Cloud AI Platform v1 API - Class PredictionServiceClient (2.12.0)

public abstract class PredictionServiceClient

Reference documentation and code samples for the Cloud AI Platform v1 API class PredictionServiceClient.

PredictionService client wrapper, for convenient use.

Inheritance

object > PredictionServiceClient

Namespace

GoogleCloudGoogle.Cloud.AIPlatformV1

Assembly

Google.Cloud.AIPlatform.V1.dll

Remarks

A service for online predictions and explanations.

Properties

DefaultEndpoint

public static string DefaultEndpoint { get; }

The default endpoint for the PredictionService service, which is a host of "aiplatform.googleapis.com" and a port of 443.

Property Value
TypeDescription
string

DefaultScopes

public static IReadOnlyList<string> DefaultScopes { get; }

The default PredictionService scopes.

Property Value
TypeDescription
IReadOnlyListstring
Remarks

The default PredictionService scopes are:

GrpcClient

public virtual PredictionService.PredictionServiceClient GrpcClient { get; }

The underlying gRPC PredictionService client

Property Value
TypeDescription
PredictionServicePredictionServiceClient

IAMPolicyClient

public virtual IAMPolicyClient IAMPolicyClient { get; }

The IAMPolicyClient associated with this client.

Property Value
TypeDescription
IAMPolicyClient

LocationsClient

public virtual LocationsClient LocationsClient { get; }

The LocationsClient associated with this client.

Property Value
TypeDescription
LocationsClient

ServiceMetadata

public static ServiceMetadata ServiceMetadata { get; }

The service metadata associated with this client type.

Property Value
TypeDescription
ServiceMetadata

Methods

Create()

public static PredictionServiceClient Create()

Synchronously creates a PredictionServiceClient using the default credentials, endpoint and settings. To specify custom credentials or other settings, use PredictionServiceClientBuilder.

Returns
TypeDescription
PredictionServiceClient

The created PredictionServiceClient.

CreateAsync(CancellationToken)

public static Task<PredictionServiceClient> CreateAsync(CancellationToken cancellationToken = default)

Asynchronously creates a PredictionServiceClient using the default credentials, endpoint and settings. To specify custom credentials or other settings, use PredictionServiceClientBuilder.

Parameter
NameDescription
cancellationTokenCancellationToken

The CancellationToken to use while creating the client.

Returns
TypeDescription
TaskPredictionServiceClient

The task representing the created PredictionServiceClient.

Explain(EndpointName, IEnumerable<Value>, Value, string, CallSettings)

public virtual ExplainResponse Explain(EndpointName endpoint, IEnumerable<Value> instances, Value parameters, string deployedModelId, CallSettings callSettings = null)

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only deployed AutoML tabular Models have explanation_spec.

Parameters
NameDescription
endpointEndpointName

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesIEnumerableValue

Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

parametersValue

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].

deployedModelIdstring

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].

callSettingsCallSettings

If not null, applies overrides to this RPC call.

Returns
TypeDescription
ExplainResponse

The RPC response.

Example
// Create client
PredictionServiceClient predictionServiceClient = PredictionServiceClient.Create();
// Initialize request argument(s)
EndpointName endpoint = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
IEnumerable<Value> instances = new Value[] { new Value(), };
Value parameters = new Value();
string deployedModelId = "";
// Make the request
ExplainResponse response = predictionServiceClient.Explain(endpoint, instances, parameters, deployedModelId);

Explain(ExplainRequest, CallSettings)

public virtual ExplainResponse Explain(ExplainRequest request, CallSettings callSettings = null)

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only deployed AutoML tabular Models have explanation_spec.

Parameters
NameDescription
requestExplainRequest

The request object containing all of the parameters for the API call.

callSettingsCallSettings

If not null, applies overrides to this RPC call.

Returns
TypeDescription
ExplainResponse

The RPC response.

Example
// Create client
PredictionServiceClient predictionServiceClient = PredictionServiceClient.Create();
// Initialize request argument(s)
ExplainRequest request = new ExplainRequest
{
    EndpointAsEndpointName = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]"),
    Instances = { new Value(), },
    DeployedModelId = "",
    Parameters = new Value(),
    ExplanationSpecOverride = new ExplanationSpecOverride(),
};
// Make the request
ExplainResponse response = predictionServiceClient.Explain(request);

Explain(string, IEnumerable<Value>, Value, string, CallSettings)

public virtual ExplainResponse Explain(string endpoint, IEnumerable<Value> instances, Value parameters, string deployedModelId, CallSettings callSettings = null)

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only deployed AutoML tabular Models have explanation_spec.

Parameters
NameDescription
endpointstring

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesIEnumerableValue

Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

parametersValue

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].

deployedModelIdstring

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].

callSettingsCallSettings

If not null, applies overrides to this RPC call.

Returns
TypeDescription
ExplainResponse

The RPC response.

Example
// Create client
PredictionServiceClient predictionServiceClient = PredictionServiceClient.Create();
// Initialize request argument(s)
string endpoint = "projects/[PROJECT]/locations/[LOCATION]/endpoints/[ENDPOINT]";
IEnumerable<Value> instances = new Value[] { new Value(), };
Value parameters = new Value();
string deployedModelId = "";
// Make the request
ExplainResponse response = predictionServiceClient.Explain(endpoint, instances, parameters, deployedModelId);

ExplainAsync(EndpointName, IEnumerable<Value>, Value, string, CallSettings)

public virtual Task<ExplainResponse> ExplainAsync(EndpointName endpoint, IEnumerable<Value> instances, Value parameters, string deployedModelId, CallSettings callSettings = null)

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only deployed AutoML tabular Models have explanation_spec.

Parameters
NameDescription
endpointEndpointName

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesIEnumerableValue

Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

parametersValue

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].

deployedModelIdstring

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].

callSettingsCallSettings

If not null, applies overrides to this RPC call.

Returns
TypeDescription
TaskExplainResponse

A Task containing the RPC response.

Example
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
EndpointName endpoint = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
IEnumerable<Value> instances = new Value[] { new Value(), };
Value parameters = new Value();
string deployedModelId = "";
// Make the request
ExplainResponse response = await predictionServiceClient.ExplainAsync(endpoint, instances, parameters, deployedModelId);

ExplainAsync(EndpointName, IEnumerable<Value>, Value, string, CancellationToken)

public virtual Task<ExplainResponse> ExplainAsync(EndpointName endpoint, IEnumerable<Value> instances, Value parameters, string deployedModelId, CancellationToken cancellationToken)

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only deployed AutoML tabular Models have explanation_spec.

Parameters
NameDescription
endpointEndpointName

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesIEnumerableValue

Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

parametersValue

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].

deployedModelIdstring

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].

cancellationTokenCancellationToken

A CancellationToken to use for this RPC.

Returns
TypeDescription
TaskExplainResponse

A Task containing the RPC response.

Example
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
EndpointName endpoint = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
IEnumerable<Value> instances = new Value[] { new Value(), };
Value parameters = new Value();
string deployedModelId = "";
// Make the request
ExplainResponse response = await predictionServiceClient.ExplainAsync(endpoint, instances, parameters, deployedModelId);

ExplainAsync(ExplainRequest, CallSettings)

public virtual Task<ExplainResponse> ExplainAsync(ExplainRequest request, CallSettings callSettings = null)

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only deployed AutoML tabular Models have explanation_spec.

Parameters
NameDescription
requestExplainRequest

The request object containing all of the parameters for the API call.

callSettingsCallSettings

If not null, applies overrides to this RPC call.

Returns
TypeDescription
TaskExplainResponse

A Task containing the RPC response.

Example
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
ExplainRequest request = new ExplainRequest
{
    EndpointAsEndpointName = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]"),
    Instances = { new Value(), },
    DeployedModelId = "",
    Parameters = new Value(),
    ExplanationSpecOverride = new ExplanationSpecOverride(),
};
// Make the request
ExplainResponse response = await predictionServiceClient.ExplainAsync(request);

ExplainAsync(ExplainRequest, CancellationToken)

public virtual Task<ExplainResponse> ExplainAsync(ExplainRequest request, CancellationToken cancellationToken)

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only deployed AutoML tabular Models have explanation_spec.

Parameters
NameDescription
requestExplainRequest

The request object containing all of the parameters for the API call.

cancellationTokenCancellationToken

A CancellationToken to use for this RPC.

Returns
TypeDescription
TaskExplainResponse

A Task containing the RPC response.

Example
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
ExplainRequest request = new ExplainRequest
{
    EndpointAsEndpointName = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]"),
    Instances = { new Value(), },
    DeployedModelId = "",
    Parameters = new Value(),
    ExplanationSpecOverride = new ExplanationSpecOverride(),
};
// Make the request
ExplainResponse response = await predictionServiceClient.ExplainAsync(request);

ExplainAsync(string, IEnumerable<Value>, Value, string, CallSettings)

public virtual Task<ExplainResponse> ExplainAsync(string endpoint, IEnumerable<Value> instances, Value parameters, string deployedModelId, CallSettings callSettings = null)

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only deployed AutoML tabular Models have explanation_spec.

Parameters
NameDescription
endpointstring

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesIEnumerableValue

Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

parametersValue

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].

deployedModelIdstring

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].

callSettingsCallSettings

If not null, applies overrides to this RPC call.

Returns
TypeDescription
TaskExplainResponse

A Task containing the RPC response.

Example
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
string endpoint = "projects/[PROJECT]/locations/[LOCATION]/endpoints/[ENDPOINT]";
IEnumerable<Value> instances = new Value[] { new Value(), };
Value parameters = new Value();
string deployedModelId = "";
// Make the request
ExplainResponse response = await predictionServiceClient.ExplainAsync(endpoint, instances, parameters, deployedModelId);

ExplainAsync(string, IEnumerable<Value>, Value, string, CancellationToken)

public virtual Task<ExplainResponse> ExplainAsync(string endpoint, IEnumerable<Value> instances, Value parameters, string deployedModelId, CancellationToken cancellationToken)

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only deployed AutoML tabular Models have explanation_spec.

Parameters
NameDescription
endpointstring

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesIEnumerableValue

Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

parametersValue

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].

deployedModelIdstring

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].

cancellationTokenCancellationToken

A CancellationToken to use for this RPC.

Returns
TypeDescription
TaskExplainResponse

A Task containing the RPC response.

Example
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
string endpoint = "projects/[PROJECT]/locations/[LOCATION]/endpoints/[ENDPOINT]";
IEnumerable<Value> instances = new Value[] { new Value(), };
Value parameters = new Value();
string deployedModelId = "";
// Make the request
ExplainResponse response = await predictionServiceClient.ExplainAsync(endpoint, instances, parameters, deployedModelId);

Predict(EndpointName, IEnumerable<Value>, Value, CallSettings)

public virtual PredictResponse Predict(EndpointName endpoint, IEnumerable<Value> instances, Value parameters, CallSettings callSettings = null)

Perform an online prediction.

Parameters
NameDescription
endpointEndpointName

Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesIEnumerableValue

Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

parametersValue

The parameters that govern the