Oracle Cloud Infrastructure

Pulumi Official
Package maintained by Pulumi
v0.1.1 published on Tuesday, May 3, 2022 by Pulumi

getModels

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

Returns a list of Models.

Example Usage

using Pulumi;
using Oci = Pulumi.Oci;

class MyStack : Stack
{
    public MyStack()
    {
        var testModels = Output.Create(Oci.AiVision.GetModels.InvokeAsync(new Oci.AiVision.GetModelsArgs
        {
            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
	})
}

Coming soon!

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,
});

Coming soon!

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
https://github.com/pulumi/pulumi-oci
License
Apache-2.0
Notes

This Pulumi package is based on the oci Terraform Provider.