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public abstract class PredictionServiceClient
PredictionService client wrapper, for convenient use.
Derived Types
Namespace
Google.Cloud.AIPlatform.V1Assembly
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 | |
---|---|
Type | Description |
String |
DefaultScopes
public static IReadOnlyList<string> DefaultScopes { get; }
The default PredictionService scopes.
Property Value | |
---|---|
Type | Description |
IReadOnlyList<String> |
The default PredictionService scopes are:
GrpcClient
public virtual PredictionService.PredictionServiceClient GrpcClient { get; }
The underlying gRPC PredictionService client
Property Value | |
---|---|
Type | Description |
PredictionService.PredictionServiceClient |
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 | |
---|---|
Type | Description |
PredictionServiceClient | The created PredictionServiceClient. |
CreateAsync(CancellationToken)
public static Task<PredictionServiceClient> CreateAsync(CancellationToken cancellationToken = default(CancellationToken))
Asynchronously creates a PredictionServiceClient using the default credentials, endpoint and settings. To specify custom credentials or other settings, use PredictionServiceClientBuilder.
Parameter | |
---|---|
Name | Description |
cancellationToken | CancellationToken The CancellationToken to use while creating the client. |
Returns | |
---|---|
Type | Description |
Task<PredictionServiceClient> | 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 | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the explanation.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
deployedModelId | String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split]. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
ExplainResponse | The RPC response. |
// 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 | |
---|---|
Name | Description |
request | ExplainRequest The request object containing all of the parameters for the API call. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
ExplainResponse | The RPC response. |
// 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 | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the explanation.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
deployedModelId | String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split]. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
ExplainResponse | The RPC response. |
// 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 | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the explanation.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
deployedModelId | String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split]. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
Task<ExplainResponse> | A Task containing the RPC response. |
// 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 | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the explanation.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
deployedModelId | String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split]. |
cancellationToken | CancellationToken A CancellationToken to use for this RPC. |
Returns | |
---|---|
Type | Description |
Task<ExplainResponse> | A Task containing the RPC response. |
// 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 | |
---|---|
Name | Description |
request | ExplainRequest The request object containing all of the parameters for the API call. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
Task<ExplainResponse> | A Task containing the RPC response. |
// 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 | |
---|---|
Name | Description |
request | ExplainRequest The request object containing all of the parameters for the API call. |
cancellationToken | CancellationToken A CancellationToken to use for this RPC. |
Returns | |
---|---|
Type | Description |
Task<ExplainResponse> | A Task containing the RPC response. |
// 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 | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the explanation.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
deployedModelId | String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split]. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
Task<ExplainResponse> | A Task containing the RPC response. |
// 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 | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the explanation.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
deployedModelId | String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split]. |
cancellationToken | CancellationToken A CancellationToken to use for this RPC. |
Returns | |
---|---|
Type | Description |
Task<ExplainResponse> | A Task containing the RPC response. |
// 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 | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the prediction.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
PredictResponse | The RPC response. |
// 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();
// Make the request
PredictResponse response = predictionServiceClient.Predict(endpoint, instances, parameters);
Predict(PredictRequest, CallSettings)
public virtual PredictResponse Predict(PredictRequest request, CallSettings callSettings = null)
Perform an online prediction.
Parameters | |
---|---|
Name | Description |
request | PredictRequest The request object containing all of the parameters for the API call. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
PredictResponse | The RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = PredictionServiceClient.Create();
// Initialize request argument(s)
PredictRequest request = new PredictRequest
{
EndpointAsEndpointName = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]"),
Instances = { new Value(), },
Parameters = new Value(),
};
// Make the request
PredictResponse response = predictionServiceClient.Predict(request);
Predict(String, IEnumerable<Value>, Value, CallSettings)
public virtual PredictResponse Predict(string endpoint, IEnumerable<Value> instances, Value parameters, CallSettings callSettings = null)
Perform an online prediction.
Parameters | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the prediction.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
PredictResponse | The RPC response. |
// 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();
// Make the request
PredictResponse response = predictionServiceClient.Predict(endpoint, instances, parameters);
PredictAsync(EndpointName, IEnumerable<Value>, Value, CallSettings)
public virtual Task<PredictResponse> PredictAsync(EndpointName endpoint, IEnumerable<Value> instances, Value parameters, CallSettings callSettings = null)
Perform an online prediction.
Parameters | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the prediction.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
Task<PredictResponse> | A Task containing the RPC response. |
// 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();
// Make the request
PredictResponse response = await predictionServiceClient.PredictAsync(endpoint, instances, parameters);
PredictAsync(EndpointName, IEnumerable<Value>, Value, CancellationToken)
public virtual Task<PredictResponse> PredictAsync(EndpointName endpoint, IEnumerable<Value> instances, Value parameters, CancellationToken cancellationToken)
Perform an online prediction.
Parameters | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the prediction.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
cancellationToken | CancellationToken A CancellationToken to use for this RPC. |
Returns | |
---|---|
Type | Description |
Task<PredictResponse> | A Task containing the RPC response. |
// 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();
// Make the request
PredictResponse response = await predictionServiceClient.PredictAsync(endpoint, instances, parameters);
PredictAsync(PredictRequest, CallSettings)
public virtual Task<PredictResponse> PredictAsync(PredictRequest request, CallSettings callSettings = null)
Perform an online prediction.
Parameters | |
---|---|
Name | Description |
request | PredictRequest The request object containing all of the parameters for the API call. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
Task<PredictResponse> | A Task containing the RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
PredictRequest request = new PredictRequest
{
EndpointAsEndpointName = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]"),
Instances = { new Value(), },
Parameters = new Value(),
};
// Make the request
PredictResponse response = await predictionServiceClient.PredictAsync(request);
PredictAsync(PredictRequest, CancellationToken)
public virtual Task<PredictResponse> PredictAsync(PredictRequest request, CancellationToken cancellationToken)
Perform an online prediction.
Parameters | |
---|---|
Name | Description |
request | PredictRequest The request object containing all of the parameters for the API call. |
cancellationToken | CancellationToken A CancellationToken to use for this RPC. |
Returns | |
---|---|
Type | Description |
Task<PredictResponse> | A Task containing the RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
PredictRequest request = new PredictRequest
{
EndpointAsEndpointName = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]"),
Instances = { new Value(), },
Parameters = new Value(),
};
// Make the request
PredictResponse response = await predictionServiceClient.PredictAsync(request);
PredictAsync(String, IEnumerable<Value>, Value, CallSettings)
public virtual Task<PredictResponse> PredictAsync(string endpoint, IEnumerable<Value> instances, Value parameters, CallSettings callSettings = null)
Perform an online prediction.
Parameters | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the prediction.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
Task<PredictResponse> | A Task containing the RPC response. |
// 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();
// Make the request
PredictResponse response = await predictionServiceClient.PredictAsync(endpoint, instances, parameters);
PredictAsync(String, IEnumerable<Value>, Value, CancellationToken)
public virtual Task<PredictResponse> PredictAsync(string endpoint, IEnumerable<Value> instances, Value parameters, CancellationToken cancellationToken)
Perform an online prediction.
Parameters | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the prediction.
Format:
|
instances | IEnumerable<Value> 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]. |
parameters | Value 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]. |
cancellationToken | CancellationToken A CancellationToken to use for this RPC. |
Returns | |
---|---|
Type | Description |
Task<PredictResponse> | A Task containing the RPC response. |
// 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();
// Make the request
PredictResponse response = await predictionServiceClient.PredictAsync(endpoint, instances, parameters);
RawPredict(EndpointName, HttpBody, CallSettings)
public virtual HttpBody RawPredict(EndpointName endpoint, HttpBody httpBody, CallSettings callSettings = null)
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id
: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
Parameters | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the prediction.
Format:
|
httpBody | HttpBody The prediction input. Supports HTTP headers and arbitrary data payload. A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict] method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the
[predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when you deploy the
|
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
HttpBody | The RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = PredictionServiceClient.Create();
// Initialize request argument(s)
EndpointName endpoint = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
HttpBody httpBody = new HttpBody();
// Make the request
HttpBody response = predictionServiceClient.RawPredict(endpoint, httpBody);
RawPredict(RawPredictRequest, CallSettings)
public virtual HttpBody RawPredict(RawPredictRequest request, CallSettings callSettings = null)
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id
: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
Parameters | |
---|---|
Name | Description |
request | RawPredictRequest The request object containing all of the parameters for the API call. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
HttpBody | The RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = PredictionServiceClient.Create();
// Initialize request argument(s)
RawPredictRequest request = new RawPredictRequest
{
EndpointAsEndpointName = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]"),
HttpBody = new HttpBody(),
};
// Make the request
HttpBody response = predictionServiceClient.RawPredict(request);
RawPredict(String, HttpBody, CallSettings)
public virtual HttpBody RawPredict(string endpoint, HttpBody httpBody, CallSettings callSettings = null)
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id
: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
Parameters | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the prediction.
Format:
|
httpBody | HttpBody The prediction input. Supports HTTP headers and arbitrary data payload. A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict] method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the
[predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when you deploy the
|
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
HttpBody | The RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = PredictionServiceClient.Create();
// Initialize request argument(s)
string endpoint = "projects/[PROJECT]/locations/[LOCATION]/endpoints/[ENDPOINT]";
HttpBody httpBody = new HttpBody();
// Make the request
HttpBody response = predictionServiceClient.RawPredict(endpoint, httpBody);
RawPredictAsync(EndpointName, HttpBody, CallSettings)
public virtual Task<HttpBody> RawPredictAsync(EndpointName endpoint, HttpBody httpBody, CallSettings callSettings = null)
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id
: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
Parameters | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the prediction.
Format:
|
httpBody | HttpBody The prediction input. Supports HTTP headers and arbitrary data payload. A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict] method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the
[predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when you deploy the
|
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
Task<HttpBody> | A Task containing the RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
EndpointName endpoint = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
HttpBody httpBody = new HttpBody();
// Make the request
HttpBody response = await predictionServiceClient.RawPredictAsync(endpoint, httpBody);
RawPredictAsync(EndpointName, HttpBody, CancellationToken)
public virtual Task<HttpBody> RawPredictAsync(EndpointName endpoint, HttpBody httpBody, CancellationToken cancellationToken)
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id
: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
Parameters | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the prediction.
Format:
|
httpBody | HttpBody The prediction input. Supports HTTP headers and arbitrary data payload. A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict] method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the
[predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when you deploy the
|
cancellationToken | CancellationToken A CancellationToken to use for this RPC. |
Returns | |
---|---|
Type | Description |
Task<HttpBody> | A Task containing the RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
EndpointName endpoint = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
HttpBody httpBody = new HttpBody();
// Make the request
HttpBody response = await predictionServiceClient.RawPredictAsync(endpoint, httpBody);
RawPredictAsync(RawPredictRequest, CallSettings)
public virtual Task<HttpBody> RawPredictAsync(RawPredictRequest request, CallSettings callSettings = null)
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id
: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
Parameters | |
---|---|
Name | Description |
request | RawPredictRequest The request object containing all of the parameters for the API call. |
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
Task<HttpBody> | A Task containing the RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
RawPredictRequest request = new RawPredictRequest
{
EndpointAsEndpointName = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]"),
HttpBody = new HttpBody(),
};
// Make the request
HttpBody response = await predictionServiceClient.RawPredictAsync(request);
RawPredictAsync(RawPredictRequest, CancellationToken)
public virtual Task<HttpBody> RawPredictAsync(RawPredictRequest request, CancellationToken cancellationToken)
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id
: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
Parameters | |
---|---|
Name | Description |
request | RawPredictRequest The request object containing all of the parameters for the API call. |
cancellationToken | CancellationToken A CancellationToken to use for this RPC. |
Returns | |
---|---|
Type | Description |
Task<HttpBody> | A Task containing the RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
RawPredictRequest request = new RawPredictRequest
{
EndpointAsEndpointName = EndpointName.FromProjectLocationEndpoint("[PROJECT]", "[LOCATION]", "[ENDPOINT]"),
HttpBody = new HttpBody(),
};
// Make the request
HttpBody response = await predictionServiceClient.RawPredictAsync(request);
RawPredictAsync(String, HttpBody, CallSettings)
public virtual Task<HttpBody> RawPredictAsync(string endpoint, HttpBody httpBody, CallSettings callSettings = null)
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id
: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
Parameters | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the prediction.
Format:
|
httpBody | HttpBody The prediction input. Supports HTTP headers and arbitrary data payload. A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict] method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the
[predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when you deploy the
|
callSettings | CallSettings If not null, applies overrides to this RPC call. |
Returns | |
---|---|
Type | Description |
Task<HttpBody> | A Task containing the RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
string endpoint = "projects/[PROJECT]/locations/[LOCATION]/endpoints/[ENDPOINT]";
HttpBody httpBody = new HttpBody();
// Make the request
HttpBody response = await predictionServiceClient.RawPredictAsync(endpoint, httpBody);
RawPredictAsync(String, HttpBody, CancellationToken)
public virtual Task<HttpBody> RawPredictAsync(string endpoint, HttpBody httpBody, CancellationToken cancellationToken)
Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id
: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
Parameters | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the prediction.
Format:
|
httpBody | HttpBody The prediction input. Supports HTTP headers and arbitrary data payload. A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict] method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the
[predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when you deploy the
|
cancellationToken | CancellationToken A CancellationToken to use for this RPC. |
Returns | |
---|---|
Type | Description |
Task<HttpBody> | A Task containing the RPC response. |
// Create client
PredictionServiceClient predictionServiceClient = await PredictionServiceClient.CreateAsync();
// Initialize request argument(s)
string endpoint = "projects/[PROJECT]/locations/[LOCATION]/endpoints/[ENDPOINT]";
HttpBody httpBody = new HttpBody();
// Make the request
HttpBody response = await predictionServiceClient.RawPredictAsync(endpoint, httpBody);
ShutdownDefaultChannelsAsync()
public static Task ShutdownDefaultChannelsAsync()
Shuts down any channels automatically created by Create() and CreateAsync(CancellationToken). Channels which weren't automatically created are not affected.
Returns | |
---|---|
Type | Description |
Task | A task representing the asynchronous shutdown operation. |
After calling this method, further calls to Create() and CreateAsync(CancellationToken) will create new channels, which could in turn be shut down by another call to this method.