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Packagesoci.AiVision.Model
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This resource provides the Model resource in Oracle Cloud Infrastructure Ai Vision service.
Creates a new Model.
Example Usage
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Oci = Pulumi.Oci;
return await Deployment.RunAsync(() =>
{
var testModel = new Oci.AiVision.Model("testModel", new()
{
CompartmentId = @var.Compartment_id,
ModelType = @var.Model_model_type,
ProjectId = oci_ai_vision_project.Test_project.Id,
TrainingDataset = new Oci.AiVision.Inputs.ModelTrainingDatasetArgs
{
DatasetType = @var.Model_training_dataset_dataset_type,
Bucket = @var.Model_training_dataset_bucket,
DatasetId = oci_data_labeling_service_dataset.Test_dataset.Id,
NamespaceName = @var.Model_training_dataset_namespace,
Object = @var.Model_training_dataset_object,
},
DefinedTags =
{
{ "foo-namespace.bar-key", "value" },
},
Description = @var.Model_description,
DisplayName = @var.Model_display_name,
FreeformTags =
{
{ "bar-key", "value" },
},
IsQuickMode = @var.Model_is_quick_mode,
MaxTrainingDurationInHours = @var.Model_max_training_duration_in_hours,
ModelVersion = @var.Model_model_version,
TestingDataset = new Oci.AiVision.Inputs.ModelTestingDatasetArgs
{
DatasetType = @var.Model_testing_dataset_dataset_type,
Bucket = @var.Model_testing_dataset_bucket,
DatasetId = oci_data_labeling_service_dataset.Test_dataset.Id,
NamespaceName = @var.Model_testing_dataset_namespace,
Object = @var.Model_testing_dataset_object,
},
ValidationDataset = new Oci.AiVision.Inputs.ModelValidationDatasetArgs
{
DatasetType = @var.Model_validation_dataset_dataset_type,
Bucket = @var.Model_validation_dataset_bucket,
DatasetId = oci_data_labeling_service_dataset.Test_dataset.Id,
NamespaceName = @var.Model_validation_dataset_namespace,
Object = @var.Model_validation_dataset_object,
},
});
});
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.NewModel(ctx, "testModel", &AiVision.ModelArgs{
CompartmentId: pulumi.Any(_var.Compartment_id),
ModelType: pulumi.Any(_var.Model_model_type),
ProjectId: pulumi.Any(oci_ai_vision_project.Test_project.Id),
TrainingDataset: &aivision.ModelTrainingDatasetArgs{
DatasetType: pulumi.Any(_var.Model_training_dataset_dataset_type),
Bucket: pulumi.Any(_var.Model_training_dataset_bucket),
DatasetId: pulumi.Any(oci_data_labeling_service_dataset.Test_dataset.Id),
NamespaceName: pulumi.Any(_var.Model_training_dataset_namespace),
Object: pulumi.Any(_var.Model_training_dataset_object),
},
DefinedTags: pulumi.AnyMap{
"foo-namespace.bar-key": pulumi.Any("value"),
},
Description: pulumi.Any(_var.Model_description),
DisplayName: pulumi.Any(_var.Model_display_name),
FreeformTags: pulumi.AnyMap{
"bar-key": pulumi.Any("value"),
},
IsQuickMode: pulumi.Any(_var.Model_is_quick_mode),
MaxTrainingDurationInHours: pulumi.Any(_var.Model_max_training_duration_in_hours),
ModelVersion: pulumi.Any(_var.Model_model_version),
TestingDataset: &aivision.ModelTestingDatasetArgs{
DatasetType: pulumi.Any(_var.Model_testing_dataset_dataset_type),
Bucket: pulumi.Any(_var.Model_testing_dataset_bucket),
DatasetId: pulumi.Any(oci_data_labeling_service_dataset.Test_dataset.Id),
NamespaceName: pulumi.Any(_var.Model_testing_dataset_namespace),
Object: pulumi.Any(_var.Model_testing_dataset_object),
},
ValidationDataset: &aivision.ModelValidationDatasetArgs{
DatasetType: pulumi.Any(_var.Model_validation_dataset_dataset_type),
Bucket: pulumi.Any(_var.Model_validation_dataset_bucket),
DatasetId: pulumi.Any(oci_data_labeling_service_dataset.Test_dataset.Id),
NamespaceName: pulumi.Any(_var.Model_validation_dataset_namespace),
Object: pulumi.Any(_var.Model_validation_dataset_object),
},
})
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.Model;
import com.pulumi.oci.AiVision.ModelArgs;
import com.pulumi.oci.AiVision.inputs.ModelTrainingDatasetArgs;
import com.pulumi.oci.AiVision.inputs.ModelTestingDatasetArgs;
import com.pulumi.oci.AiVision.inputs.ModelValidationDatasetArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var testModel = new Model("testModel", ModelArgs.builder()
.compartmentId(var_.compartment_id())
.modelType(var_.model_model_type())
.projectId(oci_ai_vision_project.test_project().id())
.trainingDataset(ModelTrainingDatasetArgs.builder()
.datasetType(var_.model_training_dataset_dataset_type())
.bucket(var_.model_training_dataset_bucket())
.datasetId(oci_data_labeling_service_dataset.test_dataset().id())
.namespaceName(var_.model_training_dataset_namespace())
.object(var_.model_training_dataset_object())
.build())
.definedTags(Map.of("foo-namespace.bar-key", "value"))
.description(var_.model_description())
.displayName(var_.model_display_name())
.freeformTags(Map.of("bar-key", "value"))
.isQuickMode(var_.model_is_quick_mode())
.maxTrainingDurationInHours(var_.model_max_training_duration_in_hours())
.modelVersion(var_.model_model_version())
.testingDataset(ModelTestingDatasetArgs.builder()
.datasetType(var_.model_testing_dataset_dataset_type())
.bucket(var_.model_testing_dataset_bucket())
.datasetId(oci_data_labeling_service_dataset.test_dataset().id())
.namespaceName(var_.model_testing_dataset_namespace())
.object(var_.model_testing_dataset_object())
.build())
.validationDataset(ModelValidationDatasetArgs.builder()
.datasetType(var_.model_validation_dataset_dataset_type())
.bucket(var_.model_validation_dataset_bucket())
.datasetId(oci_data_labeling_service_dataset.test_dataset().id())
.namespaceName(var_.model_validation_dataset_namespace())
.object(var_.model_validation_dataset_object())
.build())
.build());
}
}
import pulumi
import pulumi_oci as oci
test_model = oci.ai_vision.Model("testModel",
compartment_id=var["compartment_id"],
model_type=var["model_model_type"],
project_id=oci_ai_vision_project["test_project"]["id"],
training_dataset=oci.ai_vision.ModelTrainingDatasetArgs(
dataset_type=var["model_training_dataset_dataset_type"],
bucket=var["model_training_dataset_bucket"],
dataset_id=oci_data_labeling_service_dataset["test_dataset"]["id"],
namespace_name=var["model_training_dataset_namespace"],
object=var["model_training_dataset_object"],
),
defined_tags={
"foo-namespace.bar-key": "value",
},
description=var["model_description"],
display_name=var["model_display_name"],
freeform_tags={
"bar-key": "value",
},
is_quick_mode=var["model_is_quick_mode"],
max_training_duration_in_hours=var["model_max_training_duration_in_hours"],
model_version=var["model_model_version"],
testing_dataset=oci.ai_vision.ModelTestingDatasetArgs(
dataset_type=var["model_testing_dataset_dataset_type"],
bucket=var["model_testing_dataset_bucket"],
dataset_id=oci_data_labeling_service_dataset["test_dataset"]["id"],
namespace_name=var["model_testing_dataset_namespace"],
object=var["model_testing_dataset_object"],
),
validation_dataset=oci.ai_vision.ModelValidationDatasetArgs(
dataset_type=var["model_validation_dataset_dataset_type"],
bucket=var["model_validation_dataset_bucket"],
dataset_id=oci_data_labeling_service_dataset["test_dataset"]["id"],
namespace_name=var["model_validation_dataset_namespace"],
object=var["model_validation_dataset_object"],
))
import * as pulumi from "@pulumi/pulumi";
import * as oci from "@pulumi/oci";
const testModel = new oci.aivision.Model("testModel", {
compartmentId: _var.compartment_id,
modelType: _var.model_model_type,
projectId: oci_ai_vision_project.test_project.id,
trainingDataset: {
datasetType: _var.model_training_dataset_dataset_type,
bucket: _var.model_training_dataset_bucket,
datasetId: oci_data_labeling_service_dataset.test_dataset.id,
namespaceName: _var.model_training_dataset_namespace,
object: _var.model_training_dataset_object,
},
definedTags: {
"foo-namespace.bar-key": "value",
},
description: _var.model_description,
displayName: _var.model_display_name,
freeformTags: {
"bar-key": "value",
},
isQuickMode: _var.model_is_quick_mode,
maxTrainingDurationInHours: _var.model_max_training_duration_in_hours,
modelVersion: _var.model_model_version,
testingDataset: {
datasetType: _var.model_testing_dataset_dataset_type,
bucket: _var.model_testing_dataset_bucket,
datasetId: oci_data_labeling_service_dataset.test_dataset.id,
namespaceName: _var.model_testing_dataset_namespace,
object: _var.model_testing_dataset_object,
},
validationDataset: {
datasetType: _var.model_validation_dataset_dataset_type,
bucket: _var.model_validation_dataset_bucket,
datasetId: oci_data_labeling_service_dataset.test_dataset.id,
namespaceName: _var.model_validation_dataset_namespace,
object: _var.model_validation_dataset_object,
},
});
resources:
testModel:
type: oci:AiVision:Model
properties:
#Required
compartmentId: ${var.compartment_id}
modelType: ${var.model_model_type}
projectId: ${oci_ai_vision_project.test_project.id}
trainingDataset:
datasetType: ${var.model_training_dataset_dataset_type}
bucket: ${var.model_training_dataset_bucket}
datasetId: ${oci_data_labeling_service_dataset.test_dataset.id}
namespaceName: ${var.model_training_dataset_namespace}
object: ${var.model_training_dataset_object}
#Optional
definedTags:
foo-namespace.bar-key: value
description: ${var.model_description}
displayName: ${var.model_display_name}
freeformTags:
bar-key: value
isQuickMode: ${var.model_is_quick_mode}
maxTrainingDurationInHours: ${var.model_max_training_duration_in_hours}
modelVersion: ${var.model_model_version}
testingDataset:
datasetType: ${var.model_testing_dataset_dataset_type}
bucket: ${var.model_testing_dataset_bucket}
datasetId: ${oci_data_labeling_service_dataset.test_dataset.id}
namespaceName: ${var.model_testing_dataset_namespace}
object: ${var.model_testing_dataset_object}
validationDataset:
datasetType: ${var.model_validation_dataset_dataset_type}
bucket: ${var.model_validation_dataset_bucket}
datasetId: ${oci_data_labeling_service_dataset.test_dataset.id}
namespaceName: ${var.model_validation_dataset_namespace}
object: ${var.model_validation_dataset_object}
Create Model Resource
new Model(name: string, args: ModelArgs, opts?: CustomResourceOptions);@overload
def Model(resource_name: str,
opts: Optional[ResourceOptions] = None,
compartment_id: Optional[str] = None,
defined_tags: Optional[Mapping[str, Any]] = None,
description: Optional[str] = None,
display_name: Optional[str] = None,
freeform_tags: Optional[Mapping[str, Any]] = None,
is_quick_mode: Optional[bool] = None,
max_training_duration_in_hours: Optional[float] = None,
model_type: Optional[str] = None,
model_version: Optional[str] = None,
project_id: Optional[str] = None,
testing_dataset: Optional[_aivision.ModelTestingDatasetArgs] = None,
training_dataset: Optional[_aivision.ModelTrainingDatasetArgs] = None,
validation_dataset: Optional[_aivision.ModelValidationDatasetArgs] = None)
@overload
def Model(resource_name: str,
args: ModelArgs,
opts: Optional[ResourceOptions] = None)func NewModel(ctx *Context, name string, args ModelArgs, opts ...ResourceOption) (*Model, error)public Model(string name, ModelArgs args, CustomResourceOptions? opts = null)type: oci:AiVision:Model
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args ModelArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args ModelArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args ModelArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args ModelArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args ModelArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Model Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
The Model resource accepts the following input properties:
- Compartment
Id string (Updatable) Compartment Identifier
- Model
Type string The type of the model.
- Project
Id string The OCID of the project to associate with the model.
- Training
Dataset ModelTraining Dataset The base entity for a Dataset, which is the input for Model creation.
- Dictionary<string, object>
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- Description string
(Updatable) A short description of the Model.
- Display
Name string (Updatable) Model Identifier
- Dictionary<string, object>
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- Is
Quick boolMode If It's true, Training is set for recommended epochs needed for quick training.
- Max
Training doubleDuration In Hours The maximum duration in hours for which the training will run.
- Model
Version string Model version.
- Testing
Dataset ModelTesting Dataset The base entity for a Dataset, which is the input for Model creation.
- Validation
Dataset ModelValidation Dataset The base entity for a Dataset, which is the input for Model creation.
- Compartment
Id string (Updatable) Compartment Identifier
- Model
Type string The type of the model.
- Project
Id string The OCID of the project to associate with the model.
- Training
Dataset ModelTraining Dataset Args The base entity for a Dataset, which is the input for Model creation.
- map[string]interface{}
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- Description string
(Updatable) A short description of the Model.
- Display
Name string (Updatable) Model Identifier
- map[string]interface{}
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- Is
Quick boolMode If It's true, Training is set for recommended epochs needed for quick training.
- Max
Training float64Duration In Hours The maximum duration in hours for which the training will run.
- Model
Version string Model version.
- Testing
Dataset ModelTesting Dataset Args The base entity for a Dataset, which is the input for Model creation.
- Validation
Dataset ModelValidation Dataset Args The base entity for a Dataset, which is the input for Model creation.
- compartment
Id String (Updatable) Compartment Identifier
- model
Type String The type of the model.
- project
Id String The OCID of the project to associate with the model.
- training
Dataset ModelTraining Dataset The base entity for a Dataset, which is the input for Model creation.
- Map<String,Object>
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- description String
(Updatable) A short description of the Model.
- display
Name String (Updatable) Model Identifier
- Map<String,Object>
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- is
Quick BooleanMode If It's true, Training is set for recommended epochs needed for quick training.
- max
Training DoubleDuration In Hours The maximum duration in hours for which the training will run.
- model
Version String Model version.
- testing
Dataset ModelTesting Dataset The base entity for a Dataset, which is the input for Model creation.
- validation
Dataset ModelValidation Dataset The base entity for a Dataset, which is the input for Model creation.
- compartment
Id string (Updatable) Compartment Identifier
- model
Type string The type of the model.
- project
Id string The OCID of the project to associate with the model.
- training
Dataset ModelTraining Dataset The base entity for a Dataset, which is the input for Model creation.
- {[key: string]: any}
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- description string
(Updatable) A short description of the Model.
- display
Name string (Updatable) Model Identifier
- {[key: string]: any}
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- is
Quick booleanMode If It's true, Training is set for recommended epochs needed for quick training.
- max
Training numberDuration In Hours The maximum duration in hours for which the training will run.
- model
Version string Model version.
- testing
Dataset ModelTesting Dataset The base entity for a Dataset, which is the input for Model creation.
- validation
Dataset ModelValidation Dataset The base entity for a Dataset, which is the input for Model creation.
- compartment_
id str (Updatable) Compartment Identifier
- model_
type str The type of the model.
- project_
id str The OCID of the project to associate with the model.
- training_
dataset ModelTraining Dataset Args The base entity for a Dataset, which is the input for Model creation.
- Mapping[str, Any]
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- description str
(Updatable) A short description of the Model.
- display_
name str (Updatable) Model Identifier
- Mapping[str, Any]
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- is_
quick_ boolmode If It's true, Training is set for recommended epochs needed for quick training.
- max_
training_ floatduration_ in_ hours The maximum duration in hours for which the training will run.
- model_
version str Model version.
- testing_
dataset ModelTesting Dataset Args The base entity for a Dataset, which is the input for Model creation.
- validation_
dataset ModelValidation Dataset Args The base entity for a Dataset, which is the input for Model creation.
- compartment
Id String (Updatable) Compartment Identifier
- model
Type String The type of the model.
- project
Id String The OCID of the project to associate with the model.
- training
Dataset Property Map The base entity for a Dataset, which is the input for Model creation.
- Map<Any>
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- description String
(Updatable) A short description of the Model.
- display
Name String (Updatable) Model Identifier
- Map<Any>
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- is
Quick BooleanMode If It's true, Training is set for recommended epochs needed for quick training.
- max
Training NumberDuration In Hours The maximum duration in hours for which the training will run.
- model
Version String Model version.
- testing
Dataset Property Map The base entity for a Dataset, which is the input for Model creation.
- validation
Dataset Property Map The base entity for a Dataset, which is the input for Model creation.
Outputs
All input properties are implicitly available as output properties. Additionally, the Model resource produces the following output properties:
- Average
Precision double Average precision of the trained model
- Confidence
Threshold double Confidence ratio of the calculation
- Id string
The provider-assigned unique ID for this managed resource.
- Lifecycle
Details 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.
- Metrics string
Complete Training Metrics for successful trained model
- Precision double
Precision of the trained model
- Recall double
Recall of the trained model
- State string
The current state of the Model.
- Dictionary<string, object>
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- Test
Image intCount Total number of testing Images
- Time
Created string The time the Model was created. An RFC3339 formatted datetime string
- Time
Updated string The time the Model was updated. An RFC3339 formatted datetime string
- Total
Image intCount Total number of training Images
- Trained
Duration doubleIn Hours Total hours actually used for training
- Average
Precision float64 Average precision of the trained model
- Confidence
Threshold float64 Confidence ratio of the calculation
- Id string
The provider-assigned unique ID for this managed resource.
- Lifecycle
Details 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.
- Metrics string
Complete Training Metrics for successful trained model
- Precision float64
Precision of the trained model
- Recall float64
Recall of the trained model
- State string
The current state of the Model.
- map[string]interface{}
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- Test
Image intCount Total number of testing Images
- Time
Created string The time the Model was created. An RFC3339 formatted datetime string
- Time
Updated string The time the Model was updated. An RFC3339 formatted datetime string
- Total
Image intCount Total number of training Images
- Trained
Duration float64In Hours Total hours actually used for training
- average
Precision Double Average precision of the trained model
- confidence
Threshold Double Confidence ratio of the calculation
- id String
The provider-assigned unique ID for this managed resource.
- lifecycle
Details 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.
- metrics String
Complete Training Metrics for successful trained model
- precision Double
Precision of the trained model
- recall Double
Recall of the trained model
- state String
The current state of the Model.
- Map<String,Object>
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- test
Image IntegerCount Total number of testing Images
- time
Created String The time the Model was created. An RFC3339 formatted datetime string
- time
Updated String The time the Model was updated. An RFC3339 formatted datetime string
- total
Image IntegerCount Total number of training Images
- trained
Duration DoubleIn Hours Total hours actually used for training
- average
Precision number Average precision of the trained model
- confidence
Threshold number Confidence ratio of the calculation
- id string
The provider-assigned unique ID for this managed resource.
- lifecycle
Details 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.
- metrics string
Complete Training Metrics for successful trained model
- precision number
Precision of the trained model
- recall number
Recall of the trained model
- state string
The current state of the Model.
- {[key: string]: any}
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- test
Image numberCount Total number of testing Images
- time
Created string The time the Model was created. An RFC3339 formatted datetime string
- time
Updated string The time the Model was updated. An RFC3339 formatted datetime string
- total
Image numberCount Total number of training Images
- trained
Duration numberIn Hours Total hours actually used for training
- average_
precision float Average precision of the trained model
- confidence_
threshold float Confidence ratio of the calculation
- id str
The provider-assigned unique ID for this managed resource.
- 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.
- metrics str
Complete Training Metrics for successful trained model
- precision float
Precision of the trained model
- recall float
Recall of the trained model
- state str
The current state of the Model.
- Mapping[str, Any]
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- test_
image_ intcount Total number of testing Images
- 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_ intcount Total number of training Images
- trained_
duration_ floatin_ hours Total hours actually used for training
- average
Precision Number Average precision of the trained model
- confidence
Threshold Number Confidence ratio of the calculation
- id String
The provider-assigned unique ID for this managed resource.
- lifecycle
Details 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.
- metrics String
Complete Training Metrics for successful trained model
- precision Number
Precision of the trained model
- recall Number
Recall of the trained model
- state String
The current state of the Model.
- Map<Any>
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- test
Image NumberCount Total number of testing Images
- time
Created String The time the Model was created. An RFC3339 formatted datetime string
- time
Updated String The time the Model was updated. An RFC3339 formatted datetime string
- total
Image NumberCount Total number of training Images
- trained
Duration NumberIn Hours Total hours actually used for training
Look up Existing Model Resource
Get an existing Model resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.
public static get(name: string, id: Input<ID>, state?: ModelState, opts?: CustomResourceOptions): Model@staticmethod
def get(resource_name: str,
id: str,
opts: Optional[ResourceOptions] = None,
average_precision: Optional[float] = None,
compartment_id: Optional[str] = None,
confidence_threshold: Optional[float] = None,
defined_tags: Optional[Mapping[str, Any]] = None,
description: Optional[str] = None,
display_name: Optional[str] = None,
freeform_tags: Optional[Mapping[str, Any]] = None,
is_quick_mode: Optional[bool] = None,
lifecycle_details: Optional[str] = None,
max_training_duration_in_hours: Optional[float] = None,
metrics: Optional[str] = None,
model_type: Optional[str] = None,
model_version: Optional[str] = None,
precision: Optional[float] = None,
project_id: Optional[str] = None,
recall: Optional[float] = None,
state: Optional[str] = None,
system_tags: Optional[Mapping[str, Any]] = None,
test_image_count: Optional[int] = None,
testing_dataset: Optional[_aivision.ModelTestingDatasetArgs] = None,
time_created: Optional[str] = None,
time_updated: Optional[str] = None,
total_image_count: Optional[int] = None,
trained_duration_in_hours: Optional[float] = None,
training_dataset: Optional[_aivision.ModelTrainingDatasetArgs] = None,
validation_dataset: Optional[_aivision.ModelValidationDatasetArgs] = None) -> Modelfunc GetModel(ctx *Context, name string, id IDInput, state *ModelState, opts ...ResourceOption) (*Model, error)public static Model Get(string name, Input<string> id, ModelState? state, CustomResourceOptions? opts = null)public static Model get(String name, Output<String> id, ModelState state, CustomResourceOptions options)Resource lookup is not supported in YAML- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- resource_name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- Average
Precision double Average precision of the trained model
- Compartment
Id string (Updatable) Compartment Identifier
- Confidence
Threshold double Confidence ratio of the calculation
- Dictionary<string, object>
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- Description string
(Updatable) A short description of the Model.
- Display
Name string (Updatable) Model Identifier
- Dictionary<string, object>
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- Is
Quick boolMode If It's true, Training is set for recommended epochs needed for quick training.
- Lifecycle
Details 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.
- Max
Training doubleDuration In Hours The maximum duration in hours for which the training will run.
- Metrics string
Complete Training Metrics for successful trained model
- Model
Type string The type of the model.
- Model
Version string Model version.
- Precision double
Precision of the trained model
- Project
Id 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.
- Dictionary<string, object>
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- Test
Image intCount Total number of testing Images
- Testing
Dataset ModelTesting Dataset The base entity for a Dataset, which is the input for Model creation.
- Time
Created string The time the Model was created. An RFC3339 formatted datetime string
- Time
Updated string The time the Model was updated. An RFC3339 formatted datetime string
- Total
Image intCount Total number of training Images
- Trained
Duration doubleIn Hours Total hours actually used for training
- Training
Dataset ModelTraining Dataset The base entity for a Dataset, which is the input for Model creation.
- Validation
Dataset ModelValidation Dataset The base entity for a Dataset, which is the input for Model creation.
- Average
Precision float64 Average precision of the trained model
- Compartment
Id string (Updatable) Compartment Identifier
- Confidence
Threshold float64 Confidence ratio of the calculation
- map[string]interface{}
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- Description string
(Updatable) A short description of the Model.
- Display
Name string (Updatable) Model Identifier
- map[string]interface{}
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- Is
Quick boolMode If It's true, Training is set for recommended epochs needed for quick training.
- Lifecycle
Details 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.
- Max
Training float64Duration In Hours The maximum duration in hours for which the training will run.
- Metrics string
Complete Training Metrics for successful trained model
- Model
Type string The type of the model.
- Model
Version string Model version.
- Precision float64
Precision of the trained model
- Project
Id 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.
- map[string]interface{}
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- Test
Image intCount Total number of testing Images
- Testing
Dataset ModelTesting Dataset Args The base entity for a Dataset, which is the input for Model creation.
- Time
Created string The time the Model was created. An RFC3339 formatted datetime string
- Time
Updated string The time the Model was updated. An RFC3339 formatted datetime string
- Total
Image intCount Total number of training Images
- Trained
Duration float64In Hours Total hours actually used for training
- Training
Dataset ModelTraining Dataset Args The base entity for a Dataset, which is the input for Model creation.
- Validation
Dataset ModelValidation Dataset Args The base entity for a Dataset, which is the input for Model creation.
- average
Precision Double Average precision of the trained model
- compartment
Id String (Updatable) Compartment Identifier
- confidence
Threshold Double Confidence ratio of the calculation
- Map<String,Object>
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- description String
(Updatable) A short description of the Model.
- display
Name String (Updatable) Model Identifier
- Map<String,Object>
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- is
Quick BooleanMode If It's true, Training is set for recommended epochs needed for quick training.
- lifecycle
Details 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.
- max
Training DoubleDuration In Hours The maximum duration in hours for which the training will run.
- metrics String
Complete Training Metrics for successful trained model
- model
Type String The type of the model.
- model
Version String Model version.
- precision Double
Precision of the trained model
- project
Id 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.
- Map<String,Object>
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- test
Image IntegerCount Total number of testing Images
- testing
Dataset ModelTesting Dataset The base entity for a Dataset, which is the input for Model creation.
- time
Created String The time the Model was created. An RFC3339 formatted datetime string
- time
Updated String The time the Model was updated. An RFC3339 formatted datetime string
- total
Image IntegerCount Total number of training Images
- trained
Duration DoubleIn Hours Total hours actually used for training
- training
Dataset ModelTraining Dataset The base entity for a Dataset, which is the input for Model creation.
- validation
Dataset ModelValidation Dataset The base entity for a Dataset, which is the input for Model creation.
- average
Precision number Average precision of the trained model
- compartment
Id string (Updatable) Compartment Identifier
- confidence
Threshold number Confidence ratio of the calculation
- {[key: string]: any}
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- description string
(Updatable) A short description of the Model.
- display
Name string (Updatable) Model Identifier
- {[key: string]: any}
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- is
Quick booleanMode If It's true, Training is set for recommended epochs needed for quick training.
- lifecycle
Details 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.
- max
Training numberDuration In Hours The maximum duration in hours for which the training will run.
- metrics string
Complete Training Metrics for successful trained model
- model
Type string The type of the model.
- model
Version string Model version.
- precision number
Precision of the trained model
- project
Id 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.
- {[key: string]: any}
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- test
Image numberCount Total number of testing Images
- testing
Dataset ModelTesting Dataset The base entity for a Dataset, which is the input for Model creation.
- time
Created string The time the Model was created. An RFC3339 formatted datetime string
- time
Updated string The time the Model was updated. An RFC3339 formatted datetime string
- total
Image numberCount Total number of training Images
- trained
Duration numberIn Hours Total hours actually used for training
- training
Dataset ModelTraining Dataset The base entity for a Dataset, which is the input for Model creation.
- validation
Dataset ModelValidation Dataset 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 (Updatable) Compartment Identifier
- confidence_
threshold float Confidence ratio of the calculation
- Mapping[str, Any]
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- description str
(Updatable) A short description of the Model.
- display_
name str (Updatable) Model Identifier
- Mapping[str, Any]
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- is_
quick_ boolmode 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_ floatduration_ in_ hours The maximum duration in hours for which the training will run.
- metrics str
Complete Training Metrics for successful trained model
- model_
type str The type of the model.
- model_
version str Model version.
- 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.
- Mapping[str, Any]
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- test_
image_ intcount Total number of testing Images
- testing_
dataset ModelTesting Dataset Args 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_ intcount Total number of training Images
- trained_
duration_ floatin_ hours Total hours actually used for training
- training_
dataset ModelTraining Dataset Args The base entity for a Dataset, which is the input for Model creation.
- validation_
dataset ModelValidation Dataset Args The base entity for a Dataset, which is the input for Model creation.
- average
Precision Number Average precision of the trained model
- compartment
Id String (Updatable) Compartment Identifier
- confidence
Threshold Number Confidence ratio of the calculation
- Map<Any>
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}- description String
(Updatable) A short description of the Model.
- display
Name String (Updatable) Model Identifier
- Map<Any>
(Updatable) Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}- is
Quick BooleanMode If It's true, Training is set for recommended epochs needed for quick training.
- lifecycle
Details 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.
- max
Training NumberDuration In Hours The maximum duration in hours for which the training will run.
- metrics String
Complete Training Metrics for successful trained model
- model
Type String The type of the model.
- model
Version String Model version.
- precision Number
Precision of the trained model
- project
Id 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.
- Map<Any>
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}- test
Image NumberCount Total number of testing Images
- testing
Dataset Property Map The base entity for a Dataset, which is the input for Model creation.
- time
Created String The time the Model was created. An RFC3339 formatted datetime string
- time
Updated String The time the Model was updated. An RFC3339 formatted datetime string
- total
Image NumberCount Total number of training Images
- trained
Duration NumberIn Hours Total hours actually used for training
- training
Dataset Property Map The base entity for a Dataset, which is the input for Model creation.
- validation
Dataset Property Map The base entity for a Dataset, which is the input for Model creation.
Supporting Types
ModelTestingDataset, ModelTestingDatasetArgs
- Dataset
Type string Type of the Dataset.
- Bucket string
The name of the ObjectStorage bucket that contains the input data file.
- Dataset
Id string The OCID of the Data Science Labeling Dataset.
- Namespace
Name string The namespace name of the ObjectStorage bucket that contains the input data file.
- Object string
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- Dataset
Type string Type of the Dataset.
- Bucket string
The name of the ObjectStorage bucket that contains the input data file.
- Dataset
Id string The OCID of the Data Science Labeling Dataset.
- Namespace
Name string The namespace name of the ObjectStorage bucket that contains the input data file.
- Object string
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset
Type String Type of the Dataset.
- bucket String
The name of the ObjectStorage bucket that contains the input data file.
- dataset
Id String The OCID of the Data Science Labeling Dataset.
- namespace
Name String The namespace name of the ObjectStorage bucket that contains the input data file.
- object String
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset
Type string Type of the Dataset.
- bucket string
The name of the ObjectStorage bucket that contains the input data file.
- dataset
Id string The OCID of the Data Science Labeling Dataset.
- namespace
Name string The namespace name of the ObjectStorage bucket that contains the input data file.
- object string
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset_
type str Type of the Dataset.
- 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.
- namespace_
name str The namespace name of the ObjectStorage bucket that contains the input data file.
- object str
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset
Type String Type of the Dataset.
- bucket String
The name of the ObjectStorage bucket that contains the input data file.
- dataset
Id String The OCID of the Data Science Labeling Dataset.
- namespace
Name String The namespace name of the ObjectStorage bucket that contains the input data file.
- object String
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
ModelTrainingDataset, ModelTrainingDatasetArgs
- Dataset
Type string Type of the Dataset.
- Bucket string
The name of the ObjectStorage bucket that contains the input data file.
- Dataset
Id string The OCID of the Data Science Labeling Dataset.
- Namespace
Name string The namespace name of the ObjectStorage bucket that contains the input data file.
- Object string
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- Dataset
Type string Type of the Dataset.
- Bucket string
The name of the ObjectStorage bucket that contains the input data file.
- Dataset
Id string The OCID of the Data Science Labeling Dataset.
- Namespace
Name string The namespace name of the ObjectStorage bucket that contains the input data file.
- Object string
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset
Type String Type of the Dataset.
- bucket String
The name of the ObjectStorage bucket that contains the input data file.
- dataset
Id String The OCID of the Data Science Labeling Dataset.
- namespace
Name String The namespace name of the ObjectStorage bucket that contains the input data file.
- object String
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset
Type string Type of the Dataset.
- bucket string
The name of the ObjectStorage bucket that contains the input data file.
- dataset
Id string The OCID of the Data Science Labeling Dataset.
- namespace
Name string The namespace name of the ObjectStorage bucket that contains the input data file.
- object string
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset_
type str Type of the Dataset.
- 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.
- namespace_
name str The namespace name of the ObjectStorage bucket that contains the input data file.
- object str
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset
Type String Type of the Dataset.
- bucket String
The name of the ObjectStorage bucket that contains the input data file.
- dataset
Id String The OCID of the Data Science Labeling Dataset.
- namespace
Name String The namespace name of the ObjectStorage bucket that contains the input data file.
- object String
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
ModelValidationDataset, ModelValidationDatasetArgs
- Dataset
Type string Type of the Dataset.
- Bucket string
The name of the ObjectStorage bucket that contains the input data file.
- Dataset
Id string The OCID of the Data Science Labeling Dataset.
- Namespace
Name string The namespace name of the ObjectStorage bucket that contains the input data file.
- Object string
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- Dataset
Type string Type of the Dataset.
- Bucket string
The name of the ObjectStorage bucket that contains the input data file.
- Dataset
Id string The OCID of the Data Science Labeling Dataset.
- Namespace
Name string The namespace name of the ObjectStorage bucket that contains the input data file.
- Object string
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset
Type String Type of the Dataset.
- bucket String
The name of the ObjectStorage bucket that contains the input data file.
- dataset
Id String The OCID of the Data Science Labeling Dataset.
- namespace
Name String The namespace name of the ObjectStorage bucket that contains the input data file.
- object String
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset
Type string Type of the Dataset.
- bucket string
The name of the ObjectStorage bucket that contains the input data file.
- dataset
Id string The OCID of the Data Science Labeling Dataset.
- namespace
Name string The namespace name of the ObjectStorage bucket that contains the input data file.
- object string
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset_
type str Type of the Dataset.
- 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.
- namespace_
name str The namespace name of the ObjectStorage bucket that contains the input data file.
- object str
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
- dataset
Type String Type of the Dataset.
- bucket String
The name of the ObjectStorage bucket that contains the input data file.
- dataset
Id String The OCID of the Data Science Labeling Dataset.
- namespace
Name String The namespace name of the ObjectStorage bucket that contains the input data file.
- object String
The object name of the input data file.
** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values
Import
Models can be imported using the id, e.g.
$ pulumi import oci:AiVision/model:Model test_model "id"
Package Details
- Repository
- oci pulumi/pulumi-oci
- License
- Apache-2.0
- Notes
This Pulumi package is based on the
ociTerraform Provider.