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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

google-native.retail/v2.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

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[GoogleCloudRetailV2ModelModelFeaturesConfigArgs] = 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/v2:Model
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

Parameters

name This property is required. string
The unique name of the resource.
args This property is required. ModelArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
resource_name This property is required. str
The unique name of the resource.
args This property is required. 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 This property is required. string
The unique name of the resource.
args This property is required. ModelArgs
The arguments to resource properties.
opts ResourceOption
Bag of options to control resource's behavior.
name This property is required. string
The unique name of the resource.
args This property is required. ModelArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
name This property is required. String
The unique name of the resource.
args This property is required. 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 examplemodelResourceResourceFromRetailv2 = new GoogleNative.Retail.V2.Model("examplemodelResourceResourceFromRetailv2", new()
{
    CatalogId = "string",
    DisplayName = "string",
    Type = "string",
    DryRun = false,
    FilteringOption = GoogleNative.Retail.V2.ModelFilteringOption.RecommendationsFilteringOptionUnspecified,
    Location = "string",
    ModelFeaturesConfig = new GoogleNative.Retail.V2.Inputs.GoogleCloudRetailV2ModelModelFeaturesConfigArgs
    {
        FrequentlyBoughtTogetherConfig = new GoogleNative.Retail.V2.Inputs.GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigArgs
        {
            ContextProductsType = GoogleNative.Retail.V2.GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType.ContextProductsTypeUnspecified,
        },
    },
    Name = "string",
    OptimizationObjective = "string",
    PeriodicTuningState = GoogleNative.Retail.V2.ModelPeriodicTuningState.PeriodicTuningStateUnspecified,
    Project = "string",
    TrainingState = GoogleNative.Retail.V2.ModelTrainingState.TrainingStateUnspecified,
});
Copy
example, err := retail.NewModel(ctx, "examplemodelResourceResourceFromRetailv2", &retail.ModelArgs{
	CatalogId:       pulumi.String("string"),
	DisplayName:     pulumi.String("string"),
	Type:            pulumi.String("string"),
	DryRun:          pulumi.Bool(false),
	FilteringOption: retail.ModelFilteringOptionRecommendationsFilteringOptionUnspecified,
	Location:        pulumi.String("string"),
	ModelFeaturesConfig: &retail.GoogleCloudRetailV2ModelModelFeaturesConfigArgs{
		FrequentlyBoughtTogetherConfig: &retail.GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigArgs{
			ContextProductsType: retail.GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeContextProductsTypeUnspecified,
		},
	},
	Name:                  pulumi.String("string"),
	OptimizationObjective: pulumi.String("string"),
	PeriodicTuningState:   retail.ModelPeriodicTuningStatePeriodicTuningStateUnspecified,
	Project:               pulumi.String("string"),
	TrainingState:         retail.ModelTrainingStateTrainingStateUnspecified,
})
Copy
var examplemodelResourceResourceFromRetailv2 = new Model("examplemodelResourceResourceFromRetailv2", ModelArgs.builder()
    .catalogId("string")
    .displayName("string")
    .type("string")
    .dryRun(false)
    .filteringOption("RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIED")
    .location("string")
    .modelFeaturesConfig(GoogleCloudRetailV2ModelModelFeaturesConfigArgs.builder()
        .frequentlyBoughtTogetherConfig(GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigArgs.builder()
            .contextProductsType("CONTEXT_PRODUCTS_TYPE_UNSPECIFIED")
            .build())
        .build())
    .name("string")
    .optimizationObjective("string")
    .periodicTuningState("PERIODIC_TUNING_STATE_UNSPECIFIED")
    .project("string")
    .trainingState("TRAINING_STATE_UNSPECIFIED")
    .build());
Copy
examplemodel_resource_resource_from_retailv2 = google_native.retail.v2.Model("examplemodelResourceResourceFromRetailv2",
    catalog_id="string",
    display_name="string",
    type="string",
    dry_run=False,
    filtering_option=google_native.retail.v2.ModelFilteringOption.RECOMMENDATIONS_FILTERING_OPTION_UNSPECIFIED,
    location="string",
    model_features_config={
        "frequently_bought_together_config": {
            "context_products_type": google_native.retail.v2.GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType.CONTEXT_PRODUCTS_TYPE_UNSPECIFIED,
        },
    },
    name="string",
    optimization_objective="string",
    periodic_tuning_state=google_native.retail.v2.ModelPeriodicTuningState.PERIODIC_TUNING_STATE_UNSPECIFIED,
    project="string",
    training_state=google_native.retail.v2.ModelTrainingState.TRAINING_STATE_UNSPECIFIED)
Copy
const examplemodelResourceResourceFromRetailv2 = new google_native.retail.v2.Model("examplemodelResourceResourceFromRetailv2", {
    catalogId: "string",
    displayName: "string",
    type: "string",
    dryRun: false,
    filteringOption: google_native.retail.v2.ModelFilteringOption.RecommendationsFilteringOptionUnspecified,
    location: "string",
    modelFeaturesConfig: {
        frequentlyBoughtTogetherConfig: {
            contextProductsType: google_native.retail.v2.GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType.ContextProductsTypeUnspecified,
        },
    },
    name: "string",
    optimizationObjective: "string",
    periodicTuningState: google_native.retail.v2.ModelPeriodicTuningState.PeriodicTuningStateUnspecified,
    project: "string",
    trainingState: google_native.retail.v2.ModelTrainingState.TrainingStateUnspecified,
});
Copy
type: google-native:retail/v2: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
Copy

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
This property is required.
Changes to this property will trigger replacement.
string
DisplayName This property is required. 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 This property is required. 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.V2.ModelFilteringOption
Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.
Location Changes to this property will trigger replacement. string
ModelFeaturesConfig Pulumi.GoogleNative.Retail.V2.Inputs.GoogleCloudRetailV2ModelModelFeaturesConfig
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.V2.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 Changes to this property will trigger replacement. string
TrainingState Pulumi.GoogleNative.Retail.V2.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
This property is required.
Changes to this property will trigger replacement.
string
DisplayName This property is required. 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 This property is required. 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 Changes to this property will trigger replacement. string
ModelFeaturesConfig GoogleCloudRetailV2ModelModelFeaturesConfigArgs
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 Changes to this property will trigger replacement. 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
This property is required.
Changes to this property will trigger replacement.
String
displayName This property is required. 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 This property is required. 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 Changes to this property will trigger replacement. String
modelFeaturesConfig GoogleCloudRetailV2ModelModelFeaturesConfig
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 Changes to this property will trigger replacement. 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
This property is required.
Changes to this property will trigger replacement.
string
displayName This property is required. 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 This property is required. 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 Changes to this property will trigger replacement. string
modelFeaturesConfig GoogleCloudRetailV2ModelModelFeaturesConfig
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 Changes to this property will trigger replacement. 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
This property is required.
Changes to this property will trigger replacement.
str
display_name This property is required. 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 This property is required. 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 Changes to this property will trigger replacement. str
model_features_config GoogleCloudRetailV2ModelModelFeaturesConfigArgs
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 Changes to this property will trigger replacement. 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
This property is required.
Changes to this property will trigger replacement.
String
displayName This property is required. 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 This property is required. 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 Changes to this property will trigger replacement. 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 Changes to this property will trigger replacement. 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.V2.Outputs.GoogleCloudRetailV2ModelServingConfigListResponse>
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 []GoogleCloudRetailV2ModelServingConfigListResponse
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<GoogleCloudRetailV2ModelServingConfigListResponse>
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 GoogleCloudRetailV2ModelServingConfigListResponse[]
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[GoogleCloudRetailV2ModelServingConfigListResponse]
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

GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfig
, GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigArgs

ContextProductsType Pulumi.GoogleNative.Retail.V2.GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
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 GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
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 GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
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 GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
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 GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
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.

GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsType
, GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeArgs

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.
GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeContextProductsTypeUnspecified
CONTEXT_PRODUCTS_TYPE_UNSPECIFIEDUnspecified default value, should never be explicitly set. Defaults to MULTIPLE_CONTEXT_PRODUCTS.
GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeSingleContextProduct
SINGLE_CONTEXT_PRODUCTUse only a single product as context for the recommendation. Typically used on pages like add-to-cart or product details.
GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigContextProductsTypeMultipleContextProducts
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.

GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigResponse
, GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigResponseArgs

ContextProductsType This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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.

GoogleCloudRetailV2ModelModelFeaturesConfig
, GoogleCloudRetailV2ModelModelFeaturesConfigArgs

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

GoogleCloudRetailV2ModelModelFeaturesConfigResponse
, GoogleCloudRetailV2ModelModelFeaturesConfigResponseArgs

FrequentlyBoughtTogetherConfig This property is required. GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigResponse
Additional configs for frequently-bought-together models.
frequentlyBoughtTogetherConfig This property is required. GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigResponse
Additional configs for frequently-bought-together models.
frequentlyBoughtTogetherConfig This property is required. GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigResponse
Additional configs for frequently-bought-together models.
frequently_bought_together_config This property is required. GoogleCloudRetailV2ModelFrequentlyBoughtTogetherFeaturesConfigResponse
Additional configs for frequently-bought-together models.
frequentlyBoughtTogetherConfig This property is required. Property Map
Additional configs for frequently-bought-together models.

GoogleCloudRetailV2ModelServingConfigListResponse
, GoogleCloudRetailV2ModelServingConfigListResponseArgs

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