources used by the Model during the batch prediction. If the Model supports 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.
     */
    readonly dedicatedResources: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1BatchDedicatedResourcesResponse>;
    /**
     * For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.
     */
    readonly disableContainerLogging: pulumi.Output<boolean>;
    /**
     * The user-defined name of this BatchPredictionJob.
     */
    readonly displayName: pulumi.Output<string>;
    /**
     * 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.
     */
    readonly encryptionSpec: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1EncryptionSpecResponse>;
    /**
     * Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
     */
    readonly endTime: pulumi.Output<string>;
    /**
     * Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
     */
    readonly error: pulumi.Output<outputs.aiplatform.v1.GoogleRpcStatusResponse>;
    /**
     * Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.
     */
    readonly explanationSpec: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1ExplanationSpecResponse>;
    /**
     * Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.
     */
    readonly generateExplanation: pulumi.Output<boolean>;
    /**
     * Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.
     */
    readonly inputConfig: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponse>;
    /**
     * Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.
     */
    readonly instanceConfig: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponse>;
    /**
     * 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.
     */
    readonly labels: pulumi.Output<{
        [key: string]: string;
    }>;
    readonly location: pulumi.Output<string>;
    /**
     * Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).
     */
    readonly manualBatchTuningParameters: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1ManualBatchTuningParametersResponse>;
    /**
     * The name of the Model resource 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. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`
     */
    readonly model: pulumi.Output<string>;
    /**
     * The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.
     */
    readonly modelParameters: pulumi.Output<any>;
    /**
     * The version ID of the Model that produces the predictions via this job.
     */
    readonly modelVersionId: pulumi.Output<string>;
    /**
     * Resource name of the BatchPredictionJob.
     */
    readonly name: pulumi.Output<string>;
    /**
     * The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.
     */
    readonly outputConfig: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponse>;
    /**
     * Information further describing the output of this job.
     */
    readonly outputInfo: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponse>;
    /**
     * Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details.
     */
    readonly partialFailures: pulumi.Output<outputs.aiplatform.v1.GoogleRpcStatusResponse[]>;
    readonly project: pulumi.Output<string>;
    /**
     * 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.
     */
    readonly resourcesConsumed: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1ResourcesConsumedResponse>;
    /**
     * The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
     */
    readonly serviceAccount: pulumi.Output<string>;
    /**
     * Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.
     */
    readonly startTime: pulumi.Output<string>;
    /**
     * The detailed state of the job.
     */
    readonly state: pulumi.Output<string>;
    /**
     * Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.
     */
    readonly unmanagedContainerModel: pulumi.Output<outputs.aiplatform.v1.GoogleCloudAiplatformV1UnmanagedContainerModelResponse>;
    /**
     * Time when the BatchPredictionJob was most recently updated.
     */
    readonly updateTime: pulumi.Output<string>;
    /**
     * Create a BatchPredictionJob resource with the given unique name, arguments, and options.
     *
     * @param name The _unique_ name of the resource.
     * @param args The arguments to use to populate this resource's properties.
     * @param opts A bag of options that control this resource's behavior.
     */
    constructor(name: string, args: BatchPredictionJobArgs, opts?: pulumi.CustomResourceOptions);
}
/**
 * The set of arguments for constructing a BatchPredictionJob resource.
 */
export interface BatchPredictionJobArgs {
    /**
     * The config of resources used by the Model during the batch prediction. If the Model supports 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.
     */
    dedicatedResources?: pulumi.Input<inputs.aiplatform.v1.GoogleCloudAiplatformV1BatchDedicatedResourcesArgs>;
    /**
     * For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.
     */
    disableContainerLogging?: pulumi.Input<boolean>;
    /**
     * The user-defined name of this BatchPredictionJob.
     */
    displayName: pulumi.Input<string>;
    /**
     * 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.
     */
    encryptionSpec?: pulumi.Input<inputs.aiplatform.v1.GoogleCloudAiplatformV1EncryptionSpecArgs>;
    /**
     * Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.
     */
    explanationSpec?: pulumi.Input<inputs.aiplatform.v1.GoogleCloudAiplatformV1ExplanationSpecArgs>;
    /**
     * Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.
     */
    generateExplanation?: pulumi.Input<boolean>;
    /**
     * Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.
     */
    inputConfig: pulumi.Input<inputs.aiplatform.v1.GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs>;
    /**
     * Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.
     */
    instanceConfig?: pulumi.Input<inputs.aiplatform.v1.GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs>;
    /**
     * 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.
     */
    labels?: pulumi.Input<{
        [key: string]: pulumi.Input<string>;
    }>;
    location?: pulumi.Input<string>;
    /**
     * Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).
     */
    manualBatchTuningParameters?: pulumi.Input<inputs.aiplatform.v1.GoogleCloudAiplatformV1ManualBatchTuningParametersArgs>;
    /**
     * The name of the Model resource 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. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`
     */
    model?: pulumi.Input<string>;
    /**
     * The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.
     */
    modelParameters?: any;
    /**
     * The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.
     */
    outputConfig: pulumi.Input<inputs.aiplatform.v1.GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs>;
    project?: pulumi.Input<string>;
    /**
     * The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
     */
    serviceAccount?: pulumi.Input<string>;
    /**
     * Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.
     */
    unmanagedContainerModel?: pulumi.Input<inputs.aiplatform.v1.GoogleCloudAiplatformV1UnmanagedContainerModelArgs>;
}