Oracle Cloud Infrastructure

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

getModel

This data source provides details about a specific Model resource in Oracle Cloud Infrastructure Ai Vision service.

Gets a Model by identifier

Example Usage

using Pulumi;
using Oci = Pulumi.Oci;

class MyStack : Stack
{
    public MyStack()
    {
        var testModel = Output.Create(Oci.AiVision.GetModel.InvokeAsync(new Oci.AiVision.GetModelArgs
        {
            ModelId = oci_ai_vision_model.Test_model.Id,
        }));
    }

}
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.GetModel(ctx, &aivision.GetModelArgs{
			ModelId: oci_ai_vision_model.Test_model.Id,
		}, nil)
		if err != nil {
			return err
		}
		return nil
	})
}

Coming soon!

import pulumi
import pulumi_oci as oci

test_model = oci.AiVision.get_model(model_id=oci_ai_vision_model["test_model"]["id"])
import * as pulumi from "@pulumi/pulumi";
import * as oci from "@pulumi/oci";

const testModel = oci.AiVision.getModel({
    modelId: oci_ai_vision_model.test_model.id,
});

Coming soon!

Using getModel

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 getModel(args: GetModelArgs, opts?: InvokeOptions): Promise<GetModelResult>
function getModelOutput(args: GetModelOutputArgs, opts?: InvokeOptions): Output<GetModelResult>
def get_model(model_id: Optional[str] = None,
              opts: Optional[InvokeOptions] = None) -> GetModelResult
def get_model_output(model_id: Optional[pulumi.Input[str]] = None,
              opts: Optional[InvokeOptions] = None) -> Output[GetModelResult]
func GetModel(ctx *Context, args *GetModelArgs, opts ...InvokeOption) (*GetModelResult, error)
func GetModelOutput(ctx *Context, args *GetModelOutputArgs, opts ...InvokeOption) GetModelResultOutput

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

public static class GetModel 
{
    public static Task<GetModelResult> InvokeAsync(GetModelArgs args, InvokeOptions? opts = null)
    public static Output<GetModelResult> Invoke(GetModelInvokeArgs args, InvokeOptions? opts = null)
}
public static CompletableFuture<GetModelResult> getModel(GetModelArgs args, InvokeOptions options)
// Output-based functions aren't available in Java yet
Fn::Invoke:
  Function: oci:AiVision/getModel:getModel
  Arguments:
    # Arguments dictionary

The following arguments are supported:

ModelId string

unique Model identifier

ModelId string

unique Model identifier

modelId String

unique Model identifier

modelId string

unique Model identifier

model_id str

unique Model identifier

modelId String

unique Model identifier

getModel Result

The following output properties are available:

AveragePrecision double

Average precision of the trained model

CompartmentId string

Compartment Identifier

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

Model Identifier, can be renamed

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 identifier that is immutable on creation

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

ModelId string
ModelType string

Type of the Model.

ModelVersion string

The version of the model

Precision double

Precision of the trained model

ProjectId string

The OCID of the project to associate with the model.

Recall double

Recall of the trained model

State string

The current state of the Model.

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<GetModelTestingDataset>

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<GetModelTrainingDataset>

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

ValidationDatasets List<GetModelValidationDataset>

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

AveragePrecision float64

Average precision of the trained model

CompartmentId string

Compartment Identifier

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

Model Identifier, can be renamed

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 identifier that is immutable on creation

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

ModelId string
ModelType string

Type of the Model.

ModelVersion string

The version of the model

Precision float64

Precision of the trained model

ProjectId string

The OCID of the project to associate with the model.

Recall float64

Recall of the trained model

State string

The current state of the Model.

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 []GetModelTestingDataset

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 []GetModelTrainingDataset

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

ValidationDatasets []GetModelValidationDataset

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

averagePrecision Double

Average precision of the trained model

compartmentId String

Compartment Identifier

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

Model Identifier, can be renamed

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 identifier that is immutable on creation

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

modelId String
modelType String

Type of the Model.

modelVersion String

The version of the model

precision Double

Precision of the trained model

projectId String

The OCID of the project to associate with the model.

recall Double

Recall of the trained model

state String

The current state of the Model.

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<GetModelTestingDataset>

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<GetModelTrainingDataset>

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

validationDatasets List<GetModelValidationDataset>

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

averagePrecision number

Average precision of the trained model

compartmentId string

Compartment Identifier

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

Model Identifier, can be renamed

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 identifier that is immutable on creation

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

modelId string
modelType string

Type of the Model.

modelVersion string

The version of the model

precision number

Precision of the trained model

projectId string

The OCID of the project to associate with the model.

recall number

Recall of the trained model

state string

The current state of the Model.

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 GetModelTestingDataset[]

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 GetModelTrainingDataset[]

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

validationDatasets GetModelValidationDataset[]

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

Compartment Identifier

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

Model Identifier, can be renamed

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 identifier that is immutable on creation

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_id str
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 OCID of the project to associate with the model.

recall float

Recall of the trained model

state str

The current state of the Model.

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 GetModelTestingDataset]

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 GetModelTrainingDataset]

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

validation_datasets GetModelValidationDataset]

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

averagePrecision Number

Average precision of the trained model

compartmentId String

Compartment Identifier

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

Model Identifier, can be renamed

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 identifier that is immutable on creation

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

modelId String
modelType String

Type of the Model.

modelVersion String

The version of the model

precision Number

Precision of the trained model

projectId String

The OCID of the project to associate with the model.

recall Number

Recall of the trained model

state String

The current state of the Model.

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.

Supporting Types

GetModelTestingDataset

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.

GetModelTrainingDataset

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.

GetModelValidationDataset

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.