Class Algorithm


  • public class Algorithm
    extends com.pulumi.resources.CustomResource
    Manages an AWS SageMaker AI Algorithm. ## Example Usage ### Basic Usage
     
     package generated_program;
     
     import com.pulumi.Context;
     import com.pulumi.Pulumi;
     import com.pulumi.core.Output;
     import com.pulumi.aws.sagemaker.Algorithm;
     import com.pulumi.aws.sagemaker.AlgorithmArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationTrainingChannelArgs;
     import java.util.ArrayList;
     import java.util.Arrays;
     import java.util.Map;
     import java.io.File;
     import java.nio.file.Files;
     import java.nio.file.Paths;
     
     public class App {
         public static void main(String[] args) {
             Pulumi.run(App::stack);
         }
     
         public static void stack(Context ctx) {
             var example = new Algorithm("example", AlgorithmArgs.builder()
                 .trainingSpecification(AlgorithmTrainingSpecificationArgs.builder()
                     .trainingChannels(AlgorithmTrainingSpecificationTrainingChannelArgs.builder()
                         .name("train")
                         .supportedContentTypes("text/csv")
                         .supportedInputModes("File")
                         .build())
                     .supportedTrainingInstanceTypes("ml.m5.large")
                     .trainingImage("123456789012.dkr.ecr.us-west-2.amazonaws.com/example-training:latest")
                     .build())
                 .algorithmName("example-algorithm")
                 .tags(Map.of("Environment", "test"))
                 .build());
     
         }
     }
     
     
    ### Training Specification
     
     package generated_program;
     
     import com.pulumi.Context;
     import com.pulumi.Pulumi;
     import com.pulumi.core.Output;
     import com.pulumi.aws.sagemaker.SagemakerFunctions;
     import com.pulumi.aws.sagemaker.inputs.GetPrebuiltEcrImageArgs;
     import com.pulumi.aws.sagemaker.Algorithm;
     import com.pulumi.aws.sagemaker.AlgorithmArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationMetricDefinitionArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedHyperParameterArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedHyperParameterRangeArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedHyperParameterRangeContinuousParameterRangeSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedHyperParameterRangeIntegerParameterRangeSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedHyperParameterRangeCategoricalParameterRangeSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedTuningJobObjectiveMetricArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationTrainingChannelArgs;
     import java.util.ArrayList;
     import java.util.Arrays;
     import java.util.Map;
     import java.io.File;
     import java.nio.file.Files;
     import java.nio.file.Paths;
     
     public class App {
         public static void main(String[] args) {
             Pulumi.run(App::stack);
         }
     
         public static void stack(Context ctx) {
             final var example = SagemakerFunctions.getPrebuiltEcrImage(GetPrebuiltEcrImageArgs.builder()
                 .repositoryName("linear-learner")
                 .imageTag("1")
                 .build());
     
             var exampleAlgorithm = new Algorithm("exampleAlgorithm", AlgorithmArgs.builder()
                 .trainingSpecification(AlgorithmTrainingSpecificationArgs.builder()
                     .metricDefinitions(AlgorithmTrainingSpecificationMetricDefinitionArgs.builder()
                         .name("train:loss")
                         .regex("loss=(.*?);")
                         .build())
                     .supportedHyperParameters(                
                         AlgorithmTrainingSpecificationSupportedHyperParameterArgs.builder()
                             .range(AlgorithmTrainingSpecificationSupportedHyperParameterRangeArgs.builder()
                                 .continuousParameterRangeSpecification(AlgorithmTrainingSpecificationSupportedHyperParameterRangeContinuousParameterRangeSpecificationArgs.builder()
                                     .minValue("0.1")
                                     .maxValue("0.9")
                                     .build())
                                 .build())
                             .defaultValue("0.5")
                             .description("Continuous learning rate")
                             .isRequired(true)
                             .isTunable(true)
                             .name("eta")
                             .type("Continuous")
                             .build(),
                         AlgorithmTrainingSpecificationSupportedHyperParameterArgs.builder()
                             .range(AlgorithmTrainingSpecificationSupportedHyperParameterRangeArgs.builder()
                                 .integerParameterRangeSpecification(AlgorithmTrainingSpecificationSupportedHyperParameterRangeIntegerParameterRangeSpecificationArgs.builder()
                                     .minValue("1")
                                     .maxValue("10")
                                     .build())
                                 .build())
                             .defaultValue("5")
                             .description("Maximum tree depth")
                             .isRequired(false)
                             .isTunable(true)
                             .name("max_depth")
                             .type("Integer")
                             .build(),
                         AlgorithmTrainingSpecificationSupportedHyperParameterArgs.builder()
                             .range(AlgorithmTrainingSpecificationSupportedHyperParameterRangeArgs.builder()
                                 .categoricalParameterRangeSpecification(AlgorithmTrainingSpecificationSupportedHyperParameterRangeCategoricalParameterRangeSpecificationArgs.builder()
                                     .values(                                
                                         "reg:squarederror",
                                         "binary:logistic")
                                     .build())
                                 .build())
                             .defaultValue("reg:squarederror")
                             .description("Objective function")
                             .isRequired(false)
                             .isTunable(false)
                             .name("objective")
                             .type("Categorical")
                             .build())
                     .supportedTuningJobObjectiveMetrics(AlgorithmTrainingSpecificationSupportedTuningJobObjectiveMetricArgs.builder()
                         .metricName("train:loss")
                         .type("Minimize")
                         .build())
                     .trainingChannels(                
                         AlgorithmTrainingSpecificationTrainingChannelArgs.builder()
                             .description("Training data channel")
                             .isRequired(true)
                             .name("train")
                             .supportedCompressionTypes(                        
                                 "None",
                                 "Gzip")
                             .supportedContentTypes("text/csv")
                             .supportedInputModes("File")
                             .build(),
                         AlgorithmTrainingSpecificationTrainingChannelArgs.builder()
                             .name("validation")
                             .supportedContentTypes("application/json")
                             .supportedInputModes("Pipe")
                             .build())
                     .supportedTrainingInstanceTypes(                
                         "ml.m5.large",
                         "ml.c5.xlarge")
                     .supportsDistributedTraining(true)
                     .trainingImage(example.registryPath())
                     .build())
                 .algorithmName("example-training-algorithm")
                 .build());
     
         }
     }
     
     
    ### Inference Specification
     
     package generated_program;
     
     import com.pulumi.Context;
     import com.pulumi.Pulumi;
     import com.pulumi.core.Output;
     import com.pulumi.aws.sagemaker.SagemakerFunctions;
     import com.pulumi.aws.sagemaker.inputs.GetPrebuiltEcrImageArgs;
     import com.pulumi.aws.sagemaker.Algorithm;
     import com.pulumi.aws.sagemaker.AlgorithmArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationTrainingChannelArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmInferenceSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmInferenceSpecificationContainerArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmInferenceSpecificationContainerBaseModelArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmInferenceSpecificationContainerModelInputArgs;
     import java.util.ArrayList;
     import java.util.Arrays;
     import java.util.Map;
     import java.io.File;
     import java.nio.file.Files;
     import java.nio.file.Paths;
     
     public class App {
         public static void main(String[] args) {
             Pulumi.run(App::stack);
         }
     
         public static void stack(Context ctx) {
             final var example = SagemakerFunctions.getPrebuiltEcrImage(GetPrebuiltEcrImageArgs.builder()
                 .repositoryName("linear-learner")
                 .imageTag("1")
                 .build());
     
             var exampleAlgorithm = new Algorithm("exampleAlgorithm", AlgorithmArgs.builder()
                 .trainingSpecification(AlgorithmTrainingSpecificationArgs.builder()
                     .trainingChannels(AlgorithmTrainingSpecificationTrainingChannelArgs.builder()
                         .name("train")
                         .supportedContentTypes("text/csv")
                         .supportedInputModes("File")
                         .build())
                     .supportedTrainingInstanceTypes("ml.m5.large")
                     .trainingImage(example.registryPath())
                     .build())
                 .inferenceSpecification(AlgorithmInferenceSpecificationArgs.builder()
                     .containers(AlgorithmInferenceSpecificationContainerArgs.builder()
                         .baseModel(AlgorithmInferenceSpecificationContainerBaseModelArgs.builder()
                             .hubContentName("basemodel")
                             .hubContentVersion("1.0.0")
                             .recipeName("recipe")
                             .build())
                         .modelInput(AlgorithmInferenceSpecificationContainerModelInputArgs.builder()
                             .dataInputConfig("{}")
                             .build())
                         .containerHostname("test-host")
                         .environment(Map.of("TEST", "value"))
                         .framework("XGBOOST")
                         .frameworkVersion("1.5-1")
                         .image(example.registryPath())
                         .isCheckpoint(true)
                         .nearestModelName("nearest-model")
                         .build())
                     .supportedContentTypes("text/csv")
                     .supportedRealtimeInferenceInstanceTypes("ml.m5.large")
                     .supportedResponseMimeTypes("text/csv")
                     .supportedTransformInstanceTypes("ml.m5.large")
                     .build())
                 .algorithmName("example-inference-algorithm")
                 .build());
     
         }
     }
     
     
    ### Validation Specification
     
     package generated_program;
     
     import com.pulumi.Context;
     import com.pulumi.Pulumi;
     import com.pulumi.core.Output;
     import com.pulumi.aws.AwsFunctions;
     import com.pulumi.aws.inputs.GetPartitionArgs;
     import com.pulumi.aws.sagemaker.SagemakerFunctions;
     import com.pulumi.aws.sagemaker.inputs.GetPrebuiltEcrImageArgs;
     import com.pulumi.aws.iam.IamFunctions;
     import com.pulumi.aws.iam.inputs.GetPolicyDocumentArgs;
     import com.pulumi.aws.iam.inputs.GetPolicyDocumentStatementArgs;
     import com.pulumi.aws.iam.inputs.GetPolicyDocumentStatementPrincipalArgs;
     import com.pulumi.aws.iam.Role;
     import com.pulumi.aws.iam.RoleArgs;
     import com.pulumi.aws.iam.RolePolicyAttachment;
     import com.pulumi.aws.iam.RolePolicyAttachmentArgs;
     import com.pulumi.aws.s3.Bucket;
     import com.pulumi.aws.s3.BucketArgs;
     import com.pulumi.aws.iam.RolePolicy;
     import com.pulumi.aws.iam.RolePolicyArgs;
     import com.pulumi.aws.s3.BucketObjectv2;
     import com.pulumi.aws.s3.BucketObjectv2Args;
     import com.pulumi.aws.sagemaker.Algorithm;
     import com.pulumi.aws.sagemaker.AlgorithmArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedHyperParameterArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedHyperParameterRangeArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedHyperParameterRangeIntegerParameterRangeSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationSupportedHyperParameterRangeCategoricalParameterRangeSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmTrainingSpecificationTrainingChannelArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmInferenceSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmInferenceSpecificationContainerArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionOutputDataConfigArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionResourceConfigArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionStoppingConditionArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionInputDataConfigArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionInputDataConfigShuffleConfigArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionInputDataConfigDataSourceArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionInputDataConfigDataSourceS3DataSourceArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformInputArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformInputDataSourceArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformInputDataSourceS3DataSourceArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformOutputArgs;
     import com.pulumi.aws.sagemaker.inputs.AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformResourcesArgs;
     import com.pulumi.resources.CustomResourceOptions;
     import java.util.ArrayList;
     import java.util.Arrays;
     import java.util.Map;
     import java.io.File;
     import java.nio.file.Files;
     import java.nio.file.Paths;
     
     public class App {
         public static void main(String[] args) {
             Pulumi.run(App::stack);
         }
     
         public static void stack(Context ctx) {
             final var current = AwsFunctions.getPartition(GetPartitionArgs.builder()
                 .build());
     
             final var example = SagemakerFunctions.getPrebuiltEcrImage(GetPrebuiltEcrImageArgs.builder()
                 .repositoryName("linear-learner")
                 .imageTag("1")
                 .build());
     
             final var assumeRole = IamFunctions.getPolicyDocument(GetPolicyDocumentArgs.builder()
                 .statements(GetPolicyDocumentStatementArgs.builder()
                     .principals(GetPolicyDocumentStatementPrincipalArgs.builder()
                         .type("Service")
                         .identifiers(String.format("sagemaker.%s", current.dnsSuffix()))
                         .build())
                     .actions("sts:AssumeRole")
                     .build())
                 .build());
     
             var exampleRole = new Role("exampleRole", RoleArgs.builder()
                 .name("example-sagemaker-algorithm-role")
                 .assumeRolePolicy(assumeRole.json())
                 .build());
     
             var exampleRolePolicyAttachment = new RolePolicyAttachment("exampleRolePolicyAttachment", RolePolicyAttachmentArgs.builder()
                 .role(exampleRole.name())
                 .policyArn(String.format("arn:%s:iam::aws:policy/AmazonSageMakerFullAccess", current.partition()))
                 .build());
     
             var exampleBucket = new Bucket("exampleBucket", BucketArgs.builder()
                 .bucket("example-sagemaker-algorithm-validation-bucket")
                 .forceDestroy(true)
                 .build());
     
             final var s3Access = IamFunctions.getPolicyDocument(GetPolicyDocumentArgs.builder()
                 .statements(GetPolicyDocumentStatementArgs.builder()
                     .effect("Allow")
                     .actions(                
                         "s3:GetBucketLocation",
                         "s3:ListBucket",
                         "s3:GetObject",
                         "s3:PutObject")
                     .resources(                
                         exampleBucket.arn(),
                         exampleBucket.arn().applyValue(_arn -> String.format("%s/*", _arn)))
                     .build())
                 .build());
     
             var exampleRolePolicy = new RolePolicy("exampleRolePolicy", RolePolicyArgs.builder()
                 .role(exampleRole.name())
                 .policy(s3Access.applyValue(_s3Access -> _s3Access.json()))
                 .build());
     
             var training = new BucketObjectv2("training", BucketObjectv2Args.builder()
                 .bucket(exampleBucket.bucket())
                 .key("algorithm/training/data.csv")
                 .content("""
     1,1.0,0.0
     0,0.0,1.0
     1,1.0,1.0
     0,0.0,0.0
                 """)
                 .build());
     
             var transform = new BucketObjectv2("transform", BucketObjectv2Args.builder()
                 .bucket(exampleBucket.bucket())
                 .key("algorithm/transform/input.csv")
                 .content("""
     1.0,0.0
     0.0,1.0
                 """)
                 .build());
     
             var exampleAlgorithm = new Algorithm("exampleAlgorithm", AlgorithmArgs.builder()
                 .trainingSpecification(AlgorithmTrainingSpecificationArgs.builder()
                     .supportedHyperParameters(                
                         AlgorithmTrainingSpecificationSupportedHyperParameterArgs.builder()
                             .range(AlgorithmTrainingSpecificationSupportedHyperParameterRangeArgs.builder()
                                 .integerParameterRangeSpecification(AlgorithmTrainingSpecificationSupportedHyperParameterRangeIntegerParameterRangeSpecificationArgs.builder()
                                     .minValue("2")
                                     .maxValue("2")
                                     .build())
                                 .build())
                             .defaultValue("2")
                             .description("Feature dimension")
                             .isRequired(true)
                             .isTunable(false)
                             .name("feature_dim")
                             .type("Integer")
                             .build(),
                         AlgorithmTrainingSpecificationSupportedHyperParameterArgs.builder()
                             .range(AlgorithmTrainingSpecificationSupportedHyperParameterRangeArgs.builder()
                                 .integerParameterRangeSpecification(AlgorithmTrainingSpecificationSupportedHyperParameterRangeIntegerParameterRangeSpecificationArgs.builder()
                                     .minValue("4")
                                     .maxValue("4")
                                     .build())
                                 .build())
                             .defaultValue("4")
                             .description("Mini batch size")
                             .isRequired(true)
                             .isTunable(false)
                             .name("mini_batch_size")
                             .type("Integer")
                             .build(),
                         AlgorithmTrainingSpecificationSupportedHyperParameterArgs.builder()
                             .range(AlgorithmTrainingSpecificationSupportedHyperParameterRangeArgs.builder()
                                 .categoricalParameterRangeSpecification(AlgorithmTrainingSpecificationSupportedHyperParameterRangeCategoricalParameterRangeSpecificationArgs.builder()
                                     .values("binary_classifier")
                                     .build())
                                 .build())
                             .defaultValue("binary_classifier")
                             .description("Predictor type")
                             .isRequired(true)
                             .isTunable(false)
                             .name("predictor_type")
                             .type("Categorical")
                             .build())
                     .trainingChannels(AlgorithmTrainingSpecificationTrainingChannelArgs.builder()
                         .name("train")
                         .supportedContentTypes("text/csv")
                         .supportedInputModes("File")
                         .build())
                     .trainingImage(example.registryPath())
                     .supportedTrainingInstanceTypes("ml.m5.large")
                     .build())
                 .inferenceSpecification(AlgorithmInferenceSpecificationArgs.builder()
                     .containers(AlgorithmInferenceSpecificationContainerArgs.builder()
                         .image(example.registryPath())
                         .build())
                     .supportedContentTypes("text/csv")
                     .supportedResponseMimeTypes("text/csv")
                     .supportedTransformInstanceTypes("ml.m5.large")
                     .build())
                 .validationSpecification(AlgorithmValidationSpecificationArgs.builder()
                     .validationProfiles(AlgorithmValidationSpecificationValidationProfilesArgs.builder()
                         .trainingJobDefinition(AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionArgs.builder()
                             .outputDataConfig(AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionOutputDataConfigArgs.builder()
                                 .compressionType("GZIP")
                                 .s3OutputPath(exampleBucket.bucket().applyValue(_bucket -> String.format("s3://%s/algorithm/output", _bucket)))
                                 .build())
                             .resourceConfig(AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionResourceConfigArgs.builder()
                                 .instanceCount(1)
                                 .instanceType("ml.m5.large")
                                 .keepAlivePeriodInSeconds(60)
                                 .volumeSizeInGb(30)
                                 .build())
                             .stoppingCondition(AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionStoppingConditionArgs.builder()
                                 .maxPendingTimeInSeconds(7200)
                                 .maxRuntimeInSeconds(1800)
                                 .maxWaitTimeInSeconds(3600)
                                 .build())
                             .inputDataConfigs(AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionInputDataConfigArgs.builder()
                                 .shuffleConfig(AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionInputDataConfigShuffleConfigArgs.builder()
                                     .seed(1)
                                     .build())
                                 .dataSource(AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionInputDataConfigDataSourceArgs.builder()
                                     .s3DataSource(AlgorithmValidationSpecificationValidationProfilesTrainingJobDefinitionInputDataConfigDataSourceS3DataSourceArgs.builder()
                                         .attributeNames("label")
                                         .s3DataDistributionType("ShardedByS3Key")
                                         .s3DataType("S3Prefix")
                                         .s3Uri(exampleBucket.bucket().applyValue(_bucket -> String.format("s3://%s/algorithm/training/", _bucket)))
                                         .build())
                                     .build())
                                 .channelName("train")
                                 .compressionType("None")
                                 .contentType("text/csv")
                                 .inputMode("File")
                                 .recordWrapperType("None")
                                 .build())
                             .hyperParameters(Map.ofEntries(
                                 Map.entry("feature_dim", "2"),
                                 Map.entry("mini_batch_size", "4"),
                                 Map.entry("predictor_type", "binary_classifier")
                             ))
                             .trainingInputMode("File")
                             .build())
                         .transformJobDefinition(AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionArgs.builder()
                             .transformInput(AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformInputArgs.builder()
                                 .dataSource(AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformInputDataSourceArgs.builder()
                                     .s3DataSource(AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformInputDataSourceS3DataSourceArgs.builder()
                                         .s3DataType("S3Prefix")
                                         .s3Uri(exampleBucket.bucket().applyValue(_bucket -> String.format("s3://%s/algorithm/transform/", _bucket)))
                                         .build())
                                     .build())
                                 .compressionType("None")
                                 .contentType("text/csv")
                                 .splitType("Line")
                                 .build())
                             .transformOutput(AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformOutputArgs.builder()
                                 .accept("text/csv")
                                 .assembleWith("Line")
                                 .s3OutputPath(exampleBucket.bucket().applyValue(_bucket -> String.format("s3://%s/algorithm/transform-output", _bucket)))
                                 .build())
                             .transformResources(AlgorithmValidationSpecificationValidationProfilesTransformJobDefinitionTransformResourcesArgs.builder()
                                 .instanceCount(1)
                                 .instanceType("ml.m5.large")
                                 .build())
                             .batchStrategy("MultiRecord")
                             .environment(Map.of("Te", "enabled"))
                             .maxConcurrentTransforms(1)
                             .maxPayloadInMb(6)
                             .build())
                         .profileName("validation-profile")
                         .build())
                     .validationRole(exampleRole.arn())
                     .build())
                 .algorithmName("example-validation-algorithm")
                 .build(), CustomResourceOptions.builder()
                     .dependsOn(                
                         exampleRolePolicyAttachment,
                         exampleRolePolicy,
                         training,
                         transform)
                     .build());
     
         }
     }
     
     
    ## Import ### Identity Schema #### Required * `algorithmName` - (String) Name of the algorithm. #### Optional * `accountId` - (String) AWS account where this resource is managed. * `region` - (String) Region where this resource is managed. Using `pulumi import`, import SageMaker AI Algorithms using `algorithmName`. For example: ```sh $ pulumi import aws:sagemaker/algorithm:Algorithm example example-algorithm ```
    • Nested Class Summary

      • Nested classes/interfaces inherited from class com.pulumi.resources.CustomResource

        com.pulumi.resources.CustomResource.CustomResourceInternal
      • Nested classes/interfaces inherited from class com.pulumi.resources.Resource

        com.pulumi.resources.Resource.LazyField<T extends java.lang.Object>, com.pulumi.resources.Resource.LazyFields, com.pulumi.resources.Resource.ResourceInternal
    • Field Summary

      • Fields inherited from class com.pulumi.resources.Resource

        childResources, remote
    • Constructor Summary

      Constructors 
      Constructor Description
      Algorithm​(java.lang.String name)  
      Algorithm​(java.lang.String name, AlgorithmArgs args)  
      Algorithm​(java.lang.String name, AlgorithmArgs args, com.pulumi.resources.CustomResourceOptions options)  
    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      com.pulumi.core.Output<java.util.Optional<java.lang.String>> algorithmDescription()  
      com.pulumi.core.Output<java.lang.String> algorithmName()  
      com.pulumi.core.Output<java.lang.String> algorithmStatus()  
      com.pulumi.core.Output<java.lang.String> arn()  
      com.pulumi.core.Output<java.lang.Boolean> certifyForMarketplace()  
      com.pulumi.core.Output<java.lang.String> creationTime()  
      static Algorithm get​(java.lang.String name, com.pulumi.core.Output<java.lang.String> id, AlgorithmState state, com.pulumi.resources.CustomResourceOptions options)
      Get an existing Host resource's state with the given name, ID, and optional extra properties used to qualify the lookup.
      com.pulumi.core.Output<java.util.Optional<AlgorithmInferenceSpecification>> inferenceSpecification()  
      com.pulumi.core.Output<java.lang.String> productId()  
      com.pulumi.core.Output<java.lang.String> region()  
      com.pulumi.core.Output<java.util.Optional<java.util.Map<java.lang.String,​java.lang.String>>> tags()  
      com.pulumi.core.Output<java.util.Map<java.lang.String,​java.lang.String>> tagsAll()  
      com.pulumi.core.Output<java.util.Optional<AlgorithmTimeouts>> timeouts()  
      com.pulumi.core.Output<AlgorithmTrainingSpecification> trainingSpecification()  
      com.pulumi.core.Output<java.util.Optional<AlgorithmValidationSpecification>> validationSpecification()  
      • Methods inherited from class com.pulumi.resources.CustomResource

        getId, id, idFuture
      • Methods inherited from class com.pulumi.resources.Resource

        getChildResources, getResourceName, getResourceType, getUrn, pulumiChildResources, pulumiResourceName, pulumiResourceType, urn
      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
    • Constructor Detail

      • Algorithm

        public Algorithm​(java.lang.String name)
        Parameters:
        name - The _unique_ name of the resulting resource.
      • Algorithm

        public Algorithm​(java.lang.String name,
                         AlgorithmArgs args)
        Parameters:
        name - The _unique_ name of the resulting resource.
        args - The arguments to use to populate this resource's properties.
      • Algorithm

        public Algorithm​(java.lang.String name,
                         AlgorithmArgs args,
                         @Nullable
                         com.pulumi.resources.CustomResourceOptions options)
        Parameters:
        name - The _unique_ name of the resulting resource.
        args - The arguments to use to populate this resource's properties.
        options - A bag of options that control this resource's behavior.
    • Method Detail

      • algorithmDescription

        public com.pulumi.core.Output<java.util.Optional<java.lang.String>> algorithmDescription()
        Returns:
        Description of the algorithm.
      • algorithmName

        public com.pulumi.core.Output<java.lang.String> algorithmName()
        Returns:
        Name of the algorithm.
      • algorithmStatus

        public com.pulumi.core.Output<java.lang.String> algorithmStatus()
        Returns:
        Status of the algorithm.
      • arn

        public com.pulumi.core.Output<java.lang.String> arn()
        Returns:
        ARN of the algorithm.
      • certifyForMarketplace

        public com.pulumi.core.Output<java.lang.Boolean> certifyForMarketplace()
        Returns:
        Whether to certify the algorithm for AWS Marketplace.
      • creationTime

        public com.pulumi.core.Output<java.lang.String> creationTime()
        Returns:
        Time when the algorithm was created, in RFC3339 format.
      • inferenceSpecification

        public com.pulumi.core.Output<java.util.Optional<AlgorithmInferenceSpecification>> inferenceSpecification()
        Returns:
        Configuration for inference jobs that use this algorithm. See Inference Specification.
      • productId

        public com.pulumi.core.Output<java.lang.String> productId()
        Returns:
        AWS Marketplace product ID associated with the algorithm.
      • region

        public com.pulumi.core.Output<java.lang.String> region()
        Returns:
        Region where this resource is managed. Defaults to the Region set in the provider configuration.
      • tags

        public com.pulumi.core.Output<java.util.Optional<java.util.Map<java.lang.String,​java.lang.String>>> tags()
        Returns:
        Map of tags to assign to the resource.
      • tagsAll

        public com.pulumi.core.Output<java.util.Map<java.lang.String,​java.lang.String>> tagsAll()
        Returns:
        Map of tags assigned to the resource, including tags inherited from the provider `defaultTags` configuration block.
      • timeouts

        public com.pulumi.core.Output<java.util.Optional<AlgorithmTimeouts>> timeouts()
      • trainingSpecification

        public com.pulumi.core.Output<AlgorithmTrainingSpecification> trainingSpecification()
        Returns:
        Configuration for training jobs that use this algorithm. See Training Specification.
      • validationSpecification

        public com.pulumi.core.Output<java.util.Optional<AlgorithmValidationSpecification>> validationSpecification()
        Returns:
        Configuration used to validate the algorithm. See Validation Specification.
      • get

        public static Algorithm get​(java.lang.String name,
                                    com.pulumi.core.Output<java.lang.String> id,
                                    @Nullable
                                    AlgorithmState state,
                                    @Nullable
                                    com.pulumi.resources.CustomResourceOptions options)
        Get an existing Host resource's state with the given name, ID, and optional extra properties used to qualify the lookup.
        Parameters:
        name - The _unique_ name of the resulting resource.
        id - The _unique_ provider ID of the resource to lookup.
        state -
        options - Optional settings to control the behavior of the CustomResource.