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Oracle Cloud Infrastructure v1.10.0 published on Thursday, Sep 7, 2023 by Pulumi

oci.AiVision.getModels

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Oracle Cloud Infrastructure v1.10.0 published on Thursday, Sep 7, 2023 by Pulumi

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

    Returns a list of Models.

    Example Usage

    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 = @var.Compartment_id,
            DisplayName = @var.Model_display_name,
            Id = @var.Model_id,
            ProjectId = oci_ai_vision_project.Test_project.Id,
            State = @var.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(_var.Compartment_id),
    			DisplayName:   pulumi.StringRef(_var.Model_display_name),
    			Id:            pulumi.StringRef(_var.Model_id),
    			ProjectId:     pulumi.StringRef(oci_ai_vision_project.Test_project.Id),
    			State:         pulumi.StringRef(_var.Model_state),
    		}, nil)
    		if err != nil {
    			return err
    		}
    		return nil
    	})
    }
    
    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(var_.compartment_id())
                .displayName(var_.model_display_name())
                .id(var_.model_id())
                .projectId(oci_ai_vision_project.test_project().id())
                .state(var_.model_state())
                .build());
    
        }
    }
    
    import pulumi
    import pulumi_oci as oci
    
    test_models = oci.AiVision.get_models(compartment_id=var["compartment_id"],
        display_name=var["model_display_name"],
        id=var["model_id"],
        project_id=oci_ai_vision_project["test_project"]["id"],
        state=var["model_state"])
    
    import * as pulumi from "@pulumi/pulumi";
    import * as oci from "@pulumi/oci";
    
    const testModels = oci.AiVision.getModels({
        compartmentId: _var.compartment_id,
        displayName: _var.model_display_name,
        id: _var.model_id,
        projectId: oci_ai_vision_project.test_project.id,
        state: _var.model_state,
    });
    
    variables:
      testModels:
        fn::invoke:
          Function: oci:AiVision:getModels
          Arguments:
            compartmentId: ${var.compartment_id}
            displayName: ${var.model_display_name}
            id: ${var.model_id}
            projectId: ${oci_ai_vision_project.test_project.id}
            state: ${var.model_state}
    

    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 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 GetModelsModelCollection]

    The list of model_collection.

    compartment_id str

    Compartment Identifier

    display_name str

    Model Identifier, can be renamed

    filters 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 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 GetModelsModelCollectionItemTrainingDataset]

    The base entity for a Dataset, which is the input for Model creation.

    validation_datasets 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 v1.10.0 published on Thursday, Sep 7, 2023 by Pulumi