We recommend new projects start with resources from the AWS provider.
aws-native.personalize.Solution
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We recommend new projects start with resources from the AWS provider.
Resource schema for AWS::Personalize::Solution.
Example Usage
Example
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AwsNative = Pulumi.AwsNative;
return await Deployment.RunAsync(() =>
{
var mySolution = new AwsNative.Personalize.Solution("mySolution", new()
{
Name = "my-solution-name",
DatasetGroupArn = "arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
RecipeArn = "arn:aws:personalize:::recipe/aws-user-personalization",
SolutionConfig = new AwsNative.Personalize.Inputs.SolutionConfigArgs
{
EventValueThreshold = ".05",
},
});
});
package main
import (
"github.com/pulumi/pulumi-aws-native/sdk/go/aws/personalize"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := personalize.NewSolution(ctx, "mySolution", &personalize.SolutionArgs{
Name: pulumi.String("my-solution-name"),
DatasetGroupArn: pulumi.String("arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name"),
RecipeArn: pulumi.String("arn:aws:personalize:::recipe/aws-user-personalization"),
SolutionConfig: &personalize.SolutionConfigArgs{
EventValueThreshold: pulumi.String(".05"),
},
})
if err != nil {
return err
}
return nil
})
}
Coming soon!
import pulumi
import pulumi_aws_native as aws_native
my_solution = aws_native.personalize.Solution("mySolution",
name="my-solution-name",
dataset_group_arn="arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
recipe_arn="arn:aws:personalize:::recipe/aws-user-personalization",
solution_config={
"event_value_threshold": ".05",
})
import * as pulumi from "@pulumi/pulumi";
import * as aws_native from "@pulumi/aws-native";
const mySolution = new aws_native.personalize.Solution("mySolution", {
name: "my-solution-name",
datasetGroupArn: "arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
recipeArn: "arn:aws:personalize:::recipe/aws-user-personalization",
solutionConfig: {
eventValueThreshold: ".05",
},
});
Coming soon!
Example
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AwsNative = Pulumi.AwsNative;
return await Deployment.RunAsync(() =>
{
var mySolution = new AwsNative.Personalize.Solution("mySolution", new()
{
Name = "my-solution-name",
DatasetGroupArn = "arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
RecipeArn = "arn:aws:personalize:::recipe/aws-user-personalization",
SolutionConfig = new AwsNative.Personalize.Inputs.SolutionConfigArgs
{
EventValueThreshold = ".05",
},
});
});
package main
import (
"github.com/pulumi/pulumi-aws-native/sdk/go/aws/personalize"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := personalize.NewSolution(ctx, "mySolution", &personalize.SolutionArgs{
Name: pulumi.String("my-solution-name"),
DatasetGroupArn: pulumi.String("arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name"),
RecipeArn: pulumi.String("arn:aws:personalize:::recipe/aws-user-personalization"),
SolutionConfig: &personalize.SolutionConfigArgs{
EventValueThreshold: pulumi.String(".05"),
},
})
if err != nil {
return err
}
return nil
})
}
Coming soon!
import pulumi
import pulumi_aws_native as aws_native
my_solution = aws_native.personalize.Solution("mySolution",
name="my-solution-name",
dataset_group_arn="arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
recipe_arn="arn:aws:personalize:::recipe/aws-user-personalization",
solution_config={
"event_value_threshold": ".05",
})
import * as pulumi from "@pulumi/pulumi";
import * as aws_native from "@pulumi/aws-native";
const mySolution = new aws_native.personalize.Solution("mySolution", {
name: "my-solution-name",
datasetGroupArn: "arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
recipeArn: "arn:aws:personalize:::recipe/aws-user-personalization",
solutionConfig: {
eventValueThreshold: ".05",
},
});
Coming soon!
Create Solution Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new Solution(name: string, args: SolutionArgs, opts?: CustomResourceOptions);
@overload
def Solution(resource_name: str,
args: SolutionArgs,
opts: Optional[ResourceOptions] = None)
@overload
def Solution(resource_name: str,
opts: Optional[ResourceOptions] = None,
dataset_group_arn: Optional[str] = None,
event_type: Optional[str] = None,
name: Optional[str] = None,
perform_auto_ml: Optional[bool] = None,
perform_hpo: Optional[bool] = None,
recipe_arn: Optional[str] = None,
solution_config: Optional[SolutionConfigArgs] = None)
func NewSolution(ctx *Context, name string, args SolutionArgs, opts ...ResourceOption) (*Solution, error)
public Solution(string name, SolutionArgs args, CustomResourceOptions? opts = null)
public Solution(String name, SolutionArgs args)
public Solution(String name, SolutionArgs args, CustomResourceOptions options)
type: aws-native:personalize:Solution
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args SolutionArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args SolutionArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args SolutionArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args SolutionArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args SolutionArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Solution Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
The Solution resource accepts the following input properties:
- Dataset
Group stringArn - The ARN of the dataset group that provides the training data.
- Event
Type string - When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
- Name string
- The name for the solution
- Perform
Auto boolMl - Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
- Perform
Hpo bool - Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
- Recipe
Arn string - The ARN of the recipe to use for model training. Only specified when performAutoML is false.
- Solution
Config Pulumi.Aws Native. Personalize. Inputs. Solution Config - Describes the configuration properties for the solution.
- Dataset
Group stringArn - The ARN of the dataset group that provides the training data.
- Event
Type string - When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
- Name string
- The name for the solution
- Perform
Auto boolMl - Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
- Perform
Hpo bool - Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
- Recipe
Arn string - The ARN of the recipe to use for model training. Only specified when performAutoML is false.
- Solution
Config SolutionConfig Args - Describes the configuration properties for the solution.
- dataset
Group StringArn - The ARN of the dataset group that provides the training data.
- event
Type String - When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
- name String
- The name for the solution
- perform
Auto BooleanMl - Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
- perform
Hpo Boolean - Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
- recipe
Arn String - The ARN of the recipe to use for model training. Only specified when performAutoML is false.
- solution
Config SolutionConfig - Describes the configuration properties for the solution.
- dataset
Group stringArn - The ARN of the dataset group that provides the training data.
- event
Type string - When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
- name string
- The name for the solution
- perform
Auto booleanMl - Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
- perform
Hpo boolean - Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
- recipe
Arn string - The ARN of the recipe to use for model training. Only specified when performAutoML is false.
- solution
Config SolutionConfig - Describes the configuration properties for the solution.
- dataset_
group_ strarn - The ARN of the dataset group that provides the training data.
- event_
type str - When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
- name str
- The name for the solution
- perform_
auto_ boolml - Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
- perform_
hpo bool - Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
- recipe_
arn str - The ARN of the recipe to use for model training. Only specified when performAutoML is false.
- solution_
config SolutionConfig Args - Describes the configuration properties for the solution.
- dataset
Group StringArn - The ARN of the dataset group that provides the training data.
- event
Type String - When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
- name String
- The name for the solution
- perform
Auto BooleanMl - Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
- perform
Hpo Boolean - Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
- recipe
Arn String - The ARN of the recipe to use for model training. Only specified when performAutoML is false.
- solution
Config Property Map - Describes the configuration properties for the solution.
Outputs
All input properties are implicitly available as output properties. Additionally, the Solution resource produces the following output properties:
- Id string
- The provider-assigned unique ID for this managed resource.
- Solution
Arn string - The Amazon Resource Name (ARN) of the solution.
- Id string
- The provider-assigned unique ID for this managed resource.
- Solution
Arn string - The Amazon Resource Name (ARN) of the solution.
- id String
- The provider-assigned unique ID for this managed resource.
- solution
Arn String - The Amazon Resource Name (ARN) of the solution.
- id string
- The provider-assigned unique ID for this managed resource.
- solution
Arn string - The Amazon Resource Name (ARN) of the solution.
- id str
- The provider-assigned unique ID for this managed resource.
- solution_
arn str - The Amazon Resource Name (ARN) of the solution.
- id String
- The provider-assigned unique ID for this managed resource.
- solution
Arn String - The Amazon Resource Name (ARN) of the solution.
Supporting Types
SolutionCategoricalHyperParameterRange, SolutionCategoricalHyperParameterRangeArgs
SolutionConfig, SolutionConfigArgs
- Algorithm
Hyper Dictionary<string, string>Parameters - Lists the hyperparameter names and ranges.
- Auto
Ml Pulumi.Config Aws Native. Personalize. Inputs. Solution Config Auto Ml Config Properties - The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
- Event
Value stringThreshold - Only events with a value greater than or equal to this threshold are used for training a model.
- Feature
Transformation Dictionary<string, string>Parameters - Lists the feature transformation parameters.
- Hpo
Config Pulumi.Aws Native. Personalize. Inputs. Solution Config Hpo Config Properties - Describes the properties for hyperparameter optimization (HPO)
- Algorithm
Hyper map[string]stringParameters - Lists the hyperparameter names and ranges.
- Auto
Ml SolutionConfig Config Auto Ml Config Properties - The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
- Event
Value stringThreshold - Only events with a value greater than or equal to this threshold are used for training a model.
- Feature
Transformation map[string]stringParameters - Lists the feature transformation parameters.
- Hpo
Config SolutionConfig Hpo Config Properties - Describes the properties for hyperparameter optimization (HPO)
- algorithm
Hyper Map<String,String>Parameters - Lists the hyperparameter names and ranges.
- auto
Ml SolutionConfig Config Auto Ml Config Properties - The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
- event
Value StringThreshold - Only events with a value greater than or equal to this threshold are used for training a model.
- feature
Transformation Map<String,String>Parameters - Lists the feature transformation parameters.
- hpo
Config SolutionConfig Hpo Config Properties - Describes the properties for hyperparameter optimization (HPO)
- algorithm
Hyper {[key: string]: string}Parameters - Lists the hyperparameter names and ranges.
- auto
Ml SolutionConfig Config Auto Ml Config Properties - The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
- event
Value stringThreshold - Only events with a value greater than or equal to this threshold are used for training a model.
- feature
Transformation {[key: string]: string}Parameters - Lists the feature transformation parameters.
- hpo
Config SolutionConfig Hpo Config Properties - Describes the properties for hyperparameter optimization (HPO)
- algorithm_
hyper_ Mapping[str, str]parameters - Lists the hyperparameter names and ranges.
- auto_
ml_ Solutionconfig Config Auto Ml Config Properties - The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
- event_
value_ strthreshold - Only events with a value greater than or equal to this threshold are used for training a model.
- feature_
transformation_ Mapping[str, str]parameters - Lists the feature transformation parameters.
- hpo_
config SolutionConfig Hpo Config Properties - Describes the properties for hyperparameter optimization (HPO)
- algorithm
Hyper Map<String>Parameters - Lists the hyperparameter names and ranges.
- auto
Ml Property MapConfig - The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
- event
Value StringThreshold - Only events with a value greater than or equal to this threshold are used for training a model.
- feature
Transformation Map<String>Parameters - Lists the feature transformation parameters.
- hpo
Config Property Map - Describes the properties for hyperparameter optimization (HPO)
SolutionConfigAutoMlConfigProperties, SolutionConfigAutoMlConfigPropertiesArgs
- Metric
Name string - The metric to optimize.
- Recipe
List List<string> - The list of candidate recipes.
- Metric
Name string - The metric to optimize.
- Recipe
List []string - The list of candidate recipes.
- metric
Name String - The metric to optimize.
- recipe
List List<String> - The list of candidate recipes.
- metric
Name string - The metric to optimize.
- recipe
List string[] - The list of candidate recipes.
- metric_
name str - The metric to optimize.
- recipe_
list Sequence[str] - The list of candidate recipes.
- metric
Name String - The metric to optimize.
- recipe
List List<String> - The list of candidate recipes.
SolutionConfigHpoConfigProperties, SolutionConfigHpoConfigPropertiesArgs
- Algorithm
Hyper Pulumi.Parameter Ranges Aws Native. Personalize. Inputs. Solution Config Hpo Config Properties Algorithm Hyper Parameter Ranges Properties - The hyperparameters and their allowable ranges
- Hpo
Objective Pulumi.Aws Native. Personalize. Inputs. Solution Config Hpo Config Properties Hpo Objective Properties - The metric to optimize during HPO.
- Hpo
Resource Pulumi.Config Aws Native. Personalize. Inputs. Solution Config Hpo Config Properties Hpo Resource Config Properties - Describes the resource configuration for hyperparameter optimization (HPO).
- Algorithm
Hyper SolutionParameter Ranges Config Hpo Config Properties Algorithm Hyper Parameter Ranges Properties - The hyperparameters and their allowable ranges
- Hpo
Objective SolutionConfig Hpo Config Properties Hpo Objective Properties - The metric to optimize during HPO.
- Hpo
Resource SolutionConfig Config Hpo Config Properties Hpo Resource Config Properties - Describes the resource configuration for hyperparameter optimization (HPO).
- algorithm
Hyper SolutionParameter Ranges Config Hpo Config Properties Algorithm Hyper Parameter Ranges Properties - The hyperparameters and their allowable ranges
- hpo
Objective SolutionConfig Hpo Config Properties Hpo Objective Properties - The metric to optimize during HPO.
- hpo
Resource SolutionConfig Config Hpo Config Properties Hpo Resource Config Properties - Describes the resource configuration for hyperparameter optimization (HPO).
- algorithm
Hyper SolutionParameter Ranges Config Hpo Config Properties Algorithm Hyper Parameter Ranges Properties - The hyperparameters and their allowable ranges
- hpo
Objective SolutionConfig Hpo Config Properties Hpo Objective Properties - The metric to optimize during HPO.
- hpo
Resource SolutionConfig Config Hpo Config Properties Hpo Resource Config Properties - Describes the resource configuration for hyperparameter optimization (HPO).
- algorithm_
hyper_ Solutionparameter_ ranges Config Hpo Config Properties Algorithm Hyper Parameter Ranges Properties - The hyperparameters and their allowable ranges
- hpo_
objective SolutionConfig Hpo Config Properties Hpo Objective Properties - The metric to optimize during HPO.
- hpo_
resource_ Solutionconfig Config Hpo Config Properties Hpo Resource Config Properties - Describes the resource configuration for hyperparameter optimization (HPO).
- algorithm
Hyper Property MapParameter Ranges - The hyperparameters and their allowable ranges
- hpo
Objective Property Map - The metric to optimize during HPO.
- hpo
Resource Property MapConfig - Describes the resource configuration for hyperparameter optimization (HPO).
SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesProperties, SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesPropertiesArgs
- Categorical
Hyper List<Pulumi.Parameter Ranges Aws Native. Personalize. Inputs. Solution Categorical Hyper Parameter Range> - The categorical hyperparameters and their ranges.
- Continuous
Hyper List<Pulumi.Parameter Ranges Aws Native. Personalize. Inputs. Solution Continuous Hyper Parameter Range> - The continuous hyperparameters and their ranges.
- Integer
Hyper List<Pulumi.Parameter Ranges Aws Native. Personalize. Inputs. Solution Integer Hyper Parameter Range> - The integer hyperparameters and their ranges.
- Categorical
Hyper []SolutionParameter Ranges Categorical Hyper Parameter Range - The categorical hyperparameters and their ranges.
- Continuous
Hyper []SolutionParameter Ranges Continuous Hyper Parameter Range - The continuous hyperparameters and their ranges.
- Integer
Hyper []SolutionParameter Ranges Integer Hyper Parameter Range - The integer hyperparameters and their ranges.
- categorical
Hyper List<SolutionParameter Ranges Categorical Hyper Parameter Range> - The categorical hyperparameters and their ranges.
- continuous
Hyper List<SolutionParameter Ranges Continuous Hyper Parameter Range> - The continuous hyperparameters and their ranges.
- integer
Hyper List<SolutionParameter Ranges Integer Hyper Parameter Range> - The integer hyperparameters and their ranges.
- categorical
Hyper SolutionParameter Ranges Categorical Hyper Parameter Range[] - The categorical hyperparameters and their ranges.
- continuous
Hyper SolutionParameter Ranges Continuous Hyper Parameter Range[] - The continuous hyperparameters and their ranges.
- integer
Hyper SolutionParameter Ranges Integer Hyper Parameter Range[] - The integer hyperparameters and their ranges.
- categorical_
hyper_ Sequence[Solutionparameter_ ranges Categorical Hyper Parameter Range] - The categorical hyperparameters and their ranges.
- continuous_
hyper_ Sequence[Solutionparameter_ ranges Continuous Hyper Parameter Range] - The continuous hyperparameters and their ranges.
- integer_
hyper_ Sequence[Solutionparameter_ ranges Integer Hyper Parameter Range] - The integer hyperparameters and their ranges.
- categorical
Hyper List<Property Map>Parameter Ranges - The categorical hyperparameters and their ranges.
- continuous
Hyper List<Property Map>Parameter Ranges - The continuous hyperparameters and their ranges.
- integer
Hyper List<Property Map>Parameter Ranges - The integer hyperparameters and their ranges.
SolutionConfigHpoConfigPropertiesHpoObjectiveProperties, SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesArgs
- Metric
Name string - The name of the metric
- Metric
Regex string - A regular expression for finding the metric in the training job logs.
- Type
Pulumi.
Aws Native. Personalize. Solution Config Hpo Config Properties Hpo Objective Properties Type - The type of the metric. Valid values are Maximize and Minimize.
- Metric
Name string - The name of the metric
- Metric
Regex string - A regular expression for finding the metric in the training job logs.
- Type
Solution
Config Hpo Config Properties Hpo Objective Properties Type - The type of the metric. Valid values are Maximize and Minimize.
- metric
Name String - The name of the metric
- metric
Regex String - A regular expression for finding the metric in the training job logs.
- type
Solution
Config Hpo Config Properties Hpo Objective Properties Type - The type of the metric. Valid values are Maximize and Minimize.
- metric
Name string - The name of the metric
- metric
Regex string - A regular expression for finding the metric in the training job logs.
- type
Solution
Config Hpo Config Properties Hpo Objective Properties Type - The type of the metric. Valid values are Maximize and Minimize.
- metric_
name str - The name of the metric
- metric_
regex str - A regular expression for finding the metric in the training job logs.
- type
Solution
Config Hpo Config Properties Hpo Objective Properties Type - The type of the metric. Valid values are Maximize and Minimize.
- metric
Name String - The name of the metric
- metric
Regex String - A regular expression for finding the metric in the training job logs.
- type "Maximize" | "Minimize"
- The type of the metric. Valid values are Maximize and Minimize.
SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType, SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesTypeArgs
- Maximize
- Maximize
- Minimize
- Minimize
- Solution
Config Hpo Config Properties Hpo Objective Properties Type Maximize - Maximize
- Solution
Config Hpo Config Properties Hpo Objective Properties Type Minimize - Minimize
- Maximize
- Maximize
- Minimize
- Minimize
- Maximize
- Maximize
- Minimize
- Minimize
- MAXIMIZE
- Maximize
- MINIMIZE
- Minimize
- "Maximize"
- Maximize
- "Minimize"
- Minimize
SolutionConfigHpoConfigPropertiesHpoResourceConfigProperties, SolutionConfigHpoConfigPropertiesHpoResourceConfigPropertiesArgs
- Max
Number stringOf Training Jobs - The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
- Max
Parallel stringTraining Jobs - The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
- Max
Number stringOf Training Jobs - The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
- Max
Parallel stringTraining Jobs - The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
- max
Number StringOf Training Jobs - The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
- max
Parallel StringTraining Jobs - The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
- max
Number stringOf Training Jobs - The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
- max
Parallel stringTraining Jobs - The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
- max_
number_ strof_ training_ jobs - The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
- max_
parallel_ strtraining_ jobs - The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
- max
Number StringOf Training Jobs - The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
- max
Parallel StringTraining Jobs - The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
SolutionContinuousHyperParameterRange, SolutionContinuousHyperParameterRangeArgs
SolutionIntegerHyperParameterRange, SolutionIntegerHyperParameterRangeArgs
Package Details
- Repository
- AWS Native pulumi/pulumi-aws-native
- License
- Apache-2.0
We recommend new projects start with resources from the AWS provider.