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Oracle Cloud Infrastructure v2.17.0 published on Friday, Nov 15, 2024 by Pulumi

oci.DataScience.Model

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Oracle Cloud Infrastructure v2.17.0 published on Friday, Nov 15, 2024 by Pulumi

    This resource provides the Model resource in Oracle Cloud Infrastructure Data Science service.

    Creates a new model.

    Example Usage

    import * as pulumi from "@pulumi/pulumi";
    import * as oci from "@pulumi/oci";
    
    const testModel = new oci.datascience.Model("test_model", {
        compartmentId: compartmentId,
        projectId: testProject.id,
        backupSetting: {
            backupRegion: modelBackupSettingBackupRegion,
            isBackupEnabled: modelBackupSettingIsBackupEnabled,
            customerNotificationType: modelBackupSettingCustomerNotificationType,
        },
        customMetadataLists: [{
            category: modelCustomMetadataListCategory,
            description: modelCustomMetadataListDescription,
            key: modelCustomMetadataListKey,
            value: modelCustomMetadataListValue,
        }],
        definedMetadataLists: [{
            category: modelDefinedMetadataListCategory,
            description: modelDefinedMetadataListDescription,
            key: modelDefinedMetadataListKey,
            value: modelDefinedMetadataListValue,
        }],
        definedTags: {
            "Operations.CostCenter": "42",
        },
        description: modelDescription,
        displayName: modelDisplayName,
        freeformTags: {
            Department: "Finance",
        },
        inputSchema: modelInputSchema,
        outputSchema: modelOutputSchema,
        retentionSetting: {
            archiveAfterDays: modelRetentionSettingArchiveAfterDays,
            customerNotificationType: modelRetentionSettingCustomerNotificationType,
            deleteAfterDays: modelRetentionSettingDeleteAfterDays,
        },
        versionLabel: modelVersionLabel,
    });
    
    import pulumi
    import pulumi_oci as oci
    
    test_model = oci.data_science.Model("test_model",
        compartment_id=compartment_id,
        project_id=test_project["id"],
        backup_setting={
            "backup_region": model_backup_setting_backup_region,
            "is_backup_enabled": model_backup_setting_is_backup_enabled,
            "customer_notification_type": model_backup_setting_customer_notification_type,
        },
        custom_metadata_lists=[{
            "category": model_custom_metadata_list_category,
            "description": model_custom_metadata_list_description,
            "key": model_custom_metadata_list_key,
            "value": model_custom_metadata_list_value,
        }],
        defined_metadata_lists=[{
            "category": model_defined_metadata_list_category,
            "description": model_defined_metadata_list_description,
            "key": model_defined_metadata_list_key,
            "value": model_defined_metadata_list_value,
        }],
        defined_tags={
            "Operations.CostCenter": "42",
        },
        description=model_description,
        display_name=model_display_name,
        freeform_tags={
            "Department": "Finance",
        },
        input_schema=model_input_schema,
        output_schema=model_output_schema,
        retention_setting={
            "archive_after_days": model_retention_setting_archive_after_days,
            "customer_notification_type": model_retention_setting_customer_notification_type,
            "delete_after_days": model_retention_setting_delete_after_days,
        },
        version_label=model_version_label)
    
    package main
    
    import (
    	"github.com/pulumi/pulumi-oci/sdk/v2/go/oci/DataScience"
    	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
    )
    
    func main() {
    	pulumi.Run(func(ctx *pulumi.Context) error {
    		_, err := DataScience.NewModel(ctx, "test_model", &DataScience.ModelArgs{
    			CompartmentId: pulumi.Any(compartmentId),
    			ProjectId:     pulumi.Any(testProject.Id),
    			BackupSetting: &datascience.ModelBackupSettingArgs{
    				BackupRegion:             pulumi.Any(modelBackupSettingBackupRegion),
    				IsBackupEnabled:          pulumi.Any(modelBackupSettingIsBackupEnabled),
    				CustomerNotificationType: pulumi.Any(modelBackupSettingCustomerNotificationType),
    			},
    			CustomMetadataLists: datascience.ModelCustomMetadataListArray{
    				&datascience.ModelCustomMetadataListArgs{
    					Category:    pulumi.Any(modelCustomMetadataListCategory),
    					Description: pulumi.Any(modelCustomMetadataListDescription),
    					Key:         pulumi.Any(modelCustomMetadataListKey),
    					Value:       pulumi.Any(modelCustomMetadataListValue),
    				},
    			},
    			DefinedMetadataLists: datascience.ModelDefinedMetadataListArray{
    				&datascience.ModelDefinedMetadataListArgs{
    					Category:    pulumi.Any(modelDefinedMetadataListCategory),
    					Description: pulumi.Any(modelDefinedMetadataListDescription),
    					Key:         pulumi.Any(modelDefinedMetadataListKey),
    					Value:       pulumi.Any(modelDefinedMetadataListValue),
    				},
    			},
    			DefinedTags: pulumi.StringMap{
    				"Operations.CostCenter": pulumi.String("42"),
    			},
    			Description: pulumi.Any(modelDescription),
    			DisplayName: pulumi.Any(modelDisplayName),
    			FreeformTags: pulumi.StringMap{
    				"Department": pulumi.String("Finance"),
    			},
    			InputSchema:  pulumi.Any(modelInputSchema),
    			OutputSchema: pulumi.Any(modelOutputSchema),
    			RetentionSetting: &datascience.ModelRetentionSettingArgs{
    				ArchiveAfterDays:         pulumi.Any(modelRetentionSettingArchiveAfterDays),
    				CustomerNotificationType: pulumi.Any(modelRetentionSettingCustomerNotificationType),
    				DeleteAfterDays:          pulumi.Any(modelRetentionSettingDeleteAfterDays),
    			},
    			VersionLabel: pulumi.Any(modelVersionLabel),
    		})
    		if err != nil {
    			return err
    		}
    		return nil
    	})
    }
    
    using System.Collections.Generic;
    using System.Linq;
    using Pulumi;
    using Oci = Pulumi.Oci;
    
    return await Deployment.RunAsync(() => 
    {
        var testModel = new Oci.DataScience.Model("test_model", new()
        {
            CompartmentId = compartmentId,
            ProjectId = testProject.Id,
            BackupSetting = new Oci.DataScience.Inputs.ModelBackupSettingArgs
            {
                BackupRegion = modelBackupSettingBackupRegion,
                IsBackupEnabled = modelBackupSettingIsBackupEnabled,
                CustomerNotificationType = modelBackupSettingCustomerNotificationType,
            },
            CustomMetadataLists = new[]
            {
                new Oci.DataScience.Inputs.ModelCustomMetadataListArgs
                {
                    Category = modelCustomMetadataListCategory,
                    Description = modelCustomMetadataListDescription,
                    Key = modelCustomMetadataListKey,
                    Value = modelCustomMetadataListValue,
                },
            },
            DefinedMetadataLists = new[]
            {
                new Oci.DataScience.Inputs.ModelDefinedMetadataListArgs
                {
                    Category = modelDefinedMetadataListCategory,
                    Description = modelDefinedMetadataListDescription,
                    Key = modelDefinedMetadataListKey,
                    Value = modelDefinedMetadataListValue,
                },
            },
            DefinedTags = 
            {
                { "Operations.CostCenter", "42" },
            },
            Description = modelDescription,
            DisplayName = modelDisplayName,
            FreeformTags = 
            {
                { "Department", "Finance" },
            },
            InputSchema = modelInputSchema,
            OutputSchema = modelOutputSchema,
            RetentionSetting = new Oci.DataScience.Inputs.ModelRetentionSettingArgs
            {
                ArchiveAfterDays = modelRetentionSettingArchiveAfterDays,
                CustomerNotificationType = modelRetentionSettingCustomerNotificationType,
                DeleteAfterDays = modelRetentionSettingDeleteAfterDays,
            },
            VersionLabel = modelVersionLabel,
        });
    
    });
    
    package generated_program;
    
    import com.pulumi.Context;
    import com.pulumi.Pulumi;
    import com.pulumi.core.Output;
    import com.pulumi.oci.DataScience.Model;
    import com.pulumi.oci.DataScience.ModelArgs;
    import com.pulumi.oci.DataScience.inputs.ModelBackupSettingArgs;
    import com.pulumi.oci.DataScience.inputs.ModelCustomMetadataListArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDefinedMetadataListArgs;
    import com.pulumi.oci.DataScience.inputs.ModelRetentionSettingArgs;
    import java.util.List;
    import java.util.ArrayList;
    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 testModel = new Model("testModel", ModelArgs.builder()
                .compartmentId(compartmentId)
                .projectId(testProject.id())
                .backupSetting(ModelBackupSettingArgs.builder()
                    .backupRegion(modelBackupSettingBackupRegion)
                    .isBackupEnabled(modelBackupSettingIsBackupEnabled)
                    .customerNotificationType(modelBackupSettingCustomerNotificationType)
                    .build())
                .customMetadataLists(ModelCustomMetadataListArgs.builder()
                    .category(modelCustomMetadataListCategory)
                    .description(modelCustomMetadataListDescription)
                    .key(modelCustomMetadataListKey)
                    .value(modelCustomMetadataListValue)
                    .build())
                .definedMetadataLists(ModelDefinedMetadataListArgs.builder()
                    .category(modelDefinedMetadataListCategory)
                    .description(modelDefinedMetadataListDescription)
                    .key(modelDefinedMetadataListKey)
                    .value(modelDefinedMetadataListValue)
                    .build())
                .definedTags(Map.of("Operations.CostCenter", "42"))
                .description(modelDescription)
                .displayName(modelDisplayName)
                .freeformTags(Map.of("Department", "Finance"))
                .inputSchema(modelInputSchema)
                .outputSchema(modelOutputSchema)
                .retentionSetting(ModelRetentionSettingArgs.builder()
                    .archiveAfterDays(modelRetentionSettingArchiveAfterDays)
                    .customerNotificationType(modelRetentionSettingCustomerNotificationType)
                    .deleteAfterDays(modelRetentionSettingDeleteAfterDays)
                    .build())
                .versionLabel(modelVersionLabel)
                .build());
    
        }
    }
    
    resources:
      testModel:
        type: oci:DataScience:Model
        name: test_model
        properties:
          compartmentId: ${compartmentId}
          projectId: ${testProject.id}
          backupSetting:
            backupRegion: ${modelBackupSettingBackupRegion}
            isBackupEnabled: ${modelBackupSettingIsBackupEnabled}
            customerNotificationType: ${modelBackupSettingCustomerNotificationType}
          customMetadataLists:
            - category: ${modelCustomMetadataListCategory}
              description: ${modelCustomMetadataListDescription}
              key: ${modelCustomMetadataListKey}
              value: ${modelCustomMetadataListValue}
          definedMetadataLists:
            - category: ${modelDefinedMetadataListCategory}
              description: ${modelDefinedMetadataListDescription}
              key: ${modelDefinedMetadataListKey}
              value: ${modelDefinedMetadataListValue}
          definedTags:
            Operations.CostCenter: '42'
          description: ${modelDescription}
          displayName: ${modelDisplayName}
          freeformTags:
            Department: Finance
          inputSchema: ${modelInputSchema}
          outputSchema: ${modelOutputSchema}
          retentionSetting:
            archiveAfterDays: ${modelRetentionSettingArchiveAfterDays}
            customerNotificationType: ${modelRetentionSettingCustomerNotificationType}
            deleteAfterDays: ${modelRetentionSettingDeleteAfterDays}
          versionLabel: ${modelVersionLabel}
    

    Create Model Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new Model(name: string, args: ModelArgs, opts?: CustomResourceOptions);
    @overload
    def Model(resource_name: str,
              args: ModelArgs,
              opts: Optional[ResourceOptions] = None)
    
    @overload
    def Model(resource_name: str,
              opts: Optional[ResourceOptions] = None,
              model_artifact: Optional[str] = None,
              artifact_content_length: Optional[str] = None,
              project_id: Optional[str] = None,
              compartment_id: Optional[str] = None,
              display_name: Optional[str] = None,
              custom_metadata_lists: Optional[Sequence[_datascience.ModelCustomMetadataListArgs]] = None,
              defined_tags: Optional[Mapping[str, str]] = None,
              description: Optional[str] = None,
              artifact_content_disposition: Optional[str] = None,
              freeform_tags: Optional[Mapping[str, str]] = None,
              input_schema: Optional[str] = None,
              defined_metadata_lists: Optional[Sequence[_datascience.ModelDefinedMetadataListArgs]] = None,
              model_version_set_id: Optional[str] = None,
              model_version_set_name: Optional[str] = None,
              output_schema: Optional[str] = None,
              backup_setting: Optional[_datascience.ModelBackupSettingArgs] = None,
              retention_setting: Optional[_datascience.ModelRetentionSettingArgs] = None,
              state: Optional[str] = None,
              version_label: Optional[str] = None)
    func NewModel(ctx *Context, name string, args ModelArgs, opts ...ResourceOption) (*Model, error)
    public Model(string name, ModelArgs args, CustomResourceOptions? opts = null)
    public Model(String name, ModelArgs args)
    public Model(String name, ModelArgs args, CustomResourceOptions options)
    
    type: oci:DataScience:Model
    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 ModelArgs
    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 ModelArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args ModelArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args ModelArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args ModelArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var examplemodelResourceResourceFromDataSciencemodel = new Oci.DataScience.Model("examplemodelResourceResourceFromDataSciencemodel", new()
    {
        ModelArtifact = "string",
        ArtifactContentLength = "string",
        ProjectId = "string",
        CompartmentId = "string",
        DisplayName = "string",
        CustomMetadataLists = new[]
        {
            new Oci.DataScience.Inputs.ModelCustomMetadataListArgs
            {
                Category = "string",
                Description = "string",
                Key = "string",
                Value = "string",
            },
        },
        DefinedTags = 
        {
            { "string", "string" },
        },
        Description = "string",
        ArtifactContentDisposition = "string",
        FreeformTags = 
        {
            { "string", "string" },
        },
        InputSchema = "string",
        DefinedMetadataLists = new[]
        {
            new Oci.DataScience.Inputs.ModelDefinedMetadataListArgs
            {
                Category = "string",
                Description = "string",
                Key = "string",
                Value = "string",
            },
        },
        ModelVersionSetId = "string",
        ModelVersionSetName = "string",
        OutputSchema = "string",
        BackupSetting = new Oci.DataScience.Inputs.ModelBackupSettingArgs
        {
            BackupRegion = "string",
            IsBackupEnabled = false,
            CustomerNotificationType = "string",
        },
        RetentionSetting = new Oci.DataScience.Inputs.ModelRetentionSettingArgs
        {
            ArchiveAfterDays = 0,
            CustomerNotificationType = "string",
            DeleteAfterDays = 0,
        },
        State = "string",
        VersionLabel = "string",
    });
    
    example, err := DataScience.NewModel(ctx, "examplemodelResourceResourceFromDataSciencemodel", &DataScience.ModelArgs{
    	ModelArtifact:         pulumi.String("string"),
    	ArtifactContentLength: pulumi.String("string"),
    	ProjectId:             pulumi.String("string"),
    	CompartmentId:         pulumi.String("string"),
    	DisplayName:           pulumi.String("string"),
    	CustomMetadataLists: datascience.ModelCustomMetadataListArray{
    		&datascience.ModelCustomMetadataListArgs{
    			Category:    pulumi.String("string"),
    			Description: pulumi.String("string"),
    			Key:         pulumi.String("string"),
    			Value:       pulumi.String("string"),
    		},
    	},
    	DefinedTags: pulumi.StringMap{
    		"string": pulumi.String("string"),
    	},
    	Description:                pulumi.String("string"),
    	ArtifactContentDisposition: pulumi.String("string"),
    	FreeformTags: pulumi.StringMap{
    		"string": pulumi.String("string"),
    	},
    	InputSchema: pulumi.String("string"),
    	DefinedMetadataLists: datascience.ModelDefinedMetadataListArray{
    		&datascience.ModelDefinedMetadataListArgs{
    			Category:    pulumi.String("string"),
    			Description: pulumi.String("string"),
    			Key:         pulumi.String("string"),
    			Value:       pulumi.String("string"),
    		},
    	},
    	ModelVersionSetId:   pulumi.String("string"),
    	ModelVersionSetName: pulumi.String("string"),
    	OutputSchema:        pulumi.String("string"),
    	BackupSetting: &datascience.ModelBackupSettingArgs{
    		BackupRegion:             pulumi.String("string"),
    		IsBackupEnabled:          pulumi.Bool(false),
    		CustomerNotificationType: pulumi.String("string"),
    	},
    	RetentionSetting: &datascience.ModelRetentionSettingArgs{
    		ArchiveAfterDays:         pulumi.Int(0),
    		CustomerNotificationType: pulumi.String("string"),
    		DeleteAfterDays:          pulumi.Int(0),
    	},
    	State:        pulumi.String("string"),
    	VersionLabel: pulumi.String("string"),
    })
    
    var examplemodelResourceResourceFromDataSciencemodel = new Model("examplemodelResourceResourceFromDataSciencemodel", ModelArgs.builder()
        .modelArtifact("string")
        .artifactContentLength("string")
        .projectId("string")
        .compartmentId("string")
        .displayName("string")
        .customMetadataLists(ModelCustomMetadataListArgs.builder()
            .category("string")
            .description("string")
            .key("string")
            .value("string")
            .build())
        .definedTags(Map.of("string", "string"))
        .description("string")
        .artifactContentDisposition("string")
        .freeformTags(Map.of("string", "string"))
        .inputSchema("string")
        .definedMetadataLists(ModelDefinedMetadataListArgs.builder()
            .category("string")
            .description("string")
            .key("string")
            .value("string")
            .build())
        .modelVersionSetId("string")
        .modelVersionSetName("string")
        .outputSchema("string")
        .backupSetting(ModelBackupSettingArgs.builder()
            .backupRegion("string")
            .isBackupEnabled(false)
            .customerNotificationType("string")
            .build())
        .retentionSetting(ModelRetentionSettingArgs.builder()
            .archiveAfterDays(0)
            .customerNotificationType("string")
            .deleteAfterDays(0)
            .build())
        .state("string")
        .versionLabel("string")
        .build());
    
    examplemodel_resource_resource_from_data_sciencemodel = oci.data_science.Model("examplemodelResourceResourceFromDataSciencemodel",
        model_artifact="string",
        artifact_content_length="string",
        project_id="string",
        compartment_id="string",
        display_name="string",
        custom_metadata_lists=[{
            "category": "string",
            "description": "string",
            "key": "string",
            "value": "string",
        }],
        defined_tags={
            "string": "string",
        },
        description="string",
        artifact_content_disposition="string",
        freeform_tags={
            "string": "string",
        },
        input_schema="string",
        defined_metadata_lists=[{
            "category": "string",
            "description": "string",
            "key": "string",
            "value": "string",
        }],
        model_version_set_id="string",
        model_version_set_name="string",
        output_schema="string",
        backup_setting={
            "backup_region": "string",
            "is_backup_enabled": False,
            "customer_notification_type": "string",
        },
        retention_setting={
            "archive_after_days": 0,
            "customer_notification_type": "string",
            "delete_after_days": 0,
        },
        state="string",
        version_label="string")
    
    const examplemodelResourceResourceFromDataSciencemodel = new oci.datascience.Model("examplemodelResourceResourceFromDataSciencemodel", {
        modelArtifact: "string",
        artifactContentLength: "string",
        projectId: "string",
        compartmentId: "string",
        displayName: "string",
        customMetadataLists: [{
            category: "string",
            description: "string",
            key: "string",
            value: "string",
        }],
        definedTags: {
            string: "string",
        },
        description: "string",
        artifactContentDisposition: "string",
        freeformTags: {
            string: "string",
        },
        inputSchema: "string",
        definedMetadataLists: [{
            category: "string",
            description: "string",
            key: "string",
            value: "string",
        }],
        modelVersionSetId: "string",
        modelVersionSetName: "string",
        outputSchema: "string",
        backupSetting: {
            backupRegion: "string",
            isBackupEnabled: false,
            customerNotificationType: "string",
        },
        retentionSetting: {
            archiveAfterDays: 0,
            customerNotificationType: "string",
            deleteAfterDays: 0,
        },
        state: "string",
        versionLabel: "string",
    });
    
    type: oci:DataScience:Model
    properties:
        artifactContentDisposition: string
        artifactContentLength: string
        backupSetting:
            backupRegion: string
            customerNotificationType: string
            isBackupEnabled: false
        compartmentId: string
        customMetadataLists:
            - category: string
              description: string
              key: string
              value: string
        definedMetadataLists:
            - category: string
              description: string
              key: string
              value: string
        definedTags:
            string: string
        description: string
        displayName: string
        freeformTags:
            string: string
        inputSchema: string
        modelArtifact: string
        modelVersionSetId: string
        modelVersionSetName: string
        outputSchema: string
        projectId: string
        retentionSetting:
            archiveAfterDays: 0
            customerNotificationType: string
            deleteAfterDays: 0
        state: string
        versionLabel: string
    

    Model Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The Model resource accepts the following input properties:

    ArtifactContentLength string

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    CompartmentId string
    (Updatable) The OCID of the compartment to create the model in.
    ModelArtifact string
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    ProjectId string
    The OCID of the project to associate with the model.
    ArtifactContentDisposition string
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    BackupSetting ModelBackupSetting
    (Updatable) Back up setting details of the model.
    CustomMetadataLists List<ModelCustomMetadataList>
    (Updatable) An array of custom metadata details for the model.
    DefinedMetadataLists List<ModelDefinedMetadataList>
    (Updatable) An array of defined metadata details for the model.
    DefinedTags Dictionary<string, string>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    Description string
    (Updatable) A short description of the model.
    DisplayName string
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    FreeformTags Dictionary<string, string>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    InputSchema string
    Input schema file content in String format
    ModelVersionSetId string
    The OCID of the model version set that the model is associated to.
    ModelVersionSetName string
    The name of the model version set that the model is associated to.
    OutputSchema string
    Output schema file content in String format
    RetentionSetting ModelRetentionSetting
    (Updatable) Retention setting details of the model.
    State string
    The state of the model.
    VersionLabel string
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    ArtifactContentLength string

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    CompartmentId string
    (Updatable) The OCID of the compartment to create the model in.
    ModelArtifact string
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    ProjectId string
    The OCID of the project to associate with the model.
    ArtifactContentDisposition string
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    BackupSetting ModelBackupSettingArgs
    (Updatable) Back up setting details of the model.
    CustomMetadataLists []ModelCustomMetadataListArgs
    (Updatable) An array of custom metadata details for the model.
    DefinedMetadataLists []ModelDefinedMetadataListArgs
    (Updatable) An array of defined metadata details for the model.
    DefinedTags map[string]string
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    Description string
    (Updatable) A short description of the model.
    DisplayName string
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    FreeformTags map[string]string
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    InputSchema string
    Input schema file content in String format
    ModelVersionSetId string
    The OCID of the model version set that the model is associated to.
    ModelVersionSetName string
    The name of the model version set that the model is associated to.
    OutputSchema string
    Output schema file content in String format
    RetentionSetting ModelRetentionSettingArgs
    (Updatable) Retention setting details of the model.
    State string
    The state of the model.
    VersionLabel string
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    artifactContentLength String

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    compartmentId String
    (Updatable) The OCID of the compartment to create the model in.
    modelArtifact String
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    projectId String
    The OCID of the project to associate with the model.
    artifactContentDisposition String
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    backupSetting ModelBackupSetting
    (Updatable) Back up setting details of the model.
    customMetadataLists List<ModelCustomMetadataList>
    (Updatable) An array of custom metadata details for the model.
    definedMetadataLists List<ModelDefinedMetadataList>
    (Updatable) An array of defined metadata details for the model.
    definedTags Map<String,String>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description String
    (Updatable) A short description of the model.
    displayName String
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    freeformTags Map<String,String>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    inputSchema String
    Input schema file content in String format
    modelVersionSetId String
    The OCID of the model version set that the model is associated to.
    modelVersionSetName String
    The name of the model version set that the model is associated to.
    outputSchema String
    Output schema file content in String format
    retentionSetting ModelRetentionSetting
    (Updatable) Retention setting details of the model.
    state String
    The state of the model.
    versionLabel String
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    artifactContentLength string

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    compartmentId string
    (Updatable) The OCID of the compartment to create the model in.
    modelArtifact string
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    projectId string
    The OCID of the project to associate with the model.
    artifactContentDisposition string
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    backupSetting ModelBackupSetting
    (Updatable) Back up setting details of the model.
    customMetadataLists ModelCustomMetadataList[]
    (Updatable) An array of custom metadata details for the model.
    definedMetadataLists ModelDefinedMetadataList[]
    (Updatable) An array of defined metadata details for the model.
    definedTags {[key: string]: string}
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description string
    (Updatable) A short description of the model.
    displayName string
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    freeformTags {[key: string]: string}
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    inputSchema string
    Input schema file content in String format
    modelVersionSetId string
    The OCID of the model version set that the model is associated to.
    modelVersionSetName string
    The name of the model version set that the model is associated to.
    outputSchema string
    Output schema file content in String format
    retentionSetting ModelRetentionSetting
    (Updatable) Retention setting details of the model.
    state string
    The state of the model.
    versionLabel string
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    artifact_content_length str

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    compartment_id str
    (Updatable) The OCID of the compartment to create the model in.
    model_artifact str
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    project_id str
    The OCID of the project to associate with the model.
    artifact_content_disposition str
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    backup_setting datascience.ModelBackupSettingArgs
    (Updatable) Back up setting details of the model.
    custom_metadata_lists Sequence[datascience.ModelCustomMetadataListArgs]
    (Updatable) An array of custom metadata details for the model.
    defined_metadata_lists Sequence[datascience.ModelDefinedMetadataListArgs]
    (Updatable) An array of defined metadata details for the model.
    defined_tags Mapping[str, str]
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description str
    (Updatable) A short description of the model.
    display_name str
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    freeform_tags Mapping[str, str]
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    input_schema str
    Input schema file content in String format
    model_version_set_id str
    The OCID of the model version set that the model is associated to.
    model_version_set_name str
    The name of the model version set that the model is associated to.
    output_schema str
    Output schema file content in String format
    retention_setting datascience.ModelRetentionSettingArgs
    (Updatable) Retention setting details of the model.
    state str
    The state of the model.
    version_label str
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    artifactContentLength String

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    compartmentId String
    (Updatable) The OCID of the compartment to create the model in.
    modelArtifact String
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    projectId String
    The OCID of the project to associate with the model.
    artifactContentDisposition String
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    backupSetting Property Map
    (Updatable) Back up setting details of the model.
    customMetadataLists List<Property Map>
    (Updatable) An array of custom metadata details for the model.
    definedMetadataLists List<Property Map>
    (Updatable) An array of defined metadata details for the model.
    definedTags Map<String>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description String
    (Updatable) A short description of the model.
    displayName String
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    freeformTags Map<String>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    inputSchema String
    Input schema file content in String format
    modelVersionSetId String
    The OCID of the model version set that the model is associated to.
    modelVersionSetName String
    The name of the model version set that the model is associated to.
    outputSchema String
    Output schema file content in String format
    retentionSetting Property Map
    (Updatable) Retention setting details of the model.
    state String
    The state of the model.
    versionLabel String
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the Model resource produces the following output properties:

    ArtifactContentMd5 string
    ArtifactLastModified string
    BackupOperationDetails List<ModelBackupOperationDetail>
    Backup operation details of the model.
    CreatedBy string
    The OCID of the user who created the model.
    EmptyModel bool
    Id string
    The provider-assigned unique ID for this managed resource.
    LifecycleDetails string
    Details about the lifecycle state of the model.
    RetentionOperationDetails List<ModelRetentionOperationDetail>
    Retention operation details for the model.
    TimeCreated string
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    ArtifactContentMd5 string
    ArtifactLastModified string
    BackupOperationDetails []ModelBackupOperationDetail
    Backup operation details of the model.
    CreatedBy string
    The OCID of the user who created the model.
    EmptyModel bool
    Id string
    The provider-assigned unique ID for this managed resource.
    LifecycleDetails string
    Details about the lifecycle state of the model.
    RetentionOperationDetails []ModelRetentionOperationDetail
    Retention operation details for the model.
    TimeCreated string
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    artifactContentMd5 String
    artifactLastModified String
    backupOperationDetails List<ModelBackupOperationDetail>
    Backup operation details of the model.
    createdBy String
    The OCID of the user who created the model.
    emptyModel Boolean
    id String
    The provider-assigned unique ID for this managed resource.
    lifecycleDetails String
    Details about the lifecycle state of the model.
    retentionOperationDetails List<ModelRetentionOperationDetail>
    Retention operation details for the model.
    timeCreated String
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    artifactContentMd5 string
    artifactLastModified string
    backupOperationDetails ModelBackupOperationDetail[]
    Backup operation details of the model.
    createdBy string
    The OCID of the user who created the model.
    emptyModel boolean
    id string
    The provider-assigned unique ID for this managed resource.
    lifecycleDetails string
    Details about the lifecycle state of the model.
    retentionOperationDetails ModelRetentionOperationDetail[]
    Retention operation details for the model.
    timeCreated string
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    artifact_content_md5 str
    artifact_last_modified str
    backup_operation_details Sequence[datascience.ModelBackupOperationDetail]
    Backup operation details of the model.
    created_by str
    The OCID of the user who created the model.
    empty_model bool
    id str
    The provider-assigned unique ID for this managed resource.
    lifecycle_details str
    Details about the lifecycle state of the model.
    retention_operation_details Sequence[datascience.ModelRetentionOperationDetail]
    Retention operation details for the model.
    time_created str
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    artifactContentMd5 String
    artifactLastModified String
    backupOperationDetails List<Property Map>
    Backup operation details of the model.
    createdBy String
    The OCID of the user who created the model.
    emptyModel Boolean
    id String
    The provider-assigned unique ID for this managed resource.
    lifecycleDetails String
    Details about the lifecycle state of the model.
    retentionOperationDetails List<Property Map>
    Retention operation details for the model.
    timeCreated String
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z

    Look up Existing Model Resource

    Get an existing Model resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: ModelState, opts?: CustomResourceOptions): Model
    @staticmethod
    def get(resource_name: str,
            id: str,
            opts: Optional[ResourceOptions] = None,
            artifact_content_disposition: Optional[str] = None,
            artifact_content_length: Optional[str] = None,
            artifact_content_md5: Optional[str] = None,
            artifact_last_modified: Optional[str] = None,
            backup_operation_details: Optional[Sequence[_datascience.ModelBackupOperationDetailArgs]] = None,
            backup_setting: Optional[_datascience.ModelBackupSettingArgs] = None,
            compartment_id: Optional[str] = None,
            created_by: Optional[str] = None,
            custom_metadata_lists: Optional[Sequence[_datascience.ModelCustomMetadataListArgs]] = None,
            defined_metadata_lists: Optional[Sequence[_datascience.ModelDefinedMetadataListArgs]] = None,
            defined_tags: Optional[Mapping[str, str]] = None,
            description: Optional[str] = None,
            display_name: Optional[str] = None,
            empty_model: Optional[bool] = None,
            freeform_tags: Optional[Mapping[str, str]] = None,
            input_schema: Optional[str] = None,
            lifecycle_details: Optional[str] = None,
            model_artifact: Optional[str] = None,
            model_version_set_id: Optional[str] = None,
            model_version_set_name: Optional[str] = None,
            output_schema: Optional[str] = None,
            project_id: Optional[str] = None,
            retention_operation_details: Optional[Sequence[_datascience.ModelRetentionOperationDetailArgs]] = None,
            retention_setting: Optional[_datascience.ModelRetentionSettingArgs] = None,
            state: Optional[str] = None,
            time_created: Optional[str] = None,
            version_label: Optional[str] = None) -> Model
    func GetModel(ctx *Context, name string, id IDInput, state *ModelState, opts ...ResourceOption) (*Model, error)
    public static Model Get(string name, Input<string> id, ModelState? state, CustomResourceOptions? opts = null)
    public static Model get(String name, Output<String> id, ModelState state, CustomResourceOptions options)
    Resource lookup is not supported in YAML
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    ArtifactContentDisposition string
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    ArtifactContentLength string

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    ArtifactContentMd5 string
    ArtifactLastModified string
    BackupOperationDetails List<ModelBackupOperationDetail>
    Backup operation details of the model.
    BackupSetting ModelBackupSetting
    (Updatable) Back up setting details of the model.
    CompartmentId string
    (Updatable) The OCID of the compartment to create the model in.
    CreatedBy string
    The OCID of the user who created the model.
    CustomMetadataLists List<ModelCustomMetadataList>
    (Updatable) An array of custom metadata details for the model.
    DefinedMetadataLists List<ModelDefinedMetadataList>
    (Updatable) An array of defined metadata details for the model.
    DefinedTags Dictionary<string, string>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    Description string
    (Updatable) A short description of the model.
    DisplayName string
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    EmptyModel bool
    FreeformTags Dictionary<string, string>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    InputSchema string
    Input schema file content in String format
    LifecycleDetails string
    Details about the lifecycle state of the model.
    ModelArtifact string
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    ModelVersionSetId string
    The OCID of the model version set that the model is associated to.
    ModelVersionSetName string
    The name of the model version set that the model is associated to.
    OutputSchema string
    Output schema file content in String format
    ProjectId string
    The OCID of the project to associate with the model.
    RetentionOperationDetails List<ModelRetentionOperationDetail>
    Retention operation details for the model.
    RetentionSetting ModelRetentionSetting
    (Updatable) Retention setting details of the model.
    State string
    The state of the model.
    TimeCreated string
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    VersionLabel string
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    ArtifactContentDisposition string
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    ArtifactContentLength string

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    ArtifactContentMd5 string
    ArtifactLastModified string
    BackupOperationDetails []ModelBackupOperationDetailArgs
    Backup operation details of the model.
    BackupSetting ModelBackupSettingArgs
    (Updatable) Back up setting details of the model.
    CompartmentId string
    (Updatable) The OCID of the compartment to create the model in.
    CreatedBy string
    The OCID of the user who created the model.
    CustomMetadataLists []ModelCustomMetadataListArgs
    (Updatable) An array of custom metadata details for the model.
    DefinedMetadataLists []ModelDefinedMetadataListArgs
    (Updatable) An array of defined metadata details for the model.
    DefinedTags map[string]string
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    Description string
    (Updatable) A short description of the model.
    DisplayName string
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    EmptyModel bool
    FreeformTags map[string]string
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    InputSchema string
    Input schema file content in String format
    LifecycleDetails string
    Details about the lifecycle state of the model.
    ModelArtifact string
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    ModelVersionSetId string
    The OCID of the model version set that the model is associated to.
    ModelVersionSetName string
    The name of the model version set that the model is associated to.
    OutputSchema string
    Output schema file content in String format
    ProjectId string
    The OCID of the project to associate with the model.
    RetentionOperationDetails []ModelRetentionOperationDetailArgs
    Retention operation details for the model.
    RetentionSetting ModelRetentionSettingArgs
    (Updatable) Retention setting details of the model.
    State string
    The state of the model.
    TimeCreated string
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    VersionLabel string
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    artifactContentDisposition String
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    artifactContentLength String

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    artifactContentMd5 String
    artifactLastModified String
    backupOperationDetails List<ModelBackupOperationDetail>
    Backup operation details of the model.
    backupSetting ModelBackupSetting
    (Updatable) Back up setting details of the model.
    compartmentId String
    (Updatable) The OCID of the compartment to create the model in.
    createdBy String
    The OCID of the user who created the model.
    customMetadataLists List<ModelCustomMetadataList>
    (Updatable) An array of custom metadata details for the model.
    definedMetadataLists List<ModelDefinedMetadataList>
    (Updatable) An array of defined metadata details for the model.
    definedTags Map<String,String>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description String
    (Updatable) A short description of the model.
    displayName String
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    emptyModel Boolean
    freeformTags Map<String,String>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    inputSchema String
    Input schema file content in String format
    lifecycleDetails String
    Details about the lifecycle state of the model.
    modelArtifact String
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    modelVersionSetId String
    The OCID of the model version set that the model is associated to.
    modelVersionSetName String
    The name of the model version set that the model is associated to.
    outputSchema String
    Output schema file content in String format
    projectId String
    The OCID of the project to associate with the model.
    retentionOperationDetails List<ModelRetentionOperationDetail>
    Retention operation details for the model.
    retentionSetting ModelRetentionSetting
    (Updatable) Retention setting details of the model.
    state String
    The state of the model.
    timeCreated String
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    versionLabel String
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    artifactContentDisposition string
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    artifactContentLength string

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    artifactContentMd5 string
    artifactLastModified string
    backupOperationDetails ModelBackupOperationDetail[]
    Backup operation details of the model.
    backupSetting ModelBackupSetting
    (Updatable) Back up setting details of the model.
    compartmentId string
    (Updatable) The OCID of the compartment to create the model in.
    createdBy string
    The OCID of the user who created the model.
    customMetadataLists ModelCustomMetadataList[]
    (Updatable) An array of custom metadata details for the model.
    definedMetadataLists ModelDefinedMetadataList[]
    (Updatable) An array of defined metadata details for the model.
    definedTags {[key: string]: string}
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description string
    (Updatable) A short description of the model.
    displayName string
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    emptyModel boolean
    freeformTags {[key: string]: string}
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    inputSchema string
    Input schema file content in String format
    lifecycleDetails string
    Details about the lifecycle state of the model.
    modelArtifact string
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    modelVersionSetId string
    The OCID of the model version set that the model is associated to.
    modelVersionSetName string
    The name of the model version set that the model is associated to.
    outputSchema string
    Output schema file content in String format
    projectId string
    The OCID of the project to associate with the model.
    retentionOperationDetails ModelRetentionOperationDetail[]
    Retention operation details for the model.
    retentionSetting ModelRetentionSetting
    (Updatable) Retention setting details of the model.
    state string
    The state of the model.
    timeCreated string
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    versionLabel string
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    artifact_content_disposition str
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    artifact_content_length str

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    artifact_content_md5 str
    artifact_last_modified str
    backup_operation_details Sequence[datascience.ModelBackupOperationDetailArgs]
    Backup operation details of the model.
    backup_setting datascience.ModelBackupSettingArgs
    (Updatable) Back up setting details of the model.
    compartment_id str
    (Updatable) The OCID of the compartment to create the model in.
    created_by str
    The OCID of the user who created the model.
    custom_metadata_lists Sequence[datascience.ModelCustomMetadataListArgs]
    (Updatable) An array of custom metadata details for the model.
    defined_metadata_lists Sequence[datascience.ModelDefinedMetadataListArgs]
    (Updatable) An array of defined metadata details for the model.
    defined_tags Mapping[str, str]
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description str
    (Updatable) A short description of the model.
    display_name str
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    empty_model bool
    freeform_tags Mapping[str, str]
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    input_schema str
    Input schema file content in String format
    lifecycle_details str
    Details about the lifecycle state of the model.
    model_artifact str
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    model_version_set_id str
    The OCID of the model version set that the model is associated to.
    model_version_set_name str
    The name of the model version set that the model is associated to.
    output_schema str
    Output schema file content in String format
    project_id str
    The OCID of the project to associate with the model.
    retention_operation_details Sequence[datascience.ModelRetentionOperationDetailArgs]
    Retention operation details for the model.
    retention_setting datascience.ModelRetentionSettingArgs
    (Updatable) Retention setting details of the model.
    state str
    The state of the model.
    time_created str
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    version_label str
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.
    artifactContentDisposition String
    This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip
    artifactContentLength String

    The content length of the model_artifact.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    artifactContentMd5 String
    artifactLastModified String
    backupOperationDetails List<Property Map>
    Backup operation details of the model.
    backupSetting Property Map
    (Updatable) Back up setting details of the model.
    compartmentId String
    (Updatable) The OCID of the compartment to create the model in.
    createdBy String
    The OCID of the user who created the model.
    customMetadataLists List<Property Map>
    (Updatable) An array of custom metadata details for the model.
    definedMetadataLists List<Property Map>
    (Updatable) An array of defined metadata details for the model.
    definedTags Map<String>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description String
    (Updatable) A short description of the model.
    displayName String
    (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model
    emptyModel Boolean
    freeformTags Map<String>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    inputSchema String
    Input schema file content in String format
    lifecycleDetails String
    Details about the lifecycle state of the model.
    modelArtifact String
    The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in "Creating" state until its artifact is uploaded.
    modelVersionSetId String
    The OCID of the model version set that the model is associated to.
    modelVersionSetName String
    The name of the model version set that the model is associated to.
    outputSchema String
    Output schema file content in String format
    projectId String
    The OCID of the project to associate with the model.
    retentionOperationDetails List<Property Map>
    Retention operation details for the model.
    retentionSetting Property Map
    (Updatable) Retention setting details of the model.
    state String
    The state of the model.
    timeCreated String
    The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    versionLabel String
    (Updatable) The version label can add an additional description of the lifecycle state of the model or the application using/training the model.

    Supporting Types

    ModelBackupOperationDetail, ModelBackupOperationDetailArgs

    BackupState string
    The backup status of the model.
    BackupStateDetails string
    The backup execution status details of the model.
    TimeLastBackup string
    The last backup execution time of the model.
    BackupState string
    The backup status of the model.
    BackupStateDetails string
    The backup execution status details of the model.
    TimeLastBackup string
    The last backup execution time of the model.
    backupState String
    The backup status of the model.
    backupStateDetails String
    The backup execution status details of the model.
    timeLastBackup String
    The last backup execution time of the model.
    backupState string
    The backup status of the model.
    backupStateDetails string
    The backup execution status details of the model.
    timeLastBackup string
    The last backup execution time of the model.
    backup_state str
    The backup status of the model.
    backup_state_details str
    The backup execution status details of the model.
    time_last_backup str
    The last backup execution time of the model.
    backupState String
    The backup status of the model.
    backupStateDetails String
    The backup execution status details of the model.
    timeLastBackup String
    The last backup execution time of the model.

    ModelBackupSetting, ModelBackupSettingArgs

    BackupRegion string
    (Updatable) Oracle Cloud Infrastructure backup region for the model.
    IsBackupEnabled bool
    (Updatable) Boolean flag representing whether backup needs to be enabled/disabled for the model.
    CustomerNotificationType string
    (Updatable) Customer notification on backup success/failure events.
    BackupRegion string
    (Updatable) Oracle Cloud Infrastructure backup region for the model.
    IsBackupEnabled bool
    (Updatable) Boolean flag representing whether backup needs to be enabled/disabled for the model.
    CustomerNotificationType string
    (Updatable) Customer notification on backup success/failure events.
    backupRegion String
    (Updatable) Oracle Cloud Infrastructure backup region for the model.
    isBackupEnabled Boolean
    (Updatable) Boolean flag representing whether backup needs to be enabled/disabled for the model.
    customerNotificationType String
    (Updatable) Customer notification on backup success/failure events.
    backupRegion string
    (Updatable) Oracle Cloud Infrastructure backup region for the model.
    isBackupEnabled boolean
    (Updatable) Boolean flag representing whether backup needs to be enabled/disabled for the model.
    customerNotificationType string
    (Updatable) Customer notification on backup success/failure events.
    backup_region str
    (Updatable) Oracle Cloud Infrastructure backup region for the model.
    is_backup_enabled bool
    (Updatable) Boolean flag representing whether backup needs to be enabled/disabled for the model.
    customer_notification_type str
    (Updatable) Customer notification on backup success/failure events.
    backupRegion String
    (Updatable) Oracle Cloud Infrastructure backup region for the model.
    isBackupEnabled Boolean
    (Updatable) Boolean flag representing whether backup needs to be enabled/disabled for the model.
    customerNotificationType String
    (Updatable) Customer notification on backup success/failure events.

    ModelCustomMetadataList, ModelCustomMetadataListArgs

    Category string
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    Description string
    (Updatable) Description of model metadata
    Key string
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    Value string

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    Category string
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    Description string
    (Updatable) Description of model metadata
    Key string
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    Value string

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    category String
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    description String
    (Updatable) Description of model metadata
    key String
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    value String

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    category string
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    description string
    (Updatable) Description of model metadata
    key string
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    value string

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    category str
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    description str
    (Updatable) Description of model metadata
    key str
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    value str

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    category String
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    description String
    (Updatable) Description of model metadata
    key String
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    value String

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    ModelDefinedMetadataList, ModelDefinedMetadataListArgs

    Category string
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    Description string
    (Updatable) Description of model metadata
    Key string
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    Value string

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    Category string
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    Description string
    (Updatable) Description of model metadata
    Key string
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    Value string

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    category String
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    description String
    (Updatable) Description of model metadata
    key String
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    value String

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    category string
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    description string
    (Updatable) Description of model metadata
    key string
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    value string

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    category str
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    description str
    (Updatable) Description of model metadata
    key str
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    value str

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    category String
    (Updatable) Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values "Performance,Training Profile,Training and Validation Datasets,Training Environment,other".
    description String
    (Updatable) Description of model metadata
    key String
    (Updatable) Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults
    value String

    (Updatable) Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

    ModelRetentionOperationDetail, ModelRetentionOperationDetailArgs

    ArchiveState string
    The archival status of model.
    ArchiveStateDetails string
    The archival state details of the model.
    DeleteState string
    The deletion status of the archived model.
    DeleteStateDetails string
    The deletion status details of the archived model.
    TimeArchivalScheduled string
    The estimated archival time of the model based on the provided retention setting.
    TimeDeletionScheduled string
    The estimated deletion time of the model based on the provided retention setting.
    ArchiveState string
    The archival status of model.
    ArchiveStateDetails string
    The archival state details of the model.
    DeleteState string
    The deletion status of the archived model.
    DeleteStateDetails string
    The deletion status details of the archived model.
    TimeArchivalScheduled string
    The estimated archival time of the model based on the provided retention setting.
    TimeDeletionScheduled string
    The estimated deletion time of the model based on the provided retention setting.
    archiveState String
    The archival status of model.
    archiveStateDetails String
    The archival state details of the model.
    deleteState String
    The deletion status of the archived model.
    deleteStateDetails String
    The deletion status details of the archived model.
    timeArchivalScheduled String
    The estimated archival time of the model based on the provided retention setting.
    timeDeletionScheduled String
    The estimated deletion time of the model based on the provided retention setting.
    archiveState string
    The archival status of model.
    archiveStateDetails string
    The archival state details of the model.
    deleteState string
    The deletion status of the archived model.
    deleteStateDetails string
    The deletion status details of the archived model.
    timeArchivalScheduled string
    The estimated archival time of the model based on the provided retention setting.
    timeDeletionScheduled string
    The estimated deletion time of the model based on the provided retention setting.
    archive_state str
    The archival status of model.
    archive_state_details str
    The archival state details of the model.
    delete_state str
    The deletion status of the archived model.
    delete_state_details str
    The deletion status details of the archived model.
    time_archival_scheduled str
    The estimated archival time of the model based on the provided retention setting.
    time_deletion_scheduled str
    The estimated deletion time of the model based on the provided retention setting.
    archiveState String
    The archival status of model.
    archiveStateDetails String
    The archival state details of the model.
    deleteState String
    The deletion status of the archived model.
    deleteStateDetails String
    The deletion status details of the archived model.
    timeArchivalScheduled String
    The estimated archival time of the model based on the provided retention setting.
    timeDeletionScheduled String
    The estimated deletion time of the model based on the provided retention setting.

    ModelRetentionSetting, ModelRetentionSettingArgs

    ArchiveAfterDays int
    (Updatable) Number of days after which the model will be archived.
    CustomerNotificationType string
    (Updatable) Customer notification options on success/failure of archival, deletion events.
    DeleteAfterDays int
    (Updatable) Number of days after which the archived model will be deleted.
    ArchiveAfterDays int
    (Updatable) Number of days after which the model will be archived.
    CustomerNotificationType string
    (Updatable) Customer notification options on success/failure of archival, deletion events.
    DeleteAfterDays int
    (Updatable) Number of days after which the archived model will be deleted.
    archiveAfterDays Integer
    (Updatable) Number of days after which the model will be archived.
    customerNotificationType String
    (Updatable) Customer notification options on success/failure of archival, deletion events.
    deleteAfterDays Integer
    (Updatable) Number of days after which the archived model will be deleted.
    archiveAfterDays number
    (Updatable) Number of days after which the model will be archived.
    customerNotificationType string
    (Updatable) Customer notification options on success/failure of archival, deletion events.
    deleteAfterDays number
    (Updatable) Number of days after which the archived model will be deleted.
    archive_after_days int
    (Updatable) Number of days after which the model will be archived.
    customer_notification_type str
    (Updatable) Customer notification options on success/failure of archival, deletion events.
    delete_after_days int
    (Updatable) Number of days after which the archived model will be deleted.
    archiveAfterDays Number
    (Updatable) Number of days after which the model will be archived.
    customerNotificationType String
    (Updatable) Customer notification options on success/failure of archival, deletion events.
    deleteAfterDays Number
    (Updatable) Number of days after which the archived model will be deleted.

    Import

    Models can be imported using the id, e.g.

    $ pulumi import oci:DataScience/model:Model test_model "id"
    

    To learn more about importing existing cloud resources, see Importing resources.

    Package Details

    Repository
    oci pulumi/pulumi-oci
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the oci Terraform Provider.
    oci logo
    Oracle Cloud Infrastructure v2.17.0 published on Friday, Nov 15, 2024 by Pulumi