ModelArgs constructor

const ModelArgs({ required Input<String> catalogId, required Input<String> displayName, Input<bool>? dryRun, Input<ModelFilteringOption>? filteringOption, Input<String>? location, Input<GoogleCloudRetailV2ModelModelFeaturesConfig>? modelFeaturesConfig, Input<String>? name, Input<String>? optimizationObjective, Input<ModelPeriodicTuningState>? periodicTuningState, Input<String>? project, Input<ModelTrainingState>? trainingState, required Input<String> type, })

Creates a new ModelArgs. catalogId Required. displayName 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. dryRun Optional. Whether to run a dry run to validate the request (without actually creating the model). filteringOption Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model. location Optional. modelFeaturesConfig Optional. Additional model features config. name 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 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 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 Optional. trainingState 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. type 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.

Implementation

const ModelArgs({
  required this.catalogId,
  required this.displayName,
  this.dryRun,
  this.filteringOption,
  this.location,
  this.modelFeaturesConfig,
  this.name,
  this.optimizationObjective,
  this.periodicTuningState,
  this.project,
  this.trainingState,
  required this.type,
});