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'Amazon Web Services' Machine Learning Services

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R/personalize_interfaces.R

R/personalize_interfaces.R
In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

Defines functions update_recommender_output update_recommender_input update_metric_attribution_output update_metric_attribution_input update_dataset_output update_dataset_input update_campaign_output update_campaign_input untag_resource_output untag_resource_input tag_resource_output tag_resource_input stop_solution_version_creation_output stop_solution_version_creation_input stop_recommender_output stop_recommender_input start_recommender_output start_recommender_input list_tags_for_resource_output list_tags_for_resource_input list_solutions_output list_solutions_input list_solution_versions_output list_solution_versions_input list_schemas_output list_schemas_input list_recommenders_output list_recommenders_input list_recipes_output list_recipes_input list_metric_attributions_output list_metric_attributions_input list_metric_attribution_metrics_output list_metric_attribution_metrics_input list_filters_output list_filters_input list_event_trackers_output list_event_trackers_input list_datasets_output list_datasets_input list_dataset_import_jobs_output list_dataset_import_jobs_input list_dataset_groups_output list_dataset_groups_input list_dataset_export_jobs_output list_dataset_export_jobs_input list_campaigns_output list_campaigns_input list_batch_segment_jobs_output list_batch_segment_jobs_input list_batch_inference_jobs_output list_batch_inference_jobs_input get_solution_metrics_output get_solution_metrics_input describe_solution_version_output describe_solution_version_input describe_solution_output describe_solution_input describe_schema_output describe_schema_input describe_recommender_output describe_recommender_input describe_recipe_output describe_recipe_input describe_metric_attribution_output describe_metric_attribution_input describe_filter_output describe_filter_input describe_feature_transformation_output describe_feature_transformation_input describe_event_tracker_output describe_event_tracker_input describe_dataset_import_job_output describe_dataset_import_job_input describe_dataset_group_output describe_dataset_group_input describe_dataset_export_job_output describe_dataset_export_job_input describe_dataset_output describe_dataset_input describe_campaign_output describe_campaign_input describe_batch_segment_job_output describe_batch_segment_job_input describe_batch_inference_job_output describe_batch_inference_job_input describe_algorithm_output describe_algorithm_input delete_solution_output delete_solution_input delete_schema_output delete_schema_input delete_recommender_output delete_recommender_input delete_metric_attribution_output delete_metric_attribution_input delete_filter_output delete_filter_input delete_event_tracker_output delete_event_tracker_input delete_dataset_group_output delete_dataset_group_input delete_dataset_output delete_dataset_input delete_campaign_output delete_campaign_input create_solution_version_output create_solution_version_input create_solution_output create_solution_input create_schema_output create_schema_input create_recommender_output create_recommender_input create_metric_attribution_output create_metric_attribution_input create_filter_output create_filter_input create_event_tracker_output create_event_tracker_input create_dataset_import_job_output create_dataset_import_job_input create_dataset_group_output create_dataset_group_input create_dataset_export_job_output create_dataset_export_job_input create_dataset_output create_dataset_input create_campaign_output create_campaign_input create_batch_segment_job_output create_batch_segment_job_input create_batch_inference_job_output create_batch_inference_job_input 

# This file is generated by make.paws. Please do not edit here.
#' @importFrom paws.common populate
#' @include personalize_service.R
NULL

.personalize$create_batch_inference_job_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(jobName = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string")), filterArn = structure(logical(0), tags = list(type = "string")), numResults = structure(logical(0), tags = list(type = "integer")), jobInput = structure(list(s3DataSource = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), jobOutput = structure(list(s3DataDestination = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), roleArn = structure(logical(0), tags = list(type = "string")), batchInferenceJobConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map"))), tags = list(type = "structure")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_batch_inference_job_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(batchInferenceJobArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_batch_segment_job_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(jobName = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string")), filterArn = structure(logical(0), tags = list(type = "string")), numResults = structure(logical(0), tags = list(type = "integer")), jobInput = structure(list(s3DataSource = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), jobOutput = structure(list(s3DataDestination = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), roleArn = structure(logical(0), tags = list(type = "string")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_batch_segment_job_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(batchSegmentJobArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_campaign_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string")), minProvisionedTPS = structure(logical(0), tags = list(type = "integer")), campaignConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map"))), tags = list(type = "structure")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_campaign_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(campaignArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_dataset_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), schemaArn = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), datasetType = structure(logical(0), tags = list(type = "string")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_dataset_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_dataset_export_job_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(jobName = structure(logical(0), tags = list(type = "string")), datasetArn = structure(logical(0), tags = list(type = "string")), ingestionMode = structure(logical(0), tags = list(type = "string")), roleArn = structure(logical(0), tags = list(type = "string")), jobOutput = structure(list(s3DataDestination = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_dataset_export_job_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetExportJobArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_dataset_group_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), roleArn = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string")), domain = structure(logical(0), tags = list(type = "string")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_dataset_group_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroupArn = structure(logical(0), tags = list(type = "string")), domain = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_dataset_import_job_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(jobName = structure(logical(0), tags = list(type = "string")), datasetArn = structure(logical(0), tags = list(type = "string")), dataSource = structure(list(dataLocation = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), roleArn = structure(logical(0), tags = list(type = "string")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), importMode = structure(logical(0), tags = list(type = "string")), publishAttributionMetricsToS3 = structure(logical(0), tags = list(type = "boolean"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_dataset_import_job_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetImportJobArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_event_tracker_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_event_tracker_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(eventTrackerArn = structure(logical(0), tags = list(type = "string")), trackingId = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_filter_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), filterExpression = structure(logical(0), tags = list(type = "string", sensitive = TRUE)), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_filter_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(filterArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_metric_attribution_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), metrics = structure(list(structure(list(eventType = structure(logical(0), tags = list(type = "string")), metricName = structure(logical(0), tags = list(type = "string")), expression = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), metricsOutputConfig = structure(list(s3DataDestination = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), roleArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_metric_attribution_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(metricAttributionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_recommender_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), recipeArn = structure(logical(0), tags = list(type = "string")), recommenderConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), minRecommendationRequestsPerSecond = structure(logical(0), tags = list(type = "integer")), trainingDataConfig = structure(list(excludedDatasetColumns = structure(list(structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_recommender_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenderArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_schema_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), schema = structure(logical(0), tags = list(type = "string")), domain = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_schema_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(schemaArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_solution_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), performHPO = structure(logical(0), tags = list(type = "boolean")), performAutoML = structure(logical(0), tags = list(type = "boolean")), recipeArn = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), eventType = structure(logical(0), tags = list(type = "string")), solutionConfig = structure(list(eventValueThreshold = structure(logical(0), tags = list(type = "string")), hpoConfig = structure(list(hpoObjective = structure(list(type = structure(logical(0), tags = list(type = "string")), metricName = structure(logical(0), tags = list(type = "string")), metricRegex = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), hpoResourceConfig = structure(list(maxNumberOfTrainingJobs = structure(logical(0), tags = list(type = "string")), maxParallelTrainingJobs = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), algorithmHyperParameterRanges = structure(list(integerHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), minValue = structure(logical(0), tags = list(type = "integer")), maxValue = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))), tags = list(type = "list")), continuousHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), minValue = structure(logical(0), tags = list(type = "double")), maxValue = structure(logical(0), tags = list(type = "double"))), tags = list(type = "structure"))), tags = list(type = "list")), categoricalHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), values = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))), tags = list(type = "structure")), algorithmHyperParameters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), featureTransformationParameters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), autoMLConfig = structure(list(metricName = structure(logical(0), tags = list(type = "string")), recipeList = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "structure")), optimizationObjective = structure(list(itemAttribute = structure(logical(0), tags = list(type = "string")), objectiveSensitivity = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), trainingDataConfig = structure(list(excludedDatasetColumns = structure(list(structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_solution_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_solution_version_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(name = structure(logical(0), tags = list(type = "string")), solutionArn = structure(logical(0), tags = list(type = "string")), trainingMode = structure(logical(0), tags = list(type = "string")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$create_solution_version_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_campaign_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(campaignArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_campaign_output <- function(...) {
  list()
}

.personalize$delete_dataset_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_dataset_output <- function(...) {
  list()
}

.personalize$delete_dataset_group_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroupArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_dataset_group_output <- function(...) {
  list()
}

.personalize$delete_event_tracker_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(eventTrackerArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_event_tracker_output <- function(...) {
  list()
}

.personalize$delete_filter_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(filterArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_filter_output <- function(...) {
  list()
}

.personalize$delete_metric_attribution_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(metricAttributionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_metric_attribution_output <- function(...) {
  list()
}

.personalize$delete_recommender_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenderArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_recommender_output <- function(...) {
  list()
}

.personalize$delete_schema_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(schemaArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_schema_output <- function(...) {
  list()
}

.personalize$delete_solution_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$delete_solution_output <- function(...) {
  list()
}

.personalize$describe_algorithm_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(algorithmArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_algorithm_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(algorithm = structure(list(name = structure(logical(0), tags = list(type = "string")), algorithmArn = structure(logical(0), tags = list(type = "string")), algorithmImage = structure(list(name = structure(logical(0), tags = list(type = "string")), dockerURI = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), defaultHyperParameters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), defaultHyperParameterRanges = structure(list(integerHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), minValue = structure(logical(0), tags = list(type = "integer")), maxValue = structure(logical(0), tags = list(type = "integer")), isTunable = structure(logical(0), tags = list(type = "boolean"))), tags = list(type = "structure"))), tags = list(type = "list")), continuousHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), minValue = structure(logical(0), tags = list(type = "double")), maxValue = structure(logical(0), tags = list(type = "double")), isTunable = structure(logical(0), tags = list(type = "boolean"))), tags = list(type = "structure"))), tags = list(type = "list")), categoricalHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), values = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list")), isTunable = structure(logical(0), tags = list(type = "boolean"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure")), defaultResourceConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), trainingInputMode = structure(logical(0), tags = list(type = "string")), roleArn = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_batch_inference_job_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(batchInferenceJobArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_batch_inference_job_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(batchInferenceJob = structure(list(jobName = structure(logical(0), tags = list(type = "string")), batchInferenceJobArn = structure(logical(0), tags = list(type = "string")), filterArn = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string")), numResults = structure(logical(0), tags = list(type = "integer")), jobInput = structure(list(s3DataSource = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), jobOutput = structure(list(s3DataDestination = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), batchInferenceJobConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map"))), tags = list(type = "structure")), roleArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_batch_segment_job_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(batchSegmentJobArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_batch_segment_job_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(batchSegmentJob = structure(list(jobName = structure(logical(0), tags = list(type = "string")), batchSegmentJobArn = structure(logical(0), tags = list(type = "string")), filterArn = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string")), numResults = structure(logical(0), tags = list(type = "integer")), jobInput = structure(list(s3DataSource = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), jobOutput = structure(list(s3DataDestination = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), roleArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_campaign_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(campaignArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_campaign_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(campaign = structure(list(name = structure(logical(0), tags = list(type = "string")), campaignArn = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string")), minProvisionedTPS = structure(logical(0), tags = list(type = "integer")), campaignConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map"))), tags = list(type = "structure")), status = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), latestCampaignUpdate = structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string")), minProvisionedTPS = structure(logical(0), tags = list(type = "integer")), campaignConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map"))), tags = list(type = "structure")), status = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_dataset_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_dataset_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(dataset = structure(list(name = structure(logical(0), tags = list(type = "string")), datasetArn = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), datasetType = structure(logical(0), tags = list(type = "string")), schemaArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), latestDatasetUpdate = structure(list(schemaArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_dataset_export_job_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetExportJobArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_dataset_export_job_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetExportJob = structure(list(jobName = structure(logical(0), tags = list(type = "string")), datasetExportJobArn = structure(logical(0), tags = list(type = "string")), datasetArn = structure(logical(0), tags = list(type = "string")), ingestionMode = structure(logical(0), tags = list(type = "string")), roleArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), jobOutput = structure(list(s3DataDestination = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_dataset_group_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroupArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_dataset_group_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroup = structure(list(name = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), roleArn = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string")), domain = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_dataset_import_job_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetImportJobArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_dataset_import_job_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetImportJob = structure(list(jobName = structure(logical(0), tags = list(type = "string")), datasetImportJobArn = structure(logical(0), tags = list(type = "string")), datasetArn = structure(logical(0), tags = list(type = "string")), dataSource = structure(list(dataLocation = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), roleArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string")), importMode = structure(logical(0), tags = list(type = "string")), publishAttributionMetricsToS3 = structure(logical(0), tags = list(type = "boolean"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_event_tracker_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(eventTrackerArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_event_tracker_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(eventTracker = structure(list(name = structure(logical(0), tags = list(type = "string")), eventTrackerArn = structure(logical(0), tags = list(type = "string")), accountId = structure(logical(0), tags = list(type = "string")), trackingId = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_feature_transformation_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(featureTransformationArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_feature_transformation_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(featureTransformation = structure(list(name = structure(logical(0), tags = list(type = "string")), featureTransformationArn = structure(logical(0), tags = list(type = "string")), defaultParameters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), status = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_filter_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(filterArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_filter_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(filter = structure(list(name = structure(logical(0), tags = list(type = "string")), filterArn = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string")), filterExpression = structure(logical(0), tags = list(type = "string", sensitive = TRUE)), status = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_metric_attribution_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(metricAttributionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_metric_attribution_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(metricAttribution = structure(list(name = structure(logical(0), tags = list(type = "string")), metricAttributionArn = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), metricsOutputConfig = structure(list(s3DataDestination = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), roleArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_recipe_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recipeArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_recipe_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recipe = structure(list(name = structure(logical(0), tags = list(type = "string")), recipeArn = structure(logical(0), tags = list(type = "string")), algorithmArn = structure(logical(0), tags = list(type = "string")), featureTransformationArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), description = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), recipeType = structure(logical(0), tags = list(type = "string")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_recommender_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenderArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_recommender_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommender = structure(list(recommenderArn = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), name = structure(logical(0), tags = list(type = "string")), recipeArn = structure(logical(0), tags = list(type = "string")), recommenderConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), minRecommendationRequestsPerSecond = structure(logical(0), tags = list(type = "integer")), trainingDataConfig = structure(list(excludedDatasetColumns = structure(list(structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), status = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string")), latestRecommenderUpdate = structure(list(recommenderConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), minRecommendationRequestsPerSecond = structure(logical(0), tags = list(type = "integer")), trainingDataConfig = structure(list(excludedDatasetColumns = structure(list(structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), status = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), modelMetrics = structure(list(structure(logical(0), tags = list(type = "double"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_schema_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(schemaArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_schema_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(schema = structure(list(name = structure(logical(0), tags = list(type = "string")), schemaArn = structure(logical(0), tags = list(type = "string")), schema = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), domain = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_solution_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_solution_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solution = structure(list(name = structure(logical(0), tags = list(type = "string")), solutionArn = structure(logical(0), tags = list(type = "string")), performHPO = structure(logical(0), tags = list(type = "boolean")), performAutoML = structure(logical(0), tags = list(type = "boolean")), recipeArn = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), eventType = structure(logical(0), tags = list(type = "string")), solutionConfig = structure(list(eventValueThreshold = structure(logical(0), tags = list(type = "string")), hpoConfig = structure(list(hpoObjective = structure(list(type = structure(logical(0), tags = list(type = "string")), metricName = structure(logical(0), tags = list(type = "string")), metricRegex = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), hpoResourceConfig = structure(list(maxNumberOfTrainingJobs = structure(logical(0), tags = list(type = "string")), maxParallelTrainingJobs = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), algorithmHyperParameterRanges = structure(list(integerHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), minValue = structure(logical(0), tags = list(type = "integer")), maxValue = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))), tags = list(type = "list")), continuousHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), minValue = structure(logical(0), tags = list(type = "double")), maxValue = structure(logical(0), tags = list(type = "double"))), tags = list(type = "structure"))), tags = list(type = "list")), categoricalHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), values = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))), tags = list(type = "structure")), algorithmHyperParameters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), featureTransformationParameters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), autoMLConfig = structure(list(metricName = structure(logical(0), tags = list(type = "string")), recipeList = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "structure")), optimizationObjective = structure(list(itemAttribute = structure(logical(0), tags = list(type = "string")), objectiveSensitivity = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), trainingDataConfig = structure(list(excludedDatasetColumns = structure(list(structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure")), autoMLResult = structure(list(bestRecipeArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), latestSolutionVersion = structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_solution_version_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$describe_solution_version_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionVersion = structure(list(name = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string")), solutionArn = structure(logical(0), tags = list(type = "string")), performHPO = structure(logical(0), tags = list(type = "boolean")), performAutoML = structure(logical(0), tags = list(type = "boolean")), recipeArn = structure(logical(0), tags = list(type = "string")), eventType = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), solutionConfig = structure(list(eventValueThreshold = structure(logical(0), tags = list(type = "string")), hpoConfig = structure(list(hpoObjective = structure(list(type = structure(logical(0), tags = list(type = "string")), metricName = structure(logical(0), tags = list(type = "string")), metricRegex = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), hpoResourceConfig = structure(list(maxNumberOfTrainingJobs = structure(logical(0), tags = list(type = "string")), maxParallelTrainingJobs = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), algorithmHyperParameterRanges = structure(list(integerHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), minValue = structure(logical(0), tags = list(type = "integer")), maxValue = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))), tags = list(type = "list")), continuousHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), minValue = structure(logical(0), tags = list(type = "double")), maxValue = structure(logical(0), tags = list(type = "double"))), tags = list(type = "structure"))), tags = list(type = "list")), categoricalHyperParameterRanges = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), values = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))), tags = list(type = "structure")), algorithmHyperParameters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), featureTransformationParameters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), autoMLConfig = structure(list(metricName = structure(logical(0), tags = list(type = "string")), recipeList = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "structure")), optimizationObjective = structure(list(itemAttribute = structure(logical(0), tags = list(type = "string")), objectiveSensitivity = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), trainingDataConfig = structure(list(excludedDatasetColumns = structure(list(structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure")), trainingHours = structure(logical(0), tags = list(type = "double")), trainingMode = structure(logical(0), tags = list(type = "string")), tunedHPOParams = structure(list(algorithmHyperParameters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map"))), tags = list(type = "structure")), status = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$get_solution_metrics_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$get_solution_metrics_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string")), metrics = structure(list(structure(logical(0), tags = list(type = "double"))), tags = list(type = "map"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_batch_inference_jobs_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_batch_inference_jobs_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(batchInferenceJobs = structure(list(structure(list(batchInferenceJobArn = structure(logical(0), tags = list(type = "string")), jobName = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_batch_segment_jobs_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_batch_segment_jobs_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(batchSegmentJobs = structure(list(structure(list(batchSegmentJobArn = structure(logical(0), tags = list(type = "string")), jobName = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_campaigns_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_campaigns_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(campaigns = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), campaignArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_dataset_export_jobs_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_dataset_export_jobs_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetExportJobs = structure(list(structure(list(datasetExportJobArn = structure(logical(0), tags = list(type = "string")), jobName = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_dataset_groups_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_dataset_groups_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroups = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string")), domain = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_dataset_import_jobs_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_dataset_import_jobs_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetImportJobs = structure(list(structure(list(datasetImportJobArn = structure(logical(0), tags = list(type = "string")), jobName = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string")), importMode = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_datasets_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroupArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_datasets_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasets = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), datasetArn = structure(logical(0), tags = list(type = "string")), datasetType = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_event_trackers_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroupArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_event_trackers_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(eventTrackers = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), eventTrackerArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_filters_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroupArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_filters_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(Filters = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), filterArn = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), failureReason = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_metric_attribution_metrics_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(metricAttributionArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_metric_attribution_metrics_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(metrics = structure(list(structure(list(eventType = structure(logical(0), tags = list(type = "string")), metricName = structure(logical(0), tags = list(type = "string")), expression = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_metric_attributions_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroupArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_metric_attributions_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(metricAttributions = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), metricAttributionArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_recipes_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recipeProvider = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer")), domain = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_recipes_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recipes = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), recipeArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), domain = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_recommenders_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroupArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_recommenders_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenders = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), recommenderArn = structure(logical(0), tags = list(type = "string")), datasetGroupArn = structure(logical(0), tags = list(type = "string")), recipeArn = structure(logical(0), tags = list(type = "string")), recommenderConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), minRecommendationRequestsPerSecond = structure(logical(0), tags = list(type = "integer")), trainingDataConfig = structure(list(excludedDatasetColumns = structure(list(structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_schemas_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_schemas_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(schemas = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), schemaArn = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), domain = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_solution_versions_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_solution_versions_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionVersions = structure(list(structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), failureReason = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_solutions_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetGroupArn = structure(logical(0), tags = list(type = "string")), nextToken = structure(logical(0), tags = list(type = "string")), maxResults = structure(logical(0), tags = list(type = "integer"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_solutions_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutions = structure(list(structure(list(name = structure(logical(0), tags = list(type = "string")), solutionArn = structure(logical(0), tags = list(type = "string")), status = structure(logical(0), tags = list(type = "string")), creationDateTime = structure(logical(0), tags = list(type = "timestamp")), lastUpdatedDateTime = structure(logical(0), tags = list(type = "timestamp")), recipeArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), nextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_tags_for_resource_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(resourceArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$list_tags_for_resource_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$start_recommender_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenderArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$start_recommender_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenderArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$stop_recommender_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenderArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$stop_recommender_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenderArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$stop_solution_version_creation_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(solutionVersionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$stop_solution_version_creation_output <- function(...) {
  list()
}

.personalize$tag_resource_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(resourceArn = structure(logical(0), tags = list(type = "string")), tags = structure(list(structure(list(tagKey = structure(logical(0), tags = list(type = "string")), tagValue = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$tag_resource_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$untag_resource_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(resourceArn = structure(logical(0), tags = list(type = "string")), tagKeys = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$untag_resource_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$update_campaign_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(campaignArn = structure(logical(0), tags = list(type = "string")), solutionVersionArn = structure(logical(0), tags = list(type = "string")), minProvisionedTPS = structure(logical(0), tags = list(type = "integer")), campaignConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$update_campaign_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(campaignArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$update_dataset_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetArn = structure(logical(0), tags = list(type = "string")), schemaArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$update_dataset_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(datasetArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$update_metric_attribution_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(addMetrics = structure(list(structure(list(eventType = structure(logical(0), tags = list(type = "string")), metricName = structure(logical(0), tags = list(type = "string")), expression = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))), tags = list(type = "list")), removeMetrics = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list")), metricsOutputConfig = structure(list(s3DataDestination = structure(list(path = structure(logical(0), tags = list(type = "string")), kmsKeyArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), roleArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure")), metricAttributionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$update_metric_attribution_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(metricAttributionArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$update_recommender_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenderArn = structure(logical(0), tags = list(type = "string")), recommenderConfig = structure(list(itemExplorationConfig = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), minRecommendationRequestsPerSecond = structure(logical(0), tags = list(type = "integer")), trainingDataConfig = structure(list(excludedDatasetColumns = structure(list(structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.personalize$update_recommender_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(recommenderArn = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

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paws.machine.learning documentation built on Sept. 12, 2023, 1:14 a.m.

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