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

google-native.retail/v2beta.Model

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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
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    Creates a new model.

    Create Model Resource

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

    Constructor syntax

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

@overload
def Model(resource_name: str,
          opts: Optional[ResourceOptions] = None,
          catalog_id: Optional[str] = None,
          display_name: Optional[str] = None,
          type: Optional[str] = None,
          dry_run: Optional[bool] = None,
          filtering_option: Optional[ModelFilteringOption] = None,
          location: Optional[str] = None,
          model_features_config: Optional[GoogleCloudRetailV2betaModelModelFeaturesConfigArgs] = None,
          name: Optional[str] = None,
          optimization_objective: Optional[str] = None,
          periodic_tuning_state: Optional[ModelPeriodicTuningState] = None,
          project: Optional[str] = None,
          training_state: Optional[ModelTrainingState] = None)
    func NewModel(ctx *Context, name string, args ModelArgs, opts ...ResourceOption) (*Model, error)
    public Model(string name, ModelArgs args, CustomResourceOptions? opts = null)
    public Model(String name, ModelArgs args)
public Model(String name, ModelArgs args, CustomResourceOptions options)

    type: google-native:retail/v2beta:Model
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 ModelArgs
    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 ModelArgs
    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 ModelArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args ModelArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args ModelArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

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

    var examplemodelResourceResourceFromRetailv2beta = new GoogleNative.Retail.V2Beta.Model("examplemodelResourceResourceFromRetailv2beta", new()
{
    CatalogId = "string",
    DisplayName = "string",
    Type = "string",
    DryRun = false,
    FilteringOption = GoogleNative.Retail.V2Beta.ModelFilteringOption.RecommendationsFilteringOptionUnspecified,
    Location = "string",
    ModelFeaturesConfig = new GoogleNative.Retail.V2Beta.Inputs.GoogleCloudRetailV2betaModelModelFeaturesConfigArgs
    {
        FrequentlyBoughtTogetherConfig = new GoogleNative.Retail.V2Beta.Inputs.GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigArgs
        {
            ContextProductsType = GoogleNative.Retail.V2Beta.GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType.ContextProductsTypeUnspecified,
        },
    },
    Name = "string",
    OptimizationObjective = "string",
    PeriodicTuningState = GoogleNative.Retail.V2Beta.ModelPeriodicTuningState.PeriodicTuningStateUnspecified,
    Project = "string",
    TrainingState = GoogleNative.Retail.V2Beta.ModelTrainingState.TrainingStateUnspecified,
});

    example, err := retailv2beta.NewModel(ctx, "examplemodelResourceResourceFromRetailv2beta", &retailv2beta.ModelArgs{
	CatalogId:       pulumi.String("string"),
	DisplayName:     pulumi.String("string"),
	Type:            pulumi.String("string"),
	DryRun:          pulumi.Bool(false),
	FilteringOption: retailv2beta.ModelFilteringOptionRecommendationsFilteringOptionUnspecified,
	Location:        pulumi.String("string"),
	ModelFeaturesConfig: &retail.GoogleCloudRetailV2betaModelModelFeaturesConfigArgs{
		FrequentlyBoughtTogetherConfig: &retail.GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigArgs{
			ContextProductsType: retailv2beta.GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeContextProductsTypeUnspecified,
		},
	},
	Name:                  pulumi.String("string"),
	OptimizationObjective: pulumi.String("string"),
	PeriodicTuningState:   retailv2beta.ModelPeriodicTuningStatePeriodicTuningStateUnspecified,
	Project:               pulumi.String("string"),
	TrainingState:         retailv2beta.ModelTrainingStateTrainingStateUnspecified,
})

    var examplemodelResourceResourceFromRetailv2beta = new Model("examplemodelResourceResourceFromRetailv2beta", ModelArgs.builder()
    .catalogId("string")
    .displayName("string")
    .type("string")
    .dryRun(false)
    .filteringOption("RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIED")
    .location("string")
    .modelFeaturesConfig(GoogleCloudRetailV2betaModelModelFeaturesConfigArgs.builder()
        .frequentlyBoughtTogetherConfig(GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigArgs.builder()
            .contextProductsType("CONTEXT_PRODUCTS_TYPE_UNSPECIFIED")
            .build())
        .build())
    .name("string")
    .optimizationObjective("string")
    .periodicTuningState("PERIODIC_TUNING_STATE_UNSPECIFIED")
    .project("string")
    .trainingState("TRAINING_STATE_UNSPECIFIED")
    .build());

    examplemodel_resource_resource_from_retailv2beta = google_native.retail.v2beta.Model("examplemodelResourceResourceFromRetailv2beta",
    catalog_id="string",
    display_name="string",
    type="string",
    dry_run=False,
    filtering_option=google_native.retail.v2beta.ModelFilteringOption.RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIED,
    location="string",
    model_features_config={
        "frequently_bought_together_config": {
            "context_products_type": google_native.retail.v2beta.GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType.CONTEXT_PRODUCTS_TYPE_UNSPECIFIED,
        },
    },
    name="string",
    optimization_objective="string",
    periodic_tuning_state=google_native.retail.v2beta.ModelPeriodicTuningState.PERIODIC_TUNING_STATE_UNSPECIFIED,
    project="string",
    training_state=google_native.retail.v2beta.ModelTrainingState.TRAINING_STATE_UNSPECIFIED)

    const examplemodelResourceResourceFromRetailv2beta = new google_native.retail.v2beta.Model("examplemodelResourceResourceFromRetailv2beta", {
    catalogId: "string",
    displayName: "string",
    type: "string",
    dryRun: false,
    filteringOption: google_native.retail.v2beta.ModelFilteringOption.RecommendationsFilteringOptionUnspecified,
    location: "string",
    modelFeaturesConfig: {
        frequentlyBoughtTogetherConfig: {
            contextProductsType: google_native.retail.v2beta.GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType.ContextProductsTypeUnspecified,
        },
    },
    name: "string",
    optimizationObjective: "string",
    periodicTuningState: google_native.retail.v2beta.ModelPeriodicTuningState.PeriodicTuningStateUnspecified,
    project: "string",
    trainingState: google_native.retail.v2beta.ModelTrainingState.TrainingStateUnspecified,
});

    type: google-native:retail/v2beta:Model
properties:
    catalogId: string
    displayName: string
    dryRun: false
    filteringOption: RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIED
    location: string
    modelFeaturesConfig:
        frequentlyBoughtTogetherConfig:
            contextProductsType: CONTEXT_PRODUCTS_TYPE_UNSPECIFIED
    name: string
    optimizationObjective: string
    periodicTuningState: PERIODIC_TUNING_STATE_UNSPECIFIED
    project: string
    trainingState: TRAINING_STATE_UNSPECIFIED
    type: string

    Model Resource Properties

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

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The Model resource accepts the following input properties:

    CatalogId string
    DisplayName string
    The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
    Type string
    The type of model e.g. home-page. Currently supported values: recommended-for-you, others-you-may-like, frequently-bought-together, page-optimization, similar-items, buy-it-again, on-sale-items, and recently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    DryRun bool
    Optional. Whether to run a dry run to validate the request (without actually creating the model).
    FilteringOption Pulumi.GoogleNative.Retail.V2Beta.ModelFilteringOption
    Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.
    Location string
    ModelFeaturesConfig Pulumi.GoogleNative.Retail.V2Beta.Inputs.GoogleCloudRetailV2betaModelModelFeaturesConfig
    Optional. Additional model features config.
    Name string
    The fully qualified resource name of the model. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id} catalog_id has char limit of 50. recommendation_model_id has char limit of 40.
    OptimizationObjective string
    Optional. The optimization objective e.g. cvr. Currently supported values: ctr, cvr, revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation: recommended-for-you => ctr others-you-may-like => ctr frequently-bought-together => revenue_per_order This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    PeriodicTuningState Pulumi.GoogleNative.Retail.V2Beta.ModelPeriodicTuningState
    Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the TuneModel method. Default value is PERIODIC_TUNING_ENABLED.
    Project string
    TrainingState Pulumi.GoogleNative.Retail.V2Beta.ModelTrainingState
    Optional. The training state that the model is in (e.g. TRAINING or PAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for CreateModel method is TRAINING. The default value for UpdateModel method is to keep the state the same as before.
    CatalogId string
    DisplayName string
    The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
    Type string
    The type of model e.g. home-page. Currently supported values: recommended-for-you, others-you-may-like, frequently-bought-together, page-optimization, similar-items, buy-it-again, on-sale-items, and recently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    DryRun bool
    Optional. Whether to run a dry run to validate the request (without actually creating the model).
    FilteringOption ModelFilteringOption
    Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.
    Location string
    ModelFeaturesConfig GoogleCloudRetailV2betaModelModelFeaturesConfigArgs
    Optional. Additional model features config.
    Name string
    The fully qualified resource name of the model. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id} catalog_id has char limit of 50. recommendation_model_id has char limit of 40.
    OptimizationObjective string
    Optional. The optimization objective e.g. cvr. Currently supported values: ctr, cvr, revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation: recommended-for-you => ctr others-you-may-like => ctr frequently-bought-together => revenue_per_order This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    PeriodicTuningState ModelPeriodicTuningState
    Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the TuneModel method. Default value is PERIODIC_TUNING_ENABLED.
    Project string
    TrainingState ModelTrainingState
    Optional. The training state that the model is in (e.g. TRAINING or PAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for CreateModel method is TRAINING. The default value for UpdateModel method is to keep the state the same as before.
    catalogId String
    displayName String
    The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
    type String
    The type of model e.g. home-page. Currently supported values: recommended-for-you, others-you-may-like, frequently-bought-together, page-optimization, similar-items, buy-it-again, on-sale-items, and recently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    dryRun Boolean
    Optional. Whether to run a dry run to validate the request (without actually creating the model).
    filteringOption ModelFilteringOption
    Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.
    location String
    modelFeaturesConfig GoogleCloudRetailV2betaModelModelFeaturesConfig
    Optional. Additional model features config.
    name String
    The fully qualified resource name of the model. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id} catalog_id has char limit of 50. recommendation_model_id has char limit of 40.
    optimizationObjective String
    Optional. The optimization objective e.g. cvr. Currently supported values: ctr, cvr, revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation: recommended-for-you => ctr others-you-may-like => ctr frequently-bought-together => revenue_per_order This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    periodicTuningState ModelPeriodicTuningState
    Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the TuneModel method. Default value is PERIODIC_TUNING_ENABLED.
    project String
    trainingState ModelTrainingState
    Optional. The training state that the model is in (e.g. TRAINING or PAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for CreateModel method is TRAINING. The default value for UpdateModel method is to keep the state the same as before.
    catalogId string
    displayName string
    The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
    type string
    The type of model e.g. home-page. Currently supported values: recommended-for-you, others-you-may-like, frequently-bought-together, page-optimization, similar-items, buy-it-again, on-sale-items, and recently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    dryRun boolean
    Optional. Whether to run a dry run to validate the request (without actually creating the model).
    filteringOption ModelFilteringOption
    Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.
    location string
    modelFeaturesConfig GoogleCloudRetailV2betaModelModelFeaturesConfig
    Optional. Additional model features config.
    name string
    The fully qualified resource name of the model. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id} catalog_id has char limit of 50. recommendation_model_id has char limit of 40.
    optimizationObjective string
    Optional. The optimization objective e.g. cvr. Currently supported values: ctr, cvr, revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation: recommended-for-you => ctr others-you-may-like => ctr frequently-bought-together => revenue_per_order This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    periodicTuningState ModelPeriodicTuningState
    Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the TuneModel method. Default value is PERIODIC_TUNING_ENABLED.
    project string
    trainingState ModelTrainingState
    Optional. The training state that the model is in (e.g. TRAINING or PAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for CreateModel method is TRAINING. The default value for UpdateModel method is to keep the state the same as before.
    catalog_id str
    display_name str
    The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
    type str
    The type of model e.g. home-page. Currently supported values: recommended-for-you, others-you-may-like, frequently-bought-together, page-optimization, similar-items, buy-it-again, on-sale-items, and recently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    dry_run bool
    Optional. Whether to run a dry run to validate the request (without actually creating the model).
    filtering_option ModelFilteringOption
    Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.
    location str
    model_features_config GoogleCloudRetailV2betaModelModelFeaturesConfigArgs
    Optional. Additional model features config.
    name str
    The fully qualified resource name of the model. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id} catalog_id has char limit of 50. recommendation_model_id has char limit of 40.
    optimization_objective str
    Optional. The optimization objective e.g. cvr. Currently supported values: ctr, cvr, revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation: recommended-for-you => ctr others-you-may-like => ctr frequently-bought-together => revenue_per_order This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    periodic_tuning_state ModelPeriodicTuningState
    Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the TuneModel method. Default value is PERIODIC_TUNING_ENABLED.
    project str
    training_state ModelTrainingState
    Optional. The training state that the model is in (e.g. TRAINING or PAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for CreateModel method is TRAINING. The default value for UpdateModel method is to keep the state the same as before.
    catalogId String
    displayName String
    The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
    type String
    The type of model e.g. home-page. Currently supported values: recommended-for-you, others-you-may-like, frequently-bought-together, page-optimization, similar-items, buy-it-again, on-sale-items, and recently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    dryRun Boolean
    Optional. Whether to run a dry run to validate the request (without actually creating the model).
    filteringOption "RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIED" | "RECOMMENDATIONS_FILTERING_DISABLED" | "RECOMMENDATIONS_FILTERING_ENABLED"
    Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.
    location String
    modelFeaturesConfig Property Map
    Optional. Additional model features config.
    name String
    The fully qualified resource name of the model. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id} catalog_id has char limit of 50. recommendation_model_id has char limit of 40.
    optimizationObjective String
    Optional. The optimization objective e.g. cvr. Currently supported values: ctr, cvr, revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation: recommended-for-you => ctr others-you-may-like => ctr frequently-bought-together => revenue_per_order This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
    periodicTuningState "PERIODIC_TUNING_STATE_UNSPECIFIED" | "PERIODIC_TUNING_DISABLED" | "ALL_TUNING_DISABLED" | "PERIODIC_TUNING_ENABLED"
    Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the TuneModel method. Default value is PERIODIC_TUNING_ENABLED.
    project String
    trainingState "TRAINING_STATE_UNSPECIFIED" | "PAUSED" | "TRAINING"
    Optional. The training state that the model is in (e.g. TRAINING or PAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for CreateModel method is TRAINING. The default value for UpdateModel method is to keep the state the same as before.

    Outputs

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

    CreateTime string
    Timestamp the Recommendation Model was created at.
    DataState string
    The state of data requirements for this model: DATA_OK and DATA_ERROR. Recommendation model cannot be trained if the data is in DATA_ERROR state. Recommendation model can have DATA_ERROR state even if serving state is ACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training.
    Id string
    The provider-assigned unique ID for this managed resource.
    LastTuneTime string
    The timestamp when the latest successful tune finished.
    ServingConfigLists List<Pulumi.GoogleNative.Retail.V2Beta.Outputs.GoogleCloudRetailV2betaModelServingConfigListResponse>
    The list of valid serving configs associated with the PageOptimizationConfig.
    ServingState string
    The serving state of the model: ACTIVE, NOT_ACTIVE.
    TuningOperation string
    The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
    UpdateTime string
    Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
    CreateTime string
    Timestamp the Recommendation Model was created at.
    DataState string
    The state of data requirements for this model: DATA_OK and DATA_ERROR. Recommendation model cannot be trained if the data is in DATA_ERROR state. Recommendation model can have DATA_ERROR state even if serving state is ACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training.
    Id string
    The provider-assigned unique ID for this managed resource.
    LastTuneTime string
    The timestamp when the latest successful tune finished.
    ServingConfigLists []GoogleCloudRetailV2betaModelServingConfigListResponse
    The list of valid serving configs associated with the PageOptimizationConfig.
    ServingState string
    The serving state of the model: ACTIVE, NOT_ACTIVE.
    TuningOperation string
    The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
    UpdateTime string
    Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
    createTime String
    Timestamp the Recommendation Model was created at.
    dataState String
    The state of data requirements for this model: DATA_OK and DATA_ERROR. Recommendation model cannot be trained if the data is in DATA_ERROR state. Recommendation model can have DATA_ERROR state even if serving state is ACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training.
    id String
    The provider-assigned unique ID for this managed resource.
    lastTuneTime String
    The timestamp when the latest successful tune finished.
    servingConfigLists List<GoogleCloudRetailV2betaModelServingConfigListResponse>
    The list of valid serving configs associated with the PageOptimizationConfig.
    servingState String
    The serving state of the model: ACTIVE, NOT_ACTIVE.
    tuningOperation String
    The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
    updateTime String
    Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
    createTime string
    Timestamp the Recommendation Model was created at.
    dataState string
    The state of data requirements for this model: DATA_OK and DATA_ERROR. Recommendation model cannot be trained if the data is in DATA_ERROR state. Recommendation model can have DATA_ERROR state even if serving state is ACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training.
    id string
    The provider-assigned unique ID for this managed resource.
    lastTuneTime string
    The timestamp when the latest successful tune finished.
    servingConfigLists GoogleCloudRetailV2betaModelServingConfigListResponse[]
    The list of valid serving configs associated with the PageOptimizationConfig.
    servingState string
    The serving state of the model: ACTIVE, NOT_ACTIVE.
    tuningOperation string
    The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
    updateTime string
    Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
    create_time str
    Timestamp the Recommendation Model was created at.
    data_state str
    The state of data requirements for this model: DATA_OK and DATA_ERROR. Recommendation model cannot be trained if the data is in DATA_ERROR state. Recommendation model can have DATA_ERROR state even if serving state is ACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training.
    id str
    The provider-assigned unique ID for this managed resource.
    last_tune_time str
    The timestamp when the latest successful tune finished.
    serving_config_lists Sequence[GoogleCloudRetailV2betaModelServingConfigListResponse]
    The list of valid serving configs associated with the PageOptimizationConfig.
    serving_state str
    The serving state of the model: ACTIVE, NOT_ACTIVE.
    tuning_operation str
    The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
    update_time str
    Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.
    createTime String
    Timestamp the Recommendation Model was created at.
    dataState String
    The state of data requirements for this model: DATA_OK and DATA_ERROR. Recommendation model cannot be trained if the data is in DATA_ERROR state. Recommendation model can have DATA_ERROR state even if serving state is ACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training.
    id String
    The provider-assigned unique ID for this managed resource.
    lastTuneTime String
    The timestamp when the latest successful tune finished.
    servingConfigLists List<Property Map>
    The list of valid serving configs associated with the PageOptimizationConfig.
    servingState String
    The serving state of the model: ACTIVE, NOT_ACTIVE.
    tuningOperation String
    The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
    updateTime String
    Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.

    Supporting Types

    GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfig, GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigArgs

    ContextProductsType Pulumi.GoogleNative.Retail.V2Beta.GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    ContextProductsType GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    contextProductsType GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    contextProductsType GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    context_products_type GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    contextProductsType "CONTEXT_PRODUCTS_TYPE_UNSPECIFIED" | "SINGLE_CONTEXT_PRODUCT" | "MULTIPLE_CONTEXT_PRODUCTS"
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.

    GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType, GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeArgs

    ContextProductsTypeUnspecified
    CONTEXT_PRODUCTS_TYPE_UNSPECIFIEDUnspecified default value, should never be explicitly set. Defaults to MULTIPLE_CONTEXT_PRODUCTS.
    SingleContextProduct
    SINGLE_CONTEXT_PRODUCTUse only a single product as context for the recommendation. Typically used on pages like add-to-cart or product details.
    MultipleContextProducts
    MULTIPLE_CONTEXT_PRODUCTSUse one or multiple products as context for the recommendation. Typically used on shopping cart pages.
    GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeContextProductsTypeUnspecified
    CONTEXT_PRODUCTS_TYPE_UNSPECIFIEDUnspecified default value, should never be explicitly set. Defaults to MULTIPLE_CONTEXT_PRODUCTS.
    GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeSingleContextProduct
    SINGLE_CONTEXT_PRODUCTUse only a single product as context for the recommendation. Typically used on pages like add-to-cart or product details.
    GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeMultipleContextProducts
    MULTIPLE_CONTEXT_PRODUCTSUse one or multiple products as context for the recommendation. Typically used on shopping cart pages.
    ContextProductsTypeUnspecified
    CONTEXT_PRODUCTS_TYPE_UNSPECIFIEDUnspecified default value, should never be explicitly set. Defaults to MULTIPLE_CONTEXT_PRODUCTS.
    SingleContextProduct
    SINGLE_CONTEXT_PRODUCTUse only a single product as context for the recommendation. Typically used on pages like add-to-cart or product details.
    MultipleContextProducts
    MULTIPLE_CONTEXT_PRODUCTSUse one or multiple products as context for the recommendation. Typically used on shopping cart pages.
    ContextProductsTypeUnspecified
    CONTEXT_PRODUCTS_TYPE_UNSPECIFIEDUnspecified default value, should never be explicitly set. Defaults to MULTIPLE_CONTEXT_PRODUCTS.
    SingleContextProduct
    SINGLE_CONTEXT_PRODUCTUse only a single product as context for the recommendation. Typically used on pages like add-to-cart or product details.
    MultipleContextProducts
    MULTIPLE_CONTEXT_PRODUCTSUse one or multiple products as context for the recommendation. Typically used on shopping cart pages.
    CONTEXT_PRODUCTS_TYPE_UNSPECIFIED
    CONTEXT_PRODUCTS_TYPE_UNSPECIFIEDUnspecified default value, should never be explicitly set. Defaults to MULTIPLE_CONTEXT_PRODUCTS.
    SINGLE_CONTEXT_PRODUCT
    SINGLE_CONTEXT_PRODUCTUse only a single product as context for the recommendation. Typically used on pages like add-to-cart or product details.
    MULTIPLE_CONTEXT_PRODUCTS
    MULTIPLE_CONTEXT_PRODUCTSUse one or multiple products as context for the recommendation. Typically used on shopping cart pages.
    "CONTEXT_PRODUCTS_TYPE_UNSPECIFIED"
    CONTEXT_PRODUCTS_TYPE_UNSPECIFIEDUnspecified default value, should never be explicitly set. Defaults to MULTIPLE_CONTEXT_PRODUCTS.
    "SINGLE_CONTEXT_PRODUCT"
    SINGLE_CONTEXT_PRODUCTUse only a single product as context for the recommendation. Typically used on pages like add-to-cart or product details.
    "MULTIPLE_CONTEXT_PRODUCTS"
    MULTIPLE_CONTEXT_PRODUCTSUse one or multiple products as context for the recommendation. Typically used on shopping cart pages.

    GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigResponse, GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigResponseArgs

    ContextProductsType string
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    ContextProductsType string
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    contextProductsType String
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    contextProductsType string
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    context_products_type str
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.
    contextProductsType String
    Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.

    GoogleCloudRetailV2betaModelModelFeaturesConfig, GoogleCloudRetailV2betaModelModelFeaturesConfigArgs

    frequentlyBoughtTogetherConfig Property Map
    Additional configs for frequently-bought-together models.

    GoogleCloudRetailV2betaModelModelFeaturesConfigResponse, GoogleCloudRetailV2betaModelModelFeaturesConfigResponseArgs

    frequentlyBoughtTogetherConfig Property Map
    Additional configs for frequently-bought-together models.

    GoogleCloudRetailV2betaModelServingConfigListResponse, GoogleCloudRetailV2betaModelServingConfigListResponseArgs

    ServingConfigIds List<string>
    Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.
    ServingConfigIds []string
    Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.
    servingConfigIds List<String>
    Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.
    servingConfigIds string[]
    Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.
    serving_config_ids Sequence[str]
    Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.
    servingConfigIds List<String>
    Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.

    ModelFilteringOption, ModelFilteringOptionArgs

    RecommendationsFilteringOptionUnspecified
    RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIEDValue used when unset. In this case, server behavior defaults to RECOMMENDATIONS_FILTERING_DISABLED.
    RecommendationsFilteringDisabled
    RECOMMENDATIONS_FILTERING_DISABLEDRecommendation filtering is disabled.
    RecommendationsFilteringEnabled
    RECOMMENDATIONS_FILTERING_ENABLEDRecommendation filtering is enabled.
    ModelFilteringOptionRecommendationsFilteringOptionUnspecified
    RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIEDValue used when unset. In this case, server behavior defaults to RECOMMENDATIONS_FILTERING_DISABLED.
    ModelFilteringOptionRecommendationsFilteringDisabled
    RECOMMENDATIONS_FILTERING_DISABLEDRecommendation filtering is disabled.
    ModelFilteringOptionRecommendationsFilteringEnabled
    RECOMMENDATIONS_FILTERING_ENABLEDRecommendation filtering is enabled.
    RecommendationsFilteringOptionUnspecified
    RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIEDValue used when unset. In this case, server behavior defaults to RECOMMENDATIONS_FILTERING_DISABLED.
    RecommendationsFilteringDisabled
    RECOMMENDATIONS_FILTERING_DISABLEDRecommendation filtering is disabled.
    RecommendationsFilteringEnabled
    RECOMMENDATIONS_FILTERING_ENABLEDRecommendation filtering is enabled.
    RecommendationsFilteringOptionUnspecified
    RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIEDValue used when unset. In this case, server behavior defaults to RECOMMENDATIONS_FILTERING_DISABLED.
    RecommendationsFilteringDisabled
    RECOMMENDATIONS_FILTERING_DISABLEDRecommendation filtering is disabled.
    RecommendationsFilteringEnabled
    RECOMMENDATIONS_FILTERING_ENABLEDRecommendation filtering is enabled.
    RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIED
    RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIEDValue used when unset. In this case, server behavior defaults to RECOMMENDATIONS_FILTERING_DISABLED.
    RECOMMENDATIONS_FILTERING_DISABLED
    RECOMMENDATIONS_FILTERING_DISABLEDRecommendation filtering is disabled.
    RECOMMENDATIONS_FILTERING_ENABLED
    RECOMMENDATIONS_FILTERING_ENABLEDRecommendation filtering is enabled.
    "RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIED"
    RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIEDValue used when unset. In this case, server behavior defaults to RECOMMENDATIONS_FILTERING_DISABLED.
    "RECOMMENDATIONS_FILTERING_DISABLED"
    RECOMMENDATIONS_FILTERING_DISABLEDRecommendation filtering is disabled.
    "RECOMMENDATIONS_FILTERING_ENABLED"
    RECOMMENDATIONS_FILTERING_ENABLEDRecommendation filtering is enabled.

    ModelPeriodicTuningState, ModelPeriodicTuningStateArgs

    PeriodicTuningStateUnspecified
    PERIODIC_TUNING_STATE_UNSPECIFIEDUnspecified default value, should never be explicitly set.
    PeriodicTuningDisabled
    PERIODIC_TUNING_DISABLEDThe model has periodic tuning disabled. Tuning can be reenabled by calling the EnableModelPeriodicTuning method or by calling the TuneModel method.
    AllTuningDisabled
    ALL_TUNING_DISABLEDThe model cannot be tuned with periodic tuning OR the TuneModel method. Hide the options in customer UI and reject any requests through the backend self serve API.
    PeriodicTuningEnabled
    PERIODIC_TUNING_ENABLEDThe model has periodic tuning enabled. Tuning can be disabled by calling the DisableModelPeriodicTuning method.
    ModelPeriodicTuningStatePeriodicTuningStateUnspecified
    PERIODIC_TUNING_STATE_UNSPECIFIEDUnspecified default value, should never be explicitly set.
    ModelPeriodicTuningStatePeriodicTuningDisabled
    PERIODIC_TUNING_DISABLEDThe model has periodic tuning disabled. Tuning can be reenabled by calling the EnableModelPeriodicTuning method or by calling the TuneModel method.
    ModelPeriodicTuningStateAllTuningDisabled
    ALL_TUNING_DISABLEDThe model cannot be tuned with periodic tuning OR the TuneModel method. Hide the options in customer UI and reject any requests through the backend self serve API.
    ModelPeriodicTuningStatePeriodicTuningEnabled
    PERIODIC_TUNING_ENABLEDThe model has periodic tuning enabled. Tuning can be disabled by calling the DisableModelPeriodicTuning method.
    PeriodicTuningStateUnspecified
    PERIODIC_TUNING_STATE_UNSPECIFIEDUnspecified default value, should never be explicitly set.
    PeriodicTuningDisabled
    PERIODIC_TUNING_DISABLEDThe model has periodic tuning disabled. Tuning can be reenabled by calling the EnableModelPeriodicTuning method or by calling the TuneModel method.
    AllTuningDisabled
    ALL_TUNING_DISABLEDThe model cannot be tuned with periodic tuning OR the TuneModel method. Hide the options in customer UI and reject any requests through the backend self serve API.
    PeriodicTuningEnabled
    PERIODIC_TUNING_ENABLEDThe model has periodic tuning enabled. Tuning can be disabled by calling the DisableModelPeriodicTuning method.
    PeriodicTuningStateUnspecified
    PERIODIC_TUNING_STATE_UNSPECIFIEDUnspecified default value, should never be explicitly set.
    PeriodicTuningDisabled
    PERIODIC_TUNING_DISABLEDThe model has periodic tuning disabled. Tuning can be reenabled by calling the EnableModelPeriodicTuning method or by calling the TuneModel method.
    AllTuningDisabled
    ALL_TUNING_DISABLEDThe model cannot be tuned with periodic tuning OR the TuneModel method. Hide the options in customer UI and reject any requests through the backend self serve API.
    PeriodicTuningEnabled
    PERIODIC_TUNING_ENABLEDThe model has periodic tuning enabled. Tuning can be disabled by calling the DisableModelPeriodicTuning method.
    PERIODIC_TUNING_STATE_UNSPECIFIED
    PERIODIC_TUNING_STATE_UNSPECIFIEDUnspecified default value, should never be explicitly set.
    PERIODIC_TUNING_DISABLED
    PERIODIC_TUNING_DISABLEDThe model has periodic tuning disabled. Tuning can be reenabled by calling the EnableModelPeriodicTuning method or by calling the TuneModel method.
    ALL_TUNING_DISABLED
    ALL_TUNING_DISABLEDThe model cannot be tuned with periodic tuning OR the TuneModel method. Hide the options in customer UI and reject any requests through the backend self serve API.
    PERIODIC_TUNING_ENABLED
    PERIODIC_TUNING_ENABLEDThe model has periodic tuning enabled. Tuning can be disabled by calling the DisableModelPeriodicTuning method.
    "PERIODIC_TUNING_STATE_UNSPECIFIED"
    PERIODIC_TUNING_STATE_UNSPECIFIEDUnspecified default value, should never be explicitly set.
    "PERIODIC_TUNING_DISABLED"
    PERIODIC_TUNING_DISABLEDThe model has periodic tuning disabled. Tuning can be reenabled by calling the EnableModelPeriodicTuning method or by calling the TuneModel method.
    "ALL_TUNING_DISABLED"
    ALL_TUNING_DISABLEDThe model cannot be tuned with periodic tuning OR the TuneModel method. Hide the options in customer UI and reject any requests through the backend self serve API.
    "PERIODIC_TUNING_ENABLED"
    PERIODIC_TUNING_ENABLEDThe model has periodic tuning enabled. Tuning can be disabled by calling the DisableModelPeriodicTuning method.

    ModelTrainingState, ModelTrainingStateArgs

    TrainingStateUnspecified
    TRAINING_STATE_UNSPECIFIEDUnspecified training state.
    Paused
    PAUSEDThe model training is paused.
    Training
    TRAININGThe model is training.
    ModelTrainingStateTrainingStateUnspecified
    TRAINING_STATE_UNSPECIFIEDUnspecified training state.
    ModelTrainingStatePaused
    PAUSEDThe model training is paused.
    ModelTrainingStateTraining
    TRAININGThe model is training.
    TrainingStateUnspecified
    TRAINING_STATE_UNSPECIFIEDUnspecified training state.
    Paused
    PAUSEDThe model training is paused.
    Training
    TRAININGThe model is training.
    TrainingStateUnspecified
    TRAINING_STATE_UNSPECIFIEDUnspecified training state.
    Paused
    PAUSEDThe model training is paused.
    Training
    TRAININGThe model is training.
    TRAINING_STATE_UNSPECIFIED
    TRAINING_STATE_UNSPECIFIEDUnspecified training state.
    PAUSED
    PAUSEDThe model training is paused.
    TRAINING
    TRAININGThe model is training.
    "TRAINING_STATE_UNSPECIFIED"
    TRAINING_STATE_UNSPECIFIEDUnspecified training state.
    "PAUSED"
    PAUSEDThe model training is paused.
    "TRAINING"
    TRAININGThe model is training.

    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