1. Packages
  2. Oracle Cloud Infrastructure
  3. API Docs
  4. AiVision
  5. getModels
Oracle Cloud Infrastructure v1.40.0 published on Wednesday, Jun 12, 2024 by Pulumi

oci.AiVision.getModels

Explore with Pulumi AI

oci logo
Oracle Cloud Infrastructure v1.40.0 published on Wednesday, Jun 12, 2024 by Pulumi

    This data source provides the list of Models in Oracle Cloud Infrastructure Ai Vision service.

    Returns a list of Models.

    Example Usage

    import * as pulumi from "@pulumi/pulumi";
    import * as oci from "@pulumi/oci";
    
    const testModels = oci.AiVision.getModels({
        compartmentId: compartmentId,
        displayName: modelDisplayName,
        id: modelId,
        projectId: testProject.id,
        state: modelState,
    });
    
    import pulumi
    import pulumi_oci as oci
    
    test_models = oci.AiVision.get_models(compartment_id=compartment_id,
        display_name=model_display_name,
        id=model_id,
        project_id=test_project["id"],
        state=model_state)
    
    package main
    
    import (
    	"github.com/pulumi/pulumi-oci/sdk/go/oci/AiVision"
    	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
    )
    
    func main() {
    	pulumi.Run(func(ctx *pulumi.Context) error {
    		_, err := AiVision.GetModels(ctx, &aivision.GetModelsArgs{
    			CompartmentId: pulumi.StringRef(compartmentId),
    			DisplayName:   pulumi.StringRef(modelDisplayName),
    			Id:            pulumi.StringRef(modelId),
    			ProjectId:     pulumi.StringRef(testProject.Id),
    			State:         pulumi.StringRef(modelState),
    		}, nil)
    		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 testModels = Oci.AiVision.GetModels.Invoke(new()
        {
            CompartmentId = compartmentId,
            DisplayName = modelDisplayName,
            Id = modelId,
            ProjectId = testProject.Id,
            State = modelState,
        });
    
    });
    
    package generated_program;
    
    import com.pulumi.Context;
    import com.pulumi.Pulumi;
    import com.pulumi.core.Output;
    import com.pulumi.oci.AiVision.AiVisionFunctions;
    import com.pulumi.oci.AiVision.inputs.GetModelsArgs;
    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) {
            final var testModels = AiVisionFunctions.getModels(GetModelsArgs.builder()
                .compartmentId(compartmentId)
                .displayName(modelDisplayName)
                .id(modelId)
                .projectId(testProject.id())
                .state(modelState)
                .build());
    
        }
    }
    
    variables:
      testModels:
        fn::invoke:
          Function: oci:AiVision:getModels
          Arguments:
            compartmentId: ${compartmentId}
            displayName: ${modelDisplayName}
            id: ${modelId}
            projectId: ${testProject.id}
            state: ${modelState}
    

    Using getModels

    Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.

    function getModels(args: GetModelsArgs, opts?: InvokeOptions): Promise<GetModelsResult>
    function getModelsOutput(args: GetModelsOutputArgs, opts?: InvokeOptions): Output<GetModelsResult>
    def get_models(compartment_id: Optional[str] = None,
                   display_name: Optional[str] = None,
                   filters: Optional[Sequence[_aivision.GetModelsFilter]] = None,
                   id: Optional[str] = None,
                   project_id: Optional[str] = None,
                   state: Optional[str] = None,
                   opts: Optional[InvokeOptions] = None) -> GetModelsResult
    def get_models_output(compartment_id: Optional[pulumi.Input[str]] = None,
                   display_name: Optional[pulumi.Input[str]] = None,
                   filters: Optional[pulumi.Input[Sequence[pulumi.Input[_aivision.GetModelsFilterArgs]]]] = None,
                   id: Optional[pulumi.Input[str]] = None,
                   project_id: Optional[pulumi.Input[str]] = None,
                   state: Optional[pulumi.Input[str]] = None,
                   opts: Optional[InvokeOptions] = None) -> Output[GetModelsResult]
    func GetModels(ctx *Context, args *GetModelsArgs, opts ...InvokeOption) (*GetModelsResult, error)
    func GetModelsOutput(ctx *Context, args *GetModelsOutputArgs, opts ...InvokeOption) GetModelsResultOutput

    > Note: This function is named GetModels in the Go SDK.

    public static class GetModels 
    {
        public static Task<GetModelsResult> InvokeAsync(GetModelsArgs args, InvokeOptions? opts = null)
        public static Output<GetModelsResult> Invoke(GetModelsInvokeArgs args, InvokeOptions? opts = null)
    }
    public static CompletableFuture<GetModelsResult> getModels(GetModelsArgs args, InvokeOptions options)
    // Output-based functions aren't available in Java yet
    
    fn::invoke:
      function: oci:AiVision/getModels:getModels
      arguments:
        # arguments dictionary

    The following arguments are supported:

    CompartmentId string
    The ID of the compartment in which to list resources.
    DisplayName string
    A filter to return only resources that match the entire display name given.
    Filters List<GetModelsFilter>
    Id string
    unique Model identifier
    ProjectId string
    The ID of the project for which to list the objects.
    State string
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    CompartmentId string
    The ID of the compartment in which to list resources.
    DisplayName string
    A filter to return only resources that match the entire display name given.
    Filters []GetModelsFilter
    Id string
    unique Model identifier
    ProjectId string
    The ID of the project for which to list the objects.
    State string
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    compartmentId String
    The ID of the compartment in which to list resources.
    displayName String
    A filter to return only resources that match the entire display name given.
    filters List<GetModelsFilter>
    id String
    unique Model identifier
    projectId String
    The ID of the project for which to list the objects.
    state String
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    compartmentId string
    The ID of the compartment in which to list resources.
    displayName string
    A filter to return only resources that match the entire display name given.
    filters GetModelsFilter[]
    id string
    unique Model identifier
    projectId string
    The ID of the project for which to list the objects.
    state string
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    compartment_id str
    The ID of the compartment in which to list resources.
    display_name str
    A filter to return only resources that match the entire display name given.
    filters Sequence[aivision.GetModelsFilter]
    id str
    unique Model identifier
    project_id str
    The ID of the project for which to list the objects.
    state str
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    compartmentId String
    The ID of the compartment in which to list resources.
    displayName String
    A filter to return only resources that match the entire display name given.
    filters List<Property Map>
    id String
    unique Model identifier
    projectId String
    The ID of the project for which to list the objects.
    state String
    A filter to return only resources their lifecycleState matches the given lifecycleState.

    getModels Result

    The following output properties are available:

    ModelCollections List<GetModelsModelCollection>
    The list of model_collection.
    CompartmentId string
    Compartment Identifier
    DisplayName string
    Model Identifier, can be renamed
    Filters List<GetModelsFilter>
    Id string
    Unique identifier that is immutable on creation
    ProjectId string
    The OCID of the project to associate with the model.
    State string
    The current state of the Model.
    ModelCollections []GetModelsModelCollection
    The list of model_collection.
    CompartmentId string
    Compartment Identifier
    DisplayName string
    Model Identifier, can be renamed
    Filters []GetModelsFilter
    Id string
    Unique identifier that is immutable on creation
    ProjectId string
    The OCID of the project to associate with the model.
    State string
    The current state of the Model.
    modelCollections List<GetModelsModelCollection>
    The list of model_collection.
    compartmentId String
    Compartment Identifier
    displayName String
    Model Identifier, can be renamed
    filters List<GetModelsFilter>
    id String
    Unique identifier that is immutable on creation
    projectId String
    The OCID of the project to associate with the model.
    state String
    The current state of the Model.
    modelCollections GetModelsModelCollection[]
    The list of model_collection.
    compartmentId string
    Compartment Identifier
    displayName string
    Model Identifier, can be renamed
    filters GetModelsFilter[]
    id string
    Unique identifier that is immutable on creation
    projectId string
    The OCID of the project to associate with the model.
    state string
    The current state of the Model.
    model_collections Sequence[aivision.GetModelsModelCollection]
    The list of model_collection.
    compartment_id str
    Compartment Identifier
    display_name str
    Model Identifier, can be renamed
    filters Sequence[aivision.GetModelsFilter]
    id str
    Unique identifier that is immutable on creation
    project_id str
    The OCID of the project to associate with the model.
    state str
    The current state of the Model.
    modelCollections List<Property Map>
    The list of model_collection.
    compartmentId String
    Compartment Identifier
    displayName String
    Model Identifier, can be renamed
    filters List<Property Map>
    id String
    Unique identifier that is immutable on creation
    projectId String
    The OCID of the project to associate with the model.
    state String
    The current state of the Model.

    Supporting Types

    GetModelsFilter

    Name string
    Values List<string>
    Regex bool
    Name string
    Values []string
    Regex bool
    name String
    values List<String>
    regex Boolean
    name string
    values string[]
    regex boolean
    name str
    values Sequence[str]
    regex bool
    name String
    values List<String>
    regex Boolean

    GetModelsModelCollection

    GetModelsModelCollectionItem

    AveragePrecision double
    Average precision of the trained model
    CompartmentId string
    The ID of the compartment in which to list resources.
    ConfidenceThreshold double
    Confidence ratio of the calculation
    DefinedTags Dictionary<string, object>
    Defined tags for this resource. Each key is predefined and scoped to a namespace. Example: {"foo-namespace.bar-key": "value"}
    Description string
    A short description of the model.
    DisplayName string
    A filter to return only resources that match the entire display name given.
    FreeformTags Dictionary<string, object>
    Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: {"bar-key": "value"}
    Id string
    unique Model identifier
    IsQuickMode bool
    If It's true, Training is set for recommended epochs needed for quick training.
    LifecycleDetails string
    A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
    MaxTrainingDurationInHours double
    The maximum duration in hours for which the training will run.
    Metrics string
    Complete Training Metrics for successful trained model
    ModelType string
    Type of the Model.
    ModelVersion string
    The version of the model
    Precision double
    Precision of the trained model
    ProjectId string
    The ID of the project for which to list the objects.
    Recall double
    Recall of the trained model
    State string
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    SystemTags Dictionary<string, object>
    Usage of system tag keys. These predefined keys are scoped to namespaces. Example: {"orcl-cloud.free-tier-retained": "true"}
    TestImageCount int
    Total number of testing Images
    TestingDatasets List<GetModelsModelCollectionItemTestingDataset>
    The base entity for a Dataset, which is the input for Model creation.
    TimeCreated string
    The time the Model was created. An RFC3339 formatted datetime string
    TimeUpdated string
    The time the Model was updated. An RFC3339 formatted datetime string
    TotalImageCount int
    Total number of training Images
    TrainedDurationInHours double
    Total hours actually used for training
    TrainingDatasets List<GetModelsModelCollectionItemTrainingDataset>
    The base entity for a Dataset, which is the input for Model creation.
    ValidationDatasets List<GetModelsModelCollectionItemValidationDataset>
    The base entity for a Dataset, which is the input for Model creation.
    AveragePrecision float64
    Average precision of the trained model
    CompartmentId string
    The ID of the compartment in which to list resources.
    ConfidenceThreshold float64
    Confidence ratio of the calculation
    DefinedTags map[string]interface{}
    Defined tags for this resource. Each key is predefined and scoped to a namespace. Example: {"foo-namespace.bar-key": "value"}
    Description string
    A short description of the model.
    DisplayName string
    A filter to return only resources that match the entire display name given.
    FreeformTags map[string]interface{}
    Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: {"bar-key": "value"}
    Id string
    unique Model identifier
    IsQuickMode bool
    If It's true, Training is set for recommended epochs needed for quick training.
    LifecycleDetails string
    A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
    MaxTrainingDurationInHours float64
    The maximum duration in hours for which the training will run.
    Metrics string
    Complete Training Metrics for successful trained model
    ModelType string
    Type of the Model.
    ModelVersion string
    The version of the model
    Precision float64
    Precision of the trained model
    ProjectId string
    The ID of the project for which to list the objects.
    Recall float64
    Recall of the trained model
    State string
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    SystemTags map[string]interface{}
    Usage of system tag keys. These predefined keys are scoped to namespaces. Example: {"orcl-cloud.free-tier-retained": "true"}
    TestImageCount int
    Total number of testing Images
    TestingDatasets []GetModelsModelCollectionItemTestingDataset
    The base entity for a Dataset, which is the input for Model creation.
    TimeCreated string
    The time the Model was created. An RFC3339 formatted datetime string
    TimeUpdated string
    The time the Model was updated. An RFC3339 formatted datetime string
    TotalImageCount int
    Total number of training Images
    TrainedDurationInHours float64
    Total hours actually used for training
    TrainingDatasets []GetModelsModelCollectionItemTrainingDataset
    The base entity for a Dataset, which is the input for Model creation.
    ValidationDatasets []GetModelsModelCollectionItemValidationDataset
    The base entity for a Dataset, which is the input for Model creation.
    averagePrecision Double
    Average precision of the trained model
    compartmentId String
    The ID of the compartment in which to list resources.
    confidenceThreshold Double
    Confidence ratio of the calculation
    definedTags Map<String,Object>
    Defined tags for this resource. Each key is predefined and scoped to a namespace. Example: {"foo-namespace.bar-key": "value"}
    description String
    A short description of the model.
    displayName String
    A filter to return only resources that match the entire display name given.
    freeformTags Map<String,Object>
    Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: {"bar-key": "value"}
    id String
    unique Model identifier
    isQuickMode Boolean
    If It's true, Training is set for recommended epochs needed for quick training.
    lifecycleDetails String
    A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
    maxTrainingDurationInHours Double
    The maximum duration in hours for which the training will run.
    metrics String
    Complete Training Metrics for successful trained model
    modelType String
    Type of the Model.
    modelVersion String
    The version of the model
    precision Double
    Precision of the trained model
    projectId String
    The ID of the project for which to list the objects.
    recall Double
    Recall of the trained model
    state String
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    systemTags Map<String,Object>
    Usage of system tag keys. These predefined keys are scoped to namespaces. Example: {"orcl-cloud.free-tier-retained": "true"}
    testImageCount Integer
    Total number of testing Images
    testingDatasets List<GetModelsModelCollectionItemTestingDataset>
    The base entity for a Dataset, which is the input for Model creation.
    timeCreated String
    The time the Model was created. An RFC3339 formatted datetime string
    timeUpdated String
    The time the Model was updated. An RFC3339 formatted datetime string
    totalImageCount Integer
    Total number of training Images
    trainedDurationInHours Double
    Total hours actually used for training
    trainingDatasets List<GetModelsModelCollectionItemTrainingDataset>
    The base entity for a Dataset, which is the input for Model creation.
    validationDatasets List<GetModelsModelCollectionItemValidationDataset>
    The base entity for a Dataset, which is the input for Model creation.
    averagePrecision number
    Average precision of the trained model
    compartmentId string
    The ID of the compartment in which to list resources.
    confidenceThreshold number
    Confidence ratio of the calculation
    definedTags {[key: string]: any}
    Defined tags for this resource. Each key is predefined and scoped to a namespace. Example: {"foo-namespace.bar-key": "value"}
    description string
    A short description of the model.
    displayName string
    A filter to return only resources that match the entire display name given.
    freeformTags {[key: string]: any}
    Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: {"bar-key": "value"}
    id string
    unique Model identifier
    isQuickMode boolean
    If It's true, Training is set for recommended epochs needed for quick training.
    lifecycleDetails string
    A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
    maxTrainingDurationInHours number
    The maximum duration in hours for which the training will run.
    metrics string
    Complete Training Metrics for successful trained model
    modelType string
    Type of the Model.
    modelVersion string
    The version of the model
    precision number
    Precision of the trained model
    projectId string
    The ID of the project for which to list the objects.
    recall number
    Recall of the trained model
    state string
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    systemTags {[key: string]: any}
    Usage of system tag keys. These predefined keys are scoped to namespaces. Example: {"orcl-cloud.free-tier-retained": "true"}
    testImageCount number
    Total number of testing Images
    testingDatasets GetModelsModelCollectionItemTestingDataset[]
    The base entity for a Dataset, which is the input for Model creation.
    timeCreated string
    The time the Model was created. An RFC3339 formatted datetime string
    timeUpdated string
    The time the Model was updated. An RFC3339 formatted datetime string
    totalImageCount number
    Total number of training Images
    trainedDurationInHours number
    Total hours actually used for training
    trainingDatasets GetModelsModelCollectionItemTrainingDataset[]
    The base entity for a Dataset, which is the input for Model creation.
    validationDatasets GetModelsModelCollectionItemValidationDataset[]
    The base entity for a Dataset, which is the input for Model creation.
    average_precision float
    Average precision of the trained model
    compartment_id str
    The ID of the compartment in which to list resources.
    confidence_threshold float
    Confidence ratio of the calculation
    defined_tags Mapping[str, Any]
    Defined tags for this resource. Each key is predefined and scoped to a namespace. Example: {"foo-namespace.bar-key": "value"}
    description str
    A short description of the model.
    display_name str
    A filter to return only resources that match the entire display name given.
    freeform_tags Mapping[str, Any]
    Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: {"bar-key": "value"}
    id str
    unique Model identifier
    is_quick_mode bool
    If It's true, Training is set for recommended epochs needed for quick training.
    lifecycle_details str
    A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
    max_training_duration_in_hours float
    The maximum duration in hours for which the training will run.
    metrics str
    Complete Training Metrics for successful trained model
    model_type str
    Type of the Model.
    model_version str
    The version of the model
    precision float
    Precision of the trained model
    project_id str
    The ID of the project for which to list the objects.
    recall float
    Recall of the trained model
    state str
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    system_tags Mapping[str, Any]
    Usage of system tag keys. These predefined keys are scoped to namespaces. Example: {"orcl-cloud.free-tier-retained": "true"}
    test_image_count int
    Total number of testing Images
    testing_datasets Sequence[aivision.GetModelsModelCollectionItemTestingDataset]
    The base entity for a Dataset, which is the input for Model creation.
    time_created str
    The time the Model was created. An RFC3339 formatted datetime string
    time_updated str
    The time the Model was updated. An RFC3339 formatted datetime string
    total_image_count int
    Total number of training Images
    trained_duration_in_hours float
    Total hours actually used for training
    training_datasets Sequence[aivision.GetModelsModelCollectionItemTrainingDataset]
    The base entity for a Dataset, which is the input for Model creation.
    validation_datasets Sequence[aivision.GetModelsModelCollectionItemValidationDataset]
    The base entity for a Dataset, which is the input for Model creation.
    averagePrecision Number
    Average precision of the trained model
    compartmentId String
    The ID of the compartment in which to list resources.
    confidenceThreshold Number
    Confidence ratio of the calculation
    definedTags Map<Any>
    Defined tags for this resource. Each key is predefined and scoped to a namespace. Example: {"foo-namespace.bar-key": "value"}
    description String
    A short description of the model.
    displayName String
    A filter to return only resources that match the entire display name given.
    freeformTags Map<Any>
    Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: {"bar-key": "value"}
    id String
    unique Model identifier
    isQuickMode Boolean
    If It's true, Training is set for recommended epochs needed for quick training.
    lifecycleDetails String
    A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
    maxTrainingDurationInHours Number
    The maximum duration in hours for which the training will run.
    metrics String
    Complete Training Metrics for successful trained model
    modelType String
    Type of the Model.
    modelVersion String
    The version of the model
    precision Number
    Precision of the trained model
    projectId String
    The ID of the project for which to list the objects.
    recall Number
    Recall of the trained model
    state String
    A filter to return only resources their lifecycleState matches the given lifecycleState.
    systemTags Map<Any>
    Usage of system tag keys. These predefined keys are scoped to namespaces. Example: {"orcl-cloud.free-tier-retained": "true"}
    testImageCount Number
    Total number of testing Images
    testingDatasets List<Property Map>
    The base entity for a Dataset, which is the input for Model creation.
    timeCreated String
    The time the Model was created. An RFC3339 formatted datetime string
    timeUpdated String
    The time the Model was updated. An RFC3339 formatted datetime string
    totalImageCount Number
    Total number of training Images
    trainedDurationInHours Number
    Total hours actually used for training
    trainingDatasets List<Property Map>
    The base entity for a Dataset, which is the input for Model creation.
    validationDatasets List<Property Map>
    The base entity for a Dataset, which is the input for Model creation.

    GetModelsModelCollectionItemTestingDataset

    Bucket string
    The name of the ObjectStorage bucket that contains the input data file.
    DatasetId string
    The OCID of the Data Science Labeling Dataset.
    DatasetType string
    Type of the Dataset.
    NamespaceName string
    Object string
    The object name of the input data file.
    Bucket string
    The name of the ObjectStorage bucket that contains the input data file.
    DatasetId string
    The OCID of the Data Science Labeling Dataset.
    DatasetType string
    Type of the Dataset.
    NamespaceName string
    Object string
    The object name of the input data file.
    bucket String
    The name of the ObjectStorage bucket that contains the input data file.
    datasetId String
    The OCID of the Data Science Labeling Dataset.
    datasetType String
    Type of the Dataset.
    namespaceName String
    object String
    The object name of the input data file.
    bucket string
    The name of the ObjectStorage bucket that contains the input data file.
    datasetId string
    The OCID of the Data Science Labeling Dataset.
    datasetType string
    Type of the Dataset.
    namespaceName string
    object string
    The object name of the input data file.
    bucket str
    The name of the ObjectStorage bucket that contains the input data file.
    dataset_id str
    The OCID of the Data Science Labeling Dataset.
    dataset_type str
    Type of the Dataset.
    namespace_name str
    object str
    The object name of the input data file.
    bucket String
    The name of the ObjectStorage bucket that contains the input data file.
    datasetId String
    The OCID of the Data Science Labeling Dataset.
    datasetType String
    Type of the Dataset.
    namespaceName String
    object String
    The object name of the input data file.

    GetModelsModelCollectionItemTrainingDataset

    Bucket string
    The name of the ObjectStorage bucket that contains the input data file.
    DatasetId string
    The OCID of the Data Science Labeling Dataset.
    DatasetType string
    Type of the Dataset.
    NamespaceName string
    Object string
    The object name of the input data file.
    Bucket string
    The name of the ObjectStorage bucket that contains the input data file.
    DatasetId string
    The OCID of the Data Science Labeling Dataset.
    DatasetType string
    Type of the Dataset.
    NamespaceName string
    Object string
    The object name of the input data file.
    bucket String
    The name of the ObjectStorage bucket that contains the input data file.
    datasetId String
    The OCID of the Data Science Labeling Dataset.
    datasetType String
    Type of the Dataset.
    namespaceName String
    object String
    The object name of the input data file.
    bucket string
    The name of the ObjectStorage bucket that contains the input data file.
    datasetId string
    The OCID of the Data Science Labeling Dataset.
    datasetType string
    Type of the Dataset.
    namespaceName string
    object string
    The object name of the input data file.
    bucket str
    The name of the ObjectStorage bucket that contains the input data file.
    dataset_id str
    The OCID of the Data Science Labeling Dataset.
    dataset_type str
    Type of the Dataset.
    namespace_name str
    object str
    The object name of the input data file.
    bucket String
    The name of the ObjectStorage bucket that contains the input data file.
    datasetId String
    The OCID of the Data Science Labeling Dataset.
    datasetType String
    Type of the Dataset.
    namespaceName String
    object String
    The object name of the input data file.

    GetModelsModelCollectionItemValidationDataset

    Bucket string
    The name of the ObjectStorage bucket that contains the input data file.
    DatasetId string
    The OCID of the Data Science Labeling Dataset.
    DatasetType string
    Type of the Dataset.
    NamespaceName string
    Object string
    The object name of the input data file.
    Bucket string
    The name of the ObjectStorage bucket that contains the input data file.
    DatasetId string
    The OCID of the Data Science Labeling Dataset.
    DatasetType string
    Type of the Dataset.
    NamespaceName string
    Object string
    The object name of the input data file.
    bucket String
    The name of the ObjectStorage bucket that contains the input data file.
    datasetId String
    The OCID of the Data Science Labeling Dataset.
    datasetType String
    Type of the Dataset.
    namespaceName String
    object String
    The object name of the input data file.
    bucket string
    The name of the ObjectStorage bucket that contains the input data file.
    datasetId string
    The OCID of the Data Science Labeling Dataset.
    datasetType string
    Type of the Dataset.
    namespaceName string
    object string
    The object name of the input data file.
    bucket str
    The name of the ObjectStorage bucket that contains the input data file.
    dataset_id str
    The OCID of the Data Science Labeling Dataset.
    dataset_type str
    Type of the Dataset.
    namespace_name str
    object str
    The object name of the input data file.
    bucket String
    The name of the ObjectStorage bucket that contains the input data file.
    datasetId String
    The OCID of the Data Science Labeling Dataset.
    datasetType String
    Type of the Dataset.
    namespaceName String
    object String
    The object name of the input data file.

    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 v1.40.0 published on Wednesday, Jun 12, 2024 by Pulumi